Job Search Strategy Beginner

35 ChatGPT prompts for job seekers to reverse-engineer US job descriptions into skill checklists

If you’ve ever stared at a 600-word LinkedIn job posting and thought “what do they actually want from me?” - this is for you. These 35 ChatGPT prompts for reverse-engineering US job description skill checklist work turn any posting into a clean, ranked, ATS-ready skill inventory you can match a resume to in under 20 minutes. I’ve used variations of this playbook to decode postings at Google, Stripe, Anthropic, Pfizer, Deloitte, and a regional hospital network in Ohio. Same framework, different industry.

Here’s the uncomfortable truth. The US Bureau of Labor Statistics reported 7,618,000 job openings on the last business day of April 2026, up from 6,887,000 in March - a 731,000 jump in a single month (BLS JOLTS, June 2 2026). At the same time, LinkedIn’s Jobs on the Rise 2026 report found that 56% of US professionals plan to job-hunt this year, yet 76% say they don’t feel prepared (LinkedIn News, January 7 2026). That’s a 20-point gap between intent and readiness. Most of that gap is hidden inside the job description itself, in plain language nobody is reading carefully.

Pull quote: “US job openings jumped from 6.9M to 7.6M between March and April 2026 - the steepest monthly increase in 18 months. The market is back. Most candidates are not.” - BLS JOLTS, June 2 2026

This guide gives you 35 multi-line prompts across 6 categories: source-collection, skills & tooling, domain & impact, hidden-requirement, scoring & gap, and resume & cover-letter. Each prompt has the full body, an example output, and a pro tip. Paste, edit the bracketed fields, run it in ChatGPT (GPT-4o or GPT-5), Claude 3.5+, or Gemini 2.5 Pro, and ship.

Quick answer: what you’ll get from this guide

If you only have five minutes, this is the headline:

35 detailed ChatGPT prompts grouped into 6 JD-decode categories.
A 4-stage reverse-engineering framework: Source → Skills → Impact → Gap.
A comparison table mapping each prompt category to the JD section it mines.
A 14-day “10 JDs” sprint to overhaul your search in two weeks.
A People Also Ask FAQ that pulls the most-searched 2026 questions.

Skip to the section that matches your stage. If you’re hunting a specific role, start with “Source-collection prompts.” If you’ve got 10 JDs in hand, jump to “Skills & tooling.” If your resume isn’t converting, go to “Resume & cover-letter prompts.”

“Apply blind” means submitting a resume without ever having decoded the specific skills, keywords, and signals the employer is actually scoring against. The cost is brutal: Jobscan’s analysis of more than 10 million US job listings confirms that 99% of Fortune 500 companies use an Applicant Tracking System (ATS) to filter candidates before a human ever sees a resume (Jobscan, 2026). If your resume doesn’t mirror the JD’s keyword set, you don’t get interviews. You get silence.

The numbers are stark:

LinkedIn reports that 76% of US professionals feel unprepared for the current job market, even though 56% plan to look (LinkedIn News, January 7 2026).
BLS data shows 1,715,000 job openings in Professional and Business Services alone in April 2026 - the highest of any sector (BLS JOLTS, June 2 2026).
Jobscan’s research found communication skills appear on more than 35% of US job postings - the single most-listed transferable skill (Jobscan, October 17 2024).
The West region had 1,914,000 job openings in April 2026, a 439,000 jump from March - the largest regional move in the dataset (BLS JOLTS, June 2 2026).

Most candidates skim a JD for 30 seconds, attach a generic resume, and wonder why they never hear back. The 20% who do get interviews are doing one thing differently: they treat the JD as a spec sheet, not a wishlist. The prompts below teach you that exact skill.

The 4-stage JD-decoding framework

JD-decoding is the practice of breaking a job description into structured components - source signals, hard skills, impact metrics, and hidden requirements - so you can match a resume, cover letter, and interview story to it with surgical precision. The framework below is the spine every prompt in this guide hangs off of.

Stage 1 - Source. Collect the JD from multiple channels (LinkedIn, Indeed, the company career page, BuiltIn, Wellfound, Hired, Greenhouse/Lever-hosted boards). Companies often ship different versions of the same role, and the career page version is usually the truest.

Stage 2 - Skills & Tools. Extract every hard skill, software, framework, certification, and methodology. Bucket them into must-have, nice-to-have, and “soft signal” (buzzwords that show the company’s culture).

Stage 3 - Domain & Impact. Translate “what you’d do” into “what you’d ship.” A JD says “own the onboarding funnel”; you decode that to mean activation rate, day-7 retention, and 2+ cross-functional stakeholders.

Stage 4 - Hidden Requirements. Read between the lines. “Fast-paced” often means understaffed. “Rockstar” often means 24/7 on-call. “Competitive salary” often means below-market base with heavy variable comp. The hidden layer is where offers live or die.

Run every prompt below with that four-stage lens and you will out-read 80% of the applicant pool on day one.

Stage 1 prompts: source collection (prompts 1–5)

The first mistake people make is decoding a single JD copy. The better move is to gather three to five versions of the same role, across channels, so you can spot what the hiring manager actually cares about. These prompts handle sourcing and deduplication.

Prompt 1 - Multi-channel JD harvester

Purpose: Pull every public version of a target role into one normalized brief so you can compare the language a recruiter uses on LinkedIn versus what the hiring manager posted on Greenhouse.

You are a job-description research analyst. I'm targeting the role of [JOB TITLE] at [COMPANY NAME].

Collect and compare the following 5 versions of this JD:
1. LinkedIn job posting (paste URL or full text below)
2. Indeed / Glassdoor posting (paste URL or full text)
3. Company career page (paste URL or full text)
4. BuiltIn / Wellfound / Hired posting (paste URL or full text)
5. Greenhouse / Lever / Workday-hosted posting (paste URL or full text)

For each version, output:
- Job title (exact, as posted)
- Location & remote/hybrid policy
- Years of experience required
- Must-have skills (exact phrases used)
- Nice-to-have skills
- Salary range (if disclosed)
- Reporting line (manager title if visible)
- Application deadline

Then, in a 6th section, give me a "Delta Report": what is consistently mentioned across ALL 5 sources (the "core") and what differs between sources (the "noise"). I want to apply based on the core, not the noise.

Example output (truncated):

Core (5/5 sources): “5+ years product management,” “SQL fluency,” “experience with experimentation frameworks,” “excellent written communication.” Noise: LinkedIn says “hybrid 3 days”; Indeed says “remote-first”; BuiltIn says “NYC or SF.” Apply to the local JD, mention flexibility.

Pro tip: Save the Delta Report as a Notion page or Google Doc. When you tailor your resume, you’re tailoring to the core, not the loudest source.

Prompt 2 - JD freshness and posting-age check

Purpose: Some JDs have been up for 200+ days. The role is often already filled or paused. This prompt makes that visible before you invest hours.

I have a LinkedIn job posting URL: [URL]
I have an Indeed posting URL: [URL]

Based on the post date, the number of applicants visible, and the language used (e.g., "actively reviewing," "recently posted," "no longer accepting applications"), tell me:

1. How old is this posting, in days, on each platform?
2. Is it likely still actively hiring, on hold, or stale?
3. How many other candidates have likely applied already (estimate range based on platform norms)?
4. Should I prioritize this role, apply as a stretch, or skip it?
5. What's the best time of day/week to apply to maximize recruiter visibility?

Reason step by step.

Example output:

LinkedIn post is 41 days old, 230+ applicants - moderate competition, still active. Indeed copy is 3 days old, 12 applicants - early window. Apply on the company career page first, then mirror to LinkedIn and Indeed within 24 hours.

Pro tip: Posting age is the single biggest predictor of recruiter fatigue. If a JD is older than 90 days and still up, it usually means hiring manager and recruiter are misaligned - expect a slow process.

Prompt 3 - Recruiter and hiring-manager intel pull

Purpose: Find the actual humans behind the JD on LinkedIn. A warm intro to either one doubles your interview rate.

I am applying for [JOB TITLE] at [COMPANY NAME] (location: [CITY]).

Find me:
1. The in-house recruiter or talent partner most likely owning this req (search LinkedIn for "[company] recruiter [function]" and "[company] talent partner [city]").
2. The hiring manager (search "[title] at [company] [city]" and "[team] lead [company]").
3. Their most recent 3 LinkedIn posts and what those posts tell me about the team's current priorities.
4. A 2-sentence opener I could use in a LinkedIn connection request that's relevant, not generic.
5. One piece of public content they've shared (article, podcast, talk) I can reference to show I did my homework.

Output in a table with columns: Name, Title, LinkedIn URL, Last Post Topic, Suggested Opener.

Example output:

Priya M., Senior Recruiter at [Company], posted 3 days ago about hiring 4 PMs in Q3. Suggested opener: “Saw your post on Q3 PM hiring - I’d love to learn what kinds of product problems the team is solving this half.”

Pro tip: Never use these openers to ask for a job. Ask for a 15-minute “tour of the team’s roadmap” or a 1-question gut check on your background. The job ask comes after.

Prompt 4 - Salary benchmark triangulation

Purpose: Stop guessing what the role pays. Triangulate from three angles before you negotiate.

For the role of [JOB TITLE] at [COMPANY NAME] in [CITY / REMOTE], based on:
1. The salary band disclosed in the JD (if any)
2. Levels.fyi / Glassdoor / Comparably / Pave / Carta public data
3. BLS Occupational Employment Statistics for the relevant SOC code

Give me:
- Low / median / high base salary
- Total compensation range including equity and bonus
- Whether the band is below, at, or above market for 2026
- 3 bullet points I can use to negotiate if the first offer is below the median
- A short script for asking about the band in the recruiter screen without revealing my current comp

Cite the source for each data point.

Example output:

Base: $148K–$182K (median $165K). Total comp: $210K–$290K with 0.05%–0.12% equity. Below market for SF senior PM at this stage; the 75th percentile is closer to $205K base. Negotiation lever: competing offer or counter against a public band.

Pro tip: Always share the band, not your number, when asked. “I’m targeting the upper half of the band for this role, which I understand to be $X–$Y. Is that aligned with how this req is scoped?” is the only line you need.

Prompt 5 - JD archive and version control

Purpose: JDs change while you apply. This prompt builds a snapshot log so you can prove you matched the original posting, not whatever the company edited last Tuesday.

I am applying to [JOB TITLE] at [COMPANY NAME] on [DATE].
Paste the full JD text below:

[JD TEXT]

Do the following:
1. Generate a unique JD-ID (e.g., "COMPANY-ROLE-2026-06-11-A").
2. Hash the posting (first 12 chars of an MD5 of the full text) so I can detect later edits.
3. Extract every keyword and skill, then rank them by frequency (top 30 in a table).
4. Output a "Skills Snapshot" JSON I can save alongside my resume:

{
  "jd_id": "...",
  "hash": "...",
  "applied_date": "2026-06-11",
  "must_have_skills": [...],
  "nice_to_have_skills": [...],
  "tools_mentioned": [...],
  "soft_signals": [...]
}

5. Flag any contradictory or unusual phrasing in the JD (e.g., "junior" + "10 years experience").

Example output:

JD-ID: STRIPE-PM-2026-06-11-A. Hash: 9c4a7e1b2d8f. Must-haves: SQL, experimentation, cross-functional leadership, B2B SaaS, 5+ years PM.

Pro tip: Re-pull the JD every 7 days until you hear back. If the company edits it after you apply, you’ll know whether to refresh your resume or not.

Stage 2 prompts: skills & tooling (prompts 6–11)

Now you’ve got the JD in clean form. The next six prompts turn the text into a structured skill inventory. This is the single highest-leverage step - Jobscan’s data shows hard skills are weighted first in ATS match-rate scoring (Jobscan, 2026).

Prompt 6 - Full skill inventory extractor

Purpose: Convert the JD prose into a flat list of every skill, tool, and qualification, ranked by how often the JD leans on each.

Take the JD below and produce a complete Skill Inventory.

[JD TEXT]

Output three sections:

1. **Hard Skills (technical)** - list every specific technical skill, software, tool, language, framework, methodology, or domain knowledge. Include the count of mentions in the JD.

2. **Soft Skills (interpersonal)** - list every soft skill (e.g., "cross-functional collaboration," "executive presence"). Include mention count.

3. **Implicit / Industry Skills** - list skills that the JD assumes but doesn't name (e.g., if it says "B2B SaaS GTM," the implicit skill is "channel partner management").

For each, output:
| Skill | Category | Mentions | Importance (1–5) | Where in JD it appears (responsibilities / qualifications / about / nice-to-have) |

Sort by Importance descending.

Example output:

SQL (Hard, 4 mentions, 5★) → Experimentation (Hard, 3 mentions, 5★) → Cross-functional collaboration (Soft, 3 mentions, 4★) → B2B SaaS GTM (Implicit, 0 mentions but heavily implied, 4★)

Pro tip: Apply the “Importance × Mentions” lens. A skill mentioned once in the qualifications line-up is often more critical than a skill mentioned three times in the company boilerplate.

Prompt 7 - ATS keyword extractor (for Jobscan / Resume Worded style scoring)

Purpose: Pull only the keywords an ATS would actually score on, so you can hit Jobscan’s recommended 75% match rate without keyword-stuffing.

From the JD below, extract the exact keyword set an ATS will likely score my resume against.

[JD TEXT]

Output:
1. **Exact-match keywords** - phrases the JD uses verbatim (e.g., "Python," "stakeholder management"). Format as a comma-separated list.
2. **Acronyms & full forms** - for each acronym, also list its long form (e.g., "ATS = Applicant Tracking System," "GTM = Go-to-Market").
3. **Synonyms I can swap in** - for each keyword, list 2–3 synonyms I might already use on my resume that the ATS may or may not treat as a match (e.g., "PM" vs "Product Manager" vs "Product Management").
4. **Stop-words to ignore** - words that look like keywords but won't affect ATS scoring (e.g., "the," "will," "team," "passionate").
5. **A safe keyword density target** - for a one-page resume, how many of these exact-match keywords should I include? (Jobscan guidance is 75%+ match; I want a target like 18–22 hard-skill mentions.)

Be ruthless: if it's vague or fluffy, exclude it.

Example output:

Exact-match: “SQL,” “A/B testing,” “Tableau,” “cross-functional,” “stakeholder management,” “B2B SaaS,” “0-to-1,” “product strategy.” Target: 20 hard-skill mentions across the resume.

Pro tip: Run your draft resume through Jobscan’s free scanner. If you’re under 60% match, paste both the JD and the resume into ChatGPT and ask it to suggest neutral, honest keyword insertions (never lie about skills).

Prompt 8 - Tooling & stack decoder

Purpose: A JD that says “experience with modern data stack” is hiding 6–8 specific tools. This prompt surfaces them.

From the JD below, identify every specific tool, software, platform, language, framework, and methodology mentioned or strongly implied.

[JD TEXT]

Output:
1. **Explicit tools** (named directly) - table: Tool | Category | Required vs. Nice-to-have | Years typically expected
2. **Implicit tools** (implied by phrases like "modern data stack," "MLOps pipeline," "design system") - list with the phrase that implies them
3. **Tools that are functionally interchangeable** - group tools that an employer would treat as equivalent (e.g., "Looker ≡ Tableau ≡ Mode," "LangChain ≡ LlamaIndex," "Postgres ≡ MySQL")
4. **My coverage map** - given the list above, give me 3 categories I might already cover and 2 I should brush up on. Don't suggest new tools; just help me see overlap.

Reasoning should be explicit. If you can't infer a tool, say "uncertain" rather than guess.

Example output:

Explicit: SQL, Python, dbt, Snowflake, Looker, Amplitude, Amplitude Experiment. Implied (via “MLOps”): Airflow, Docker, basic Kubernetes. Interchangeable: Tableau ≡ Looker. Coverage: I have SQL+Python+Snowflake already; I need to get specific on dbt and Amplitude.

Pro tip: If you don’t have hands-on time with a “must-have” tool, the honest move is to acknowledge it in the cover letter (“proficient in X, ramping on Y”) and link to a 30-day learning plan. Hiring managers respect honesty more than bluff.

Prompt 9 - Years-of-experience reality check

Purpose: “5+ years” doesn’t always mean 5 years. Sometimes it means 3 with the right industry, sometimes it means 7 with a specific tool. This prompt decodes the actual ask.

The JD below says: [PASTE YEARS-OF-EXPERIENCE LINE]

[JD TEXT]

Tell me:
1. The literal minimum (e.g., "5 years")
2. The likely *real* minimum based on context (industry, seniority signals, comp, role scope) - e.g., "3 years with strong B2B SaaS + experimentation is probably the practical floor"
3. The likely "stretch" range - what would put me in the top quartile of applicants
4. Whether this role is more about depth (specialist) or breadth (generalist)
5. Three resume signals that would let me apply *as if* I had 2 fewer years (e.g., "shipped 2+ products 0-to-1," "managed a $1M+ budget," "mentored 3+ junior PMs")
6. Whether the years line is "hard floor" or "soft signal" (some companies use years as a proxy, not a rule)

Cite the JD line you're decoding.

Example output:

Literal: 5+ years. Real: 3+ years with B2B SaaS at a growth-stage company. Stretch: 6+ years with team management. Hard floor: probably no - they used the same line in their 2025 JD for a role they hired at 3.5 years.

Pro tip: LinkedIn’s algorithm down-ranks applicants whose profile headline doesn’t match the role’s seniority signal. If you have 3.5 years and the JD says 5+, lead your headline with the level (“Senior PM | 4 years”) not the gap.

Prompt 10 - Certification & education decoder

Purpose: Most JD education lines are soft. This prompt tells you when they’re hard and when you can skip them.

From the JD below, decode the education and certification lines.

[JD TEXT]

For each requirement (degree, certification, license), output:
| Requirement | Stated? | Hard floor or soft signal? | What proves it without the literal credential | Risk if I apply without it |

Then, list:
- 3 alternative credentials that are functionally equivalent (e.g., "AWS Solutions Architect" vs "AWS Cloud Practitioner" - sometimes the lower cert is enough)
- 1–2 ways to surface relevant learning *in lieu of* the credential (e.g., "Built an LLM-powered side project using X," "Completed Y on Coursera")
- Whether the company's industry (regulated: finance, healthcare, gov) makes the credential a legal requirement vs. a preference

Reason step by step.

Example output:

“Bachelor’s degree in CS or related” - soft signal. Risk: low for a senior IC. “AWS Solutions Architect Professional” - hard floor for the cloud team. Risk: high if I don’t have it.

Pro tip: Many JDs at places like Stripe, Plaid, and Anthropic say “Bachelor’s or equivalent practical experience.” If you can show equivalent practical experience (open-source, side projects, teaching), the line usually doesn’t filter you out.

Prompt 11 - Seniority calibration

Purpose: “Senior” at one company is “Staff” at another. This prompt places the role on a known ladder so you can pitch yourself at the right altitude.

The JD below is for [JOB TITLE] at [COMPANY NAME].

[JD TEXT]

Using common US tech ladders (e.g., Google L3–L8, Meta E3–E7, Amazon L4–L7, plus general industry levels: Junior, Mid, Senior, Staff, Principal, Director, VP), tell me:

1. The internal level this role most closely maps to (e.g., "L5 / Senior IC, with 1–2 reports implied")
2. The expected scope (people managed, $ budget, customers touched, OKRs owned)
3. The expected comp band (base + equity) at the 50th percentile
4. Three signals in the JD that scream "senior" and three that scream "mid"
5. The closest alternative titles at peer companies (e.g., "Senior PM at Stripe ≈ Product Lead at Linear ≈ Senior PM at Notion")
6. Whether the scope matches the title or if it's a "title inflation" role (e.g., a "Head of" posting that's really a senior IC role)

Be honest about uncertainty.

Example output:

Maps to L5 / Senior PM (Stripe), E5 (Meta), L6 (Amazon). Scope: 0–2 reports, $5M+ business, 1 flagship product line. Comp: $185K base / 0.08% / 15% bonus. Title is honest.

Pro tip: Calibrate the comp band before the recruiter screen. If the band is below your floor, withdraw early. Don’t waste cycles on roles that can’t pay your number.

Stage 3 prompts: domain & impact (prompts 12–17)

Skills are the what. Impact is the why it matters. This is the layer that separates “matches the JD” from “wins the interview.” These prompts force the JD to translate from job duties to business outcomes.

Prompt 12 - Day-in-the-life reconstruction

Purpose: JDs list duties. Recruiters think in stories. Reconstruct the actual week-to-week so you can speak to it in the screen.

The JD below is for [JOB TITLE] at [COMPANY NAME].

[JD TEXT]

Reconstruct what a real week looks like in this role, based on the JD's responsibilities, the team structure, and the company's stage.

Output:
- **Monday morning** - what does the person walk into?
- **Daily rhythms** - meetings, deep work, customer time, code/PR, write-ups
- **Weekly cadence** - 1:1s, team standup, OKR review, customer interviews
- **Monthly / quarterly** - launches, planning cycles, offsites, all-hands
- **The single highest-stakes moment** in a typical quarter (e.g., a launch, a board review, a customer escalation)
- **The single most unglamorous task** that takes 20% of the week (e.g., Jira cleanup, weekly status emails, ticket triage)
- **3 "shadow questions"** the hiring manager will probably ask in the screen (e.g., "Tell me about a time you turned around a stalled project")

Be specific. Use the company name and product where possible.

Example output:

Monday: standup at 9:30 PT, then 2 hours of customer call synthesis. Highest-stakes moment: monthly OKR review with the VP. Unglamorous: triaging ~30 Linear tickets a week.

Pro tip: Bring this reconstruction into your prep doc. When the recruiter asks “what questions do you have?” you can ask sharp, specific things like “How is the weekly OKR review structured?” - that signal alone is worth 5 extra points.

Prompt 13 - Business-impact translator

Purpose: “Own the onboarding funnel” doesn’t say what’s at stake. Translate every responsibility into a metric, a dollar, or a strategic outcome.

For each responsibility listed in the JD below, translate it into:
- The **business metric** it most likely moves (e.g., activation rate, NRR, CAC payback, NPS)
- The **stakeholder** it impacts (e.g., VP Eng, Head of Sales, CSMs)
- The **failure mode** if it's done poorly (e.g., "missed launch = $2M ARR slip")
- The **success mode** if it's done well (e.g., "shipped 4 weeks early = $400K saved")

Then, group all responsibilities into 3 buckets:
- **Revenue-direct** (directly tied to ARR or NRR)
- **Revenue-adjacent** (improves retention, efficiency, brand)
- **Revenue-infrastructure** (builds the systems that future revenue depends on)

[JD TEXT]

Example output:

“Run the experimentation roadmap” → Activation rate (+3 pts target) → VP Growth → failure: roadmap slips, OKRs missed → success: 2 shipped experiments lift weekly actives by 8%. Bucket: Revenue-direct.

Pro tip: In your interview, lead with the impact you drove, not the duty you held. “Owned the onboarding funnel” loses to “moved activation from 32% to 47% in 6 months by redesigning the email cadence.”

Prompt 14 - Cross-functional stakeholder map

Purpose: Every role lives in a web. Map the web before the screen so you can talk fluently about who you’d partner with.

Based on the JD below, map the cross-functional stakeholders this role will work with most often.

[JD TEXT]

Output a 2-axis matrix:
- X-axis: **Internal vs. External**
- Y-axis: **Daily vs. Monthly**

For each cell, list the specific roles (e.g., "Eng Manager," "Brand Designer," "Enterprise AE," "Customer Success Lead"). Include:
- The shared deliverable (what you'd hand them / what they'd hand you)
- The political dynamic to be aware of (e.g., "Eng will push back on launch dates; Sales will push for more features")
- One sentence on how to build trust with that stakeholder in the first 30 days

Then, list the **3 stakeholders I should explicitly name in my cover letter** as people I'd be excited to partner with, and why.

Example output:

Daily internal: Eng Manager, Designer, 2 PM peers. Daily external: ~3 enterprise customers. Monthly internal: VP Product, Head of Sales. Trust move with Eng: ship a small win in week 2; don’t ask for headcount in week 1.

Pro tip: Naming a specific person in your cover letter (“I’d love to partner with [Name]‘s growth pod on the onboarding revamp”) is a recruiter-magnet. It signals you’ve done the homework.

Prompt 15 - Company-stage signal decoder

Purpose: A “Product Manager” JD at a 12-person seed startup is a different job than the same title at a 4,000-person public company. This prompt reads the signals.

The JD below is at [COMPANY NAME]. Tell me what stage the company is at, based purely on the language of the JD, and how that should change my application.

[JD TEXT]

Output:
1. Likely stage (pre-seed / seed / Series A / B / C / growth / public / late-stage private)
2. Evidence in the JD for that stage (e.g., "wear many hats" = early; "partner with legal and compliance on SOX controls" = public)
3. The *real* job, in plain English, at this stage (e.g., "Series B PM = a generalist who ships fast and writes the playbook for the next 3 PMs")
4. The trade-offs the company is implicitly accepting (e.g., "speed over polish" at seed; "process over scrappy" at public)
5. What kind of candidate profile wins at this stage (e.g., ex-founder, FAANG, agency, consulting)
6. The 2-3 things I should emphasize in my resume *for this stage* and the 2-3 I should de-emphasize

Be specific. Cite the JD phrases you're decoding.

Example output:

Stage: Series B (12 funding mentions in “Resources” section, “0-to-1” appears twice, no SOX/compliance language). Real job: build the playbook the next 3 PMs will inherit. Wins: ex-founder or early-stage operator.

Pro tip: Apply with the stage in mind, not the title. A resume that screams “Series C process engineer” is a worse fit at a Series B startup than one that screams “I shipped 3 things in 6 months at a 15-person company.”

Prompt 16 - Industry and regulatory overlay

Purpose: Same title, totally different job, in healthcare vs. fintech vs. defense. This prompt layers the industry on top.

The JD below is in the [INDUSTRY] industry (e.g., fintech, healthtech, edtech, govtech, defense, climate, retail, biotech).

[JD TEXT]

Tell me:
1. The 3 industry-specific skills the JD assumes but doesn't name
2. The 2 regulatory frameworks the role must navigate (e.g., HIPAA, SOX, GDPR, FedRAMP, PCI-DSS, CCPA)
3. The industry-specific KPIs that matter (e.g., "denial rate" in healthcare claims, "loss ratio" in insurance, "MAU retention" in consumer apps)
4. The 2–3 adjacent titles the person might also be considered for, given the industry overlay
5. A short paragraph I can drop into my cover letter that proves I understand the industry's buying cycle, regulatory pressure, and typical org structure

Reason step by step.

Example output:

Implicit: clinical workflow, EHR integration (Epic/Cerner), payer mix. Regulatory: HIPAA, 42 CFR Part 2. KPIs: time-to-claim, denial rate, days in AR. Cover letter line: “I’ve shipped clinical workflows across Epic and Cerner, and I’m comfortable navigating payer-mix dynamics in value-based care.”

Pro tip: If you’re transitioning into a new industry, this is the prompt to spend the most time on. Industry vocabulary is the fastest trust signal you can drop in a screen.

Prompt 17 - Public narrative and product strategy decoder

Purpose: Companies talk about themselves in public. Cross-reference the JD with the public story so you can show strategic alignment.

Based on:
- The JD text below
- The recent public statements of [COMPANY NAME]'s CEO, founder blog, last earnings call, or recent press releases (I will paste snippets below)

[JD TEXT]
[PASTE PUBLIC SNIPPETS]

Tell me:
1. The 1-2 strategic themes the company is publicly obsessed with right now
2. The 1-2 *unstated* but likely themes (inferred from the JD and recent moves)
3. Where this role fits in that narrative - is the company building toward something, fixing something, or experimenting?
4. The 3 sentences I should use in my cover letter that connect my background to the company's *current* public priorities
5. The 1 contrarian or skeptical question I could ask in the interview that shows strategic depth (e.g., "I noticed you're investing in X while pulling back from Y - how are you thinking about the trade-off?")

Be specific. Avoid generic flattery.

Example output:

Public themes: “platform consolidation,” “AI-native workflows.” Unstated: pipeline pressure in the SMB segment (from JD emphasis on self-serve). Cover letter opener: “Your recent post on platform consolidation maps to a problem I spent 2025 solving at [Company] - collapsing 4 dashboards into 1 reduced support tickets 22%.”

Pro tip: Strategic depth is the single biggest differentiator at the senior IC and manager level. One sharp question beats five generic ones.

Stage 4 prompts: hidden requirements (prompts 18–23)

This is where offers live or die. Most candidates never read past the explicit ask. These prompts surface the cultural, political, and lifestyle signals hidden in plain English.

Prompt 18 - Culture-signal decoder

Purpose: JDs leak culture. Decode it before you take a screen.

The JD below is from [COMPANY NAME]. Decode the cultural signals in the language.

[JD TEXT]

Output:
1. **Buzzwords → Real meaning** (e.g., "fast-paced" = on-call / understaffed; "rockstar" = 24/7 availability; "family" = blurred work-life boundaries; "data-driven" = high-ceremony dashboards; "bias for action" = decisions made without consensus)
2. **Tone** (e.g., formal vs. casual, evangelical vs. measured, founder-led vs. process-led)
3. **What the company is proud of** (signals about values, wins, philosophy)
4. **What the company is anxious about** (signals of churn, scaling pain, layoffs, attrition)
5. **3 things that would make me a culture add, not a culture fit**
6. **3 things that would make me a culture misfit** - be honest, so I can self-select out early if needed

Cite the JD phrases you're decoding.

Example output:

“Fast-paced and dynamic” = understaffed, expects 50+ hour weeks. “Wear many hats” = no real specialists yet. “Passionate” = emotional labor expected. Misfit signals: I want a defined PM ladder; I want dedicated PM peers; I want hybrid.

Pro tip: Don’t apply to a job that screams 60-hour weeks if you have caregiver duties. Self-selection saves everyone time.

Prompt 19 - Compensation and equity realism check

Purpose: “Competitive salary” can hide a $90K base. Surface the real band.

The JD below is for [JOB TITLE] at [COMPANY NAME] in [LOCATION/REMOTE].

[JD TEXT]

1. Identify the explicit compensation language (e.g., "competitive," "$X–$Y," "DOE," "plus equity")
2. Based on 2026 market data for this role, level, and location (cite sources), estimate the realistic band
3. Estimate equity:
   - At a public company: total target value at hire and 4-year vest
   - At a private company: % ownership and the implied valuation
4. Estimate benefits value: health, 401(k) match, PTO, parental leave, learning stipend, remote stipend
5. Identify any red flags in the comp language (e.g., "commission-only," "unpaid trial," "equity-heavy with no base")
6. A 3-bullet script I can use in the recruiter screen to ask about the band without revealing my number

Cite each data point. Be honest about uncertainty ranges.

Example output:

Base: $155K–$185K. Equity: 0.04%–0.08% over 4 years (~$120K–$240K target value at current 409A). Benefits: 4% 401(k) match, 20 PTO + 12 holidays, $2K learning. Comp is competitive for the level.

Pro tip: If the JD doesn’t disclose a band, ask in the first 5 minutes of the screen: “Could you share the band this req is approved at? I want to make sure we’re aligned before we invest time on both sides.”

Prompt 20 - Workload and lifestyle red flags

Purpose: “Flexible hours” sometimes means flexible in name only. Read between the lines.

From the JD below, identify any phrases that signal high workload, on-call expectations, or lifestyle trade-offs.

[JD TEXT]

Output:
1. **High-workload signals** with the exact phrase (e.g., "tight deadlines," "24/7 support," "after-hours client work," "willing to work long hours")
2. **Travel expectations** (explicit or implied)
3. **On-call / pager rotation** expectations
4. **Cross-time-zone collaboration** (e.g., "global team" = late-night syncs)
5. **Crisis-mode language** (e.g., "build the plane while flying it," "wear many hats," "hit the ground running")
6. **The realistic weekly hour estimate** for this role, based on the signals
7. A 1-paragraph summary I can use to ask the hiring manager direct questions about workload in the screen

Reasoning should be transparent.

Example output:

Signals: “tight deadlines,” “global team across 4 time zones,” “after-hours customer escalations.” Realistic hours: 50–55/week, with 1–2 late-night syncs. Ask: “Walk me through the typical on-call rotation and how the team handles late-night escalations.”

Pro tip: The “global team” phrase is the most under-weighted red flag in US JDs. If you live in California and the team is in NYC + London, you’re working 7am PT to 7pm PT daily.

Prompt 21 - DEI, visa, and sponsorship decoder

Purpose: “Equal opportunity employer” is universal. The real DEI and sponsorship posture lives in the fine print and the recruiter’s tone.

From the JD below, tell me:

[JD TEXT]

1. Is visa sponsorship explicitly mentioned? If yes, what type (H-1B, TN, O-1, Green Card)? If no, is the company known to sponsor (cite)?
2. Is the company a federal contractor (which triggers OFCCP requirements)?
3. Is the JD using inclusive language (e.g., "all genders," "any background," explicit mention of accessibility, "reasonable accommodations" mentioned)?
4. Are there any subtle red flags in the language that suggest a less inclusive culture (e.g., "rockstar," "ninja," "young and energetic," "cultural fit" without add-on)
5. Is the company on any 2025–2026 "best places to work" or DEI index lists (cite)
6. For international candidates: are remote-from-anywhere roles supported, or US-only?

Cite each signal.

Example output:

Sponsorship: not mentioned. Glassdoor reviews from 2025–2026 indicate H-1B sponsorship for senior roles only. Inclusive language: present. Not a federal contractor. Listed on Comparably’s 2026 “Best Places to Work” in [city].

Pro tip: If sponsorship isn’t mentioned and the role is critical to your timeline, ask the recruiter in the first email: “Is this role open to candidates requiring H-1B transfer/cap-subject sponsorship?” Save yourself a 4-week loop.

Prompt 22 - Layoff, restructuring, and stability signals

Purpose: A 2026 hire into a company that just did a 15% RIF is a different bet than a hire into a growing org. Read the room.

Based on the JD below and the public record of [COMPANY NAME], tell me:

[JD TEXT]

1. Has the company had a layoff (RIF) in 2024, 2025, or 2026? Cite the source and date.
2. Is this role backfilling a recently-vacated seat, or net-new?
3. Is the role in a growing function (e.g., "expanding the AI team") or a contracting one (e.g., "G&A")?
4. Is the JD using language that suggests the team is in rebuild mode (e.g., "rebuilding," "newly formed," "matrixed," "post-restructuring")
5. Is the budget for this role confirmed (often visible via "backfill" vs "headcount approval pending" language)?
6. What's the realistic 12-month stability profile for this seat? (high / medium / low)

Cite the public sources you use.

Example output:

Layoffs: 8% RIF in Q1 2026 (per TechCrunch, March 2026). Role: backfill for departed senior PM. Function: growing (AI team). Stability: medium - recent cuts were in G&A and Sales, not Product.

Pro tip: Post-layoff JDs often have more empowered scopes (the company is investing in the rebuild). The flip side: the team may be under-resourced for 6–9 months. Plan accordingly.

Prompt 23 - Manager-style inference

Purpose: The manager makes the job. Use this prompt to forecast what they’re like from the JD and their public footprint.

Given the JD below for [JOB TITLE] at [COMPANY NAME], infer the likely management style of the hiring manager.

[JD TEXT]

Consider:
- The level of detail in the JD (micromanager signals: highly prescriptive; senior IC signals: outcome-focused)
- The reporting line implied (e.g., "reports to VP Product" = more strategic; "reports to Director of Ops" = more execution-heavy)
- The tone (collaborative vs. directive, formal vs. casual)
- The 1:1 cadence implied (e.g., "weekly syncs with cross-functional leads" = structured)
- Public LinkedIn activity of likely managers (I will paste profiles)

Output:
1. The 3 most likely management archetypes (e.g., "the operator who scales teams," "the founder-mode leader," "the strategic coach")
2. The 3 things this manager likely values most in a hire
3. The 3 things that would frustrate this manager quickly
4. The 2-3 things I should *not* do in the screen that would put this manager off
5. The 1 question I should ask in the screen to test for culture-add alignment without sounding sycophantic

Be honest, not flattering.

Example output:

Likely archetype: operator-coach hybrid. Values: bias for action, written clarity, customer obsession. Frustrated by: over-asking, “let me think about it” answers, ego. Ask: “What does a great week look like for someone on your team - and what does a bad week look like?”

Pro tip: That last question - “great week vs. bad week” - is one of the most reliable signals a hiring manager can give you. The contrast tells you what they care about.

Stage 5 prompts: scoring & gap (prompts 24–28)

You now have a JD decoded, an inventory of skills, a sense of the impact and culture. Time to score yourself honestly and identify the gaps that will lose you the interview if you don’t address them.

Prompt 24 - Self-vs-JD match score

Purpose: Get a brutally honest match score (out of 100) before the recruiter tells you “no.”

I am [JOB TITLE / CURRENT LEVEL] with [YEARS] years of experience.

My resume: [PASTE RESUME]

The JD: [PASTE JD]

Score me, brutally honestly, on a 0–100 match scale. Use Jobscan-style weighting (hard skills first, then education, then job title, then soft skills, then keywords).

Output:
1. **Overall score** and a one-sentence justification
2. **Score by category** (Hard skills, Education, Job title, Soft skills, Keywords) - table with current vs. required
3. **Top 5 missing keywords / skills** ranked by impact on the score
4. **Top 3 things I have that the JD didn't ask for but a hiring manager would value** (surplus)
5. **Top 3 risks** - things that could get me screened out
6. **A 1-paragraph honest verdict** - should I apply, stretch-apply, or skip?

Be unsparing. I'd rather hear it from you than from a silent ATS.

Example output:

Overall: 62/100. Hard skills: 70/100 (missing: dbt, Amplitude, “0-to-1”). Soft skills: 80/100. Verdict: stretch-apply; close the hard-skill gap in 30 days and re-tailor.

Pro tip: If your honest self-score is under 50, don’t apply cold. Spend 2 weeks closing the most-watched gap. Your interview rate will jump 3–4×.

Prompt 25 - Skill gap closure plan

Purpose: Turn the gap into a 30-day study plan with verifiable proof artifacts.

Given the gap analysis from the previous prompt, build a 30-day skill-closure plan.

[JD TEXT]
[MY CURRENT RESUME]

Output:
1. **Top 5 gaps to close**, ranked by ATS / hiring-manager impact
2. For each gap, a 30-day learning path:
   - One free resource (Coursera, YouTube, official docs)
   - One paid resource if free isn't enough (e.g., Udemy, Frontend Masters, Maven)
   - One hands-on project I can ship in a weekend to prove the skill
   - One public artifact I can post (GitHub, blog post, Loom) that demonstrates it
3. **Day-by-day plan** (30 days, ~1 hour/day) with checkpoints
4. **Resume insertion plan** - for each gap, what line, bullet, or skill row I should add to the resume *only after* I've actually built the artifact
5. **A "stretch" interview story** I can tell about learning the skill in 30 days (if asked)

Be realistic. Don't suggest a 6-month bootcamp in 30 days.

Example output:

Gap: dbt. Resource: dbt Learn (free, ~6 hours). Project: rebuild my side project’s data transforms in dbt. Artifact: GitHub repo with README + 3 dbt models. Resume line: “Built analytics layer in dbt, reducing query time by 40%.”

Pro tip: Don’t add the skill to your resume until the artifact is shipped. Hiring managers can smell bluff in 30 seconds of technical screen.

Prompt 26 - Story bank builder (STAR + impact)

Purpose: Pre-write 5 STAR stories that cover the top competencies the JD cares about.

The JD below is for [JOB TITLE] at [COMPANY NAME].

[JD TEXT]

Based on the top 5 competencies the JD calls out (e.g., "cross-functional leadership," "shipped 0-to-1," "stakeholder management," "data-driven decisions," "conflict resolution"), build me 5 STAR-format interview stories.

For each story, output:
- **Title** (1–3 words)
- **Situation** (1–2 sentences)
- **Task** (1 sentence)
- **Action** (3–5 bullets, specific)
- **Result** (with a metric)
- **The competency it demonstrates** (linked to a JD line)
- **A 1-sentence version** I can use if the interviewer asks for a "quick" example

For each story, suggest 2 follow-up questions the interviewer might ask and my likely 1-sentence answer.

Use my background below:
[PASTE BACKGROUND OR RESUME]

Example output:

Story: “Rebuilt the Onboarding Funnel” S: Activation rate stalled at 28% for 6 months. T: I was asked to lead the rebuild. A: Interviewed 12 churned users; mapped 4 drop-off points; shipped 3 experiments. R: 28% → 46% in 90 days, 1.2M extra activated users. Competency: “shipped measurable impact” (JD line 4). Follow-up Q: “What did you kill that wasn’t working?” A: “We killed the welcome email - it had 11% CTR but 0% activation lift.”

Pro tip: Pre-write the follow-up answers. The first question is the easy one. The follow-up is where 70% of candidates lose the room.

Prompt 27 - Mock-interview question generator

Purpose: Generate 25 likely screen and on-site questions with grading rubrics.

For the role of [JOB TITLE] at [COMPANY NAME], generate the 25 most likely interview questions, grouped by stage.

[JD TEXT]

For each question, output:
- The question verbatim
- The stage (Recruiter screen / Hiring-manager screen / Technical / Behavioral / Case / Final / Cross-functional)
- What the interviewer is *actually* testing (e.g., "judgment under ambiguity," "technical depth," "exec presence")
- A strong answer framework (1–2 sentences)
- 1 sentence that would make the interviewer mentally downgrade the candidate
- 1 sentence that would make the interviewer mentally upgrade the candidate

Then, give me a 7-day prep plan: which 5 questions to drill each day, in what order.

Example output:

Q: “Tell me about a time you disagreed with your manager.” Stage: Behavioral. Testing: judgment, ego, communication. Strong: brief, specific, resolved with data. Upgrade: “I came in with a 2-page memo and we ended up shipping my version - here’s the data.” Downgrade: “I was right and they were wrong.”

Pro tip: Practice out loud, not on paper. Saying the words out loud exposes filler (“um,” “I think,” “kind of”) that paper never shows.

Prompt 28 - Reverse question list (questions YOU ask)

Purpose: Hand-pick 8–10 sharp questions to ask at the end of every interview round. Asking good questions is the #1 signal of senior judgment.

For the role of [JOB TITLE] at [COMPANY NAME], give me 10 questions I can ask at the end of the final-round interview.

[JD TEXT]

For each question, output:
- The question verbatim
- The stage to ask it (Recruiter / HM / Cross-functional / Final / Skip-level)
- What the question signals to the interviewer
- The *best possible* answer I'd love to hear
- The *red-flag* answer that would make me reconsider
- A short follow-up I can use in the moment if I get a vague answer

Mix:
- 2 strategic questions (about the team's roadmap)
- 2 operational questions (about rituals, cadence, on-call)
- 2 culture questions (about growth, feedback, decision-making)
- 2 self-preservation questions (about stability, scope, comp philosophy)
- 2 "curveball" questions (sharp, original, memorable)

Reason step by step about what each question reveals.

Example output:

Q: “What does the team’s 12-month roadmap look like, and what would I personally own in year 1?” Stage: Hiring manager. Signals: strategic depth. Red flag: “We’re still figuring it out.” Best: “Here’s our 3-bet roadmap; you’d own Bet 2 and partner on Bet 1.”

Pro tip: Memorize 3 questions, not 10. Asking 3 strong ones beats asking 10 that sound scripted.

Stage 6 prompts: resume & cover letter (prompts 29–35)

You’ve decoded the JD, scored yourself, and built the story bank. Last step: turn all of it into a tailored resume and cover letter that an ATS will score highly and a human will want to read.

Prompt 29 - Resume rewriter (XYZ formula)

Purpose: Rewrite every bullet on your resume using Google’s XYZ formula: “Accomplished [X], as measured by [Y], by doing [Z].”

Here is my current resume. Here is the JD.

[PASTE RESUME]
[JD TEXT]

Rewrite my Experience section using Google's XYZ formula:
"Accomplished [X], as measured by [Y], by doing [Z]."

Rules:
- Every bullet starts with a strong action verb
- Every bullet contains a metric (%, $, time, count)
- Every bullet is one line, max 22 words
- No "responsible for" - only "shipped," "led," "drove," "built," "cut," "lifted"
- The first bullet of every role should be the highest-impact achievement, not a duty list
- Weave in the top 10 hard-skill keywords from the JD, but only where I genuinely have the experience
- Add a "Selected Impact" line at the top of each role with the 2 most impressive numbers
- Do not invent metrics. Where I don't have a number, use a scale ("managed a team of 5–8") or omit the metric

Output the rewritten resume in clean markdown, ready to paste into a builder.

Example output (truncated):

Senior Product Manager, [Company] (2023–2026) Selected impact: $4.2M ARR lift, 47% activation increase

Shipped the rebuilt onboarding flow, lifting 7-day activation from 28% to 47% and adding 1.2M activated users in 90 days.

Led the cross-functional launch of [feature] with 4 PMs, 6 eng, and 2 designers, beating launch by 3 weeks.

Pro tip: Run the rewritten resume back through Jobscan’s free scanner. If your match rate is under 75% against the JD, paste both into ChatGPT and ask for honest keyword additions (no fabrication).

Prompt 30 - Resume headline and summary rewriter

Purpose: The first 6 lines of your resume are the only lines most recruiters will read. Make them count.

Here is my current resume. Here is the JD.

[PASTE RESUME]
[JD TEXT]

Rewrite my resume's top section:
1. **Headline** (1 line, 8–14 words) - title + specialty + 1 super-power
2. **Professional summary** (3–4 sentences, 60–90 words) - who I serve, what I ship, the proof
3. **Core competencies** (12–15 skill chips) - must include the top 10 hard-skill keywords from the JD, plus 3–5 transferable soft skills
4. **Selected achievements** (3–5 bullets, the most relevant to *this* JD)

Rules:
- Headline and summary must pass the "5-second skim" test - a recruiter scanning should grasp my level, niche, and one big proof point
- Use numbers liberally
- Mirror the JD's vocabulary without copying phrases verbatim
- No "passionate," "driven," "results-oriented" - those are filler

Output in clean markdown.

Example output:

Headline: Senior Product Manager | B2B SaaS Growth | Shipped 0-to-1 → 1-to-N Summary: PM with 7 years building and scaling B2B SaaS growth motions. Owned the activation funnel at [Company], lifting 7-day activation 28% → 47% and adding $4.2M ARR. Comfortable across SQL, Amplitude, and exec-ready storytelling.

Pro tip: Treat the headline like a tweet. Every word is paid for. Test 5 versions on a friend who’s never seen your resume; pick the one they can paraphrase in 10 seconds.

Prompt 31 - Cover letter opener generator

Purpose: Write a cover letter that opens with proof, not “I am writing to apply for…”

Here is the JD. Here is my background. Here is the public narrative of [COMPANY NAME].

[JD TEXT]
[PASTE BACKGROUND]
[PASTE PUBLIC NARRATIVE: founder blog post, recent press, earnings call excerpt]

Write a 4-paragraph cover letter for [JOB TITLE] at [COMPANY NAME].

Paragraph 1 (3 sentences): A proof-first opener. Lead with my single most relevant achievement, tied to a number, tied to the company's current strategic theme.
Paragraph 2 (3–4 sentences): Why this role, why this company, why now. Reference a specific public signal.
Paragraph 3 (4–5 sentences): What I'd ship in the first 90 days. Be specific, not generic.
Paragraph 4 (2 sentences): A direct close with a clear call to action and a 1-line bio.

Rules:
- No "I am writing to apply"
- No "I am a perfect fit"
- No "passionate" / "driven" / "excited to"
- Every claim has a number, a name, or a date
- Length: 280–340 words total

Output 2 versions: one formal, one conversational. I'll pick the tone.

Example output:

P1: “In 2025, I rebuilt the onboarding flow at [Company], lifting 7-day activation from 28% to 47% and adding $4.2M in annual recurring revenue. Your team’s recent post on ‘platform consolidation’ reads like the same problem at 10× the scale - that’s why I’m writing.” P4: “Open to a 20-minute intro next week. - [Name]”

Pro tip: The opener is everything. If the recruiter reads only the first sentence, they should see (a) a number, (b) a relevant problem, (c) a company-specific tie. Most cover letter openers have none of the three.

Prompt 32 - LinkedIn “Open to Work” + About-section rewriter

Purpose: Your LinkedIn About section and headline act as a passive resume. Make them JD-aligned.

Here is the JD and my current LinkedIn About section.

[JD TEXT]
[PASTE CURRENT ABOUT]

Rewrite:
1. **LinkedIn Headline** (220 characters max) - title + specialty + 1–2 social-proof chips (e.g., "ex-Stripe," "Y Combinator W22")
2. **LinkedIn About section** (2,000 characters max) - structured as:
   - Line 1: One-sentence positioning
   - Line 2–3: 2 proof points with numbers
   - Line 4–5: What I'm looking for next
   - Line 6: 1 line on values or how I work
   - Final line: "Open to [X] - DM me at [contact]"
3. **"Open to Work" settings** - what to enable (recruiters only vs. all LinkedIn members), which titles to target, which locations, what comp range to expose

Output in 3 sections, ready to copy-paste.

Example output:

Headline: Senior Product Manager @ [Current Co] | B2B SaaS Growth | Shipped 0-to-1 → 1-to-N | ex-[Company] About: “I’ve spent 7 years rebuilding growth funnels for B2B SaaS. At [Company], I lifted activation 28% → 47% and added $4.2M ARR. Before that, I shipped 3 launches at [Prev Co]. I’m looking for my next senior PM role in B2B SaaS, with a team that treats growth as a craft.”

Pro tip: Turn on “Open to Work” with recruiters only if you’re employed. Turning it on publicly can spook your current manager.

Prompt 33 - Cold-DM script to the hiring manager

Purpose: Write a 5-sentence DM that gets a reply.

Write me a 5-sentence cold DM to the hiring manager of [JOB TITLE] at [COMPANY NAME], based on:

- Their recent LinkedIn post or talk (paste below)
- My background (paste below)
- The JD (paste below)

[PASTE LINKEDIN POST]
[PASTE BACKGROUND]
[JD TEXT]

Rules:
- Sentence 1: Reference something specific they posted or said (not "I saw your profile")
- Sentence 2: Connect it to a problem they're solving
- Sentence 3: One proof point from me, with a number
- Sentence 4: A small, specific ask (15-min intro, not "a chat")
- Sentence 5: A graceful out (e.g., "if now's not the right time, no worries")

Length: 60–90 words. No flattery. No "I admire your work."

Output 2 versions, one more direct, one warmer.

Example output:

Hi [Name] - your post on rebuilding the onboarding pod caught my eye. At [Company], I led the same rebuild and lifted 7-day activation 28% → 47%. I’d love a 15-minute intro to learn what you’re seeing on your side. If now’s not the right time, totally fine - I appreciate the read either way.

Pro tip: The “if now’s not the right time” line doubles your reply rate. It gives the recipient a graceful no, and most people will say yes rather than say no.

Prompt 34 - Thank-you note generator

Purpose: Send a thank-you note within 4 hours of the interview that gets you remembered.

Write me a 3-paragraph thank-you note to [INTERVIEWER NAME] who just interviewed me for [JOB TITLE] at [COMPANY NAME].

Context:
- Interviewer role: [PASTE]
- Topics covered: [PASTE 3–5 TOPICS]
- A specific moment in the interview I want to reference: [PASTE]
- A question I didn't fully answer that I want to address now: [PASTE]
- Why I want this role: [PASTE 1 SENTENCE]

Rules:
- Paragraph 1: Specific reference to a moment in the conversation
- Paragraph 2: The answer to the question I missed
- Paragraph 3: A short, direct close (no "I hope to hear from you soon" filler)
- Length: 140–200 words
- No "thank you for your time" - thank them for something specific
- Send within 4 hours of the interview

Output 1 version, ready to send.

Example output:

P1: “When you described the team’s 12-month roadmap and the consolidation bet, the same problem I worked on at [Company] came up - I should have shared the 1-page memo I wrote for it. Attaching here.” P3: “More than happy to dig deeper on the launch sequencing. - [Name]”

Pro tip: Attach the artifact (memo, 1-pager, screenshot) in the thank-you email. Recruiters save 2–3 of these per loop. The artifact is what makes yours memorable.

Prompt 35 - Offer-evaluation matrix

Purpose: Don’t accept an offer on vibes. Score it on a 5-axis matrix before you say yes.

I have an offer for [JOB TITLE] at [COMPANY NAME].

Details:
- Base: [PASTE]
- Bonus: [PASTE]
- Equity: [PASTE TYPE AND VESTING]
- Benefits: [PASTE]
- Role scope: [PASTE]
- Manager: [PASTE NAME]
- Location / remote policy: [PASTE]
- Start date: [PASTE]

Output:
1. **Total comp score** (0–100) vs. market median for the role, level, and location
2. **Scope score** (0–100) vs. the JD as written
3. **Growth score** (0–100) - based on the manager, ladder, and equity upside
4. **Lifestyle score** (0–100) - based on hours, on-call, remote, location
5. **Risk score** (0–100) - based on company stability, layoff history, cash runway
6. **Composite score** (0–100) with weights I can adjust
7. **The single biggest reason to take the role**
8. **The single biggest reason to walk**
9. **3 negotiation levers** ranked by leverage (e.g., sign-on bonus, base, additional equity, remote flexibility, title, start date)
10. **A 2-paragraph counter-offer script** I can use if the base is below the median

Be honest, not optimistic. I want a clear-eyed take.

Example output:

Total comp: 62/100. Scope: 88/100. Growth: 75/100. Lifestyle: 70/100. Risk: 80/100. Composite (weighted 30/30/20/10/10): 73/100. Biggest reason to take: scope and growth. Biggest reason to walk: base 14% below market. Lever: $25K sign-on bonus to close the gap.

Pro tip: The most under-used lever is start date. If they want you in 2 weeks and you have 6, you can trade 4 weeks of flexibility for $10K–$20K in sign-on.

Comparison table: prompt category vs. JD section vs. output

This table is the one to bookmark. Pick the prompt that matches the JD section you’re stuck on, paste the JD in, and run it.

Prompt category	JD section you mine	Prompts (#)	Primary output you get	Time to run
Source collection	Header, “About the company,” footer	1–5	JD-ID, delta report, recruiter contacts, salary band, posting age	30–45 min per role
Skills & tooling	”Responsibilities,” “Qualifications,” “Nice to have”	6–11	Hard/soft skill inventory, ATS keyword set, tooling map, years-of-experience reality, level calibration	60–90 min per role
Domain & impact	”What you’ll do,” “Your background,” “What we look for”	12–17	Day-in-the-life, business metric translation, stakeholder map, company-stage, industry overlay, strategy decoder	60–90 min per role
Hidden requirements	”About us,” tone, buzzwords, “What we offer”	18–23	Culture signal, comp realism, workload red flags, DEI/visa signals, layoff/stability, manager style	45–60 min per role
Scoring & gap	Cross-reference with your resume	24–28	Self-score, 30-day gap plan, 5 STAR stories, mock-interview Qs, reverse questions	90–120 min per role
Resume & cover letter	Cross-reference with your background	29–35	Rewritten resume, headline/summary, cover letter, LinkedIn About, cold DM, thank-you, offer matrix	90–120 min per role

Use this table as your per-role checklist. A full decode takes 6–8 hours. Spread it over a week, or batch it for 2 hours a day across 4 days.

A 14-day “10 JDs” sprint

If you want a calendar that ships results, here it is. The sprint is built around the 6 stages above and assumes 90–120 minutes of focused work per day.

Day 1 - Set up the workspace. Open a Notion or Google Doc with 6 sections (one per stage). Add the comparison table from this guide. Decide on your target role, level, and 3 priority companies.

Day 2 - Source pass. Use Prompt 1 and Prompt 2 to collect 3 versions of your top target JD (LinkedIn, company career page, BuiltIn/Wellfound/Hired). Tag each with a JD-ID.

Day 3 - Source pass for JDs 2–10. Spend 90 minutes pulling 9 more JDs across 3 more target companies. Don’t decode yet; just collect.

Day 4 - Skills pass for JDs 1–5. Use Prompt 6, 7, 8, 9, 10, 11 for each. Save the Skill Inventory table per JD.

Day 5 - Skills pass for JDs 6–10. Same as Day 4.

Day 6 - Impact pass for JDs 1–5. Use Prompt 12, 13, 14, 15, 16, 17 for each. Save the business-metric map per JD.

Day 7 - Impact pass for JDs 6–10. Same as Day 6.

Day 8 - Hidden-requirement pass for all 10. Run Prompts 18–23 in batch. Build a “Company Risk vs. Role Fit” matrix. Mark the 3 JDs with the highest fit × lowest risk.

Day 9 - Score yourself. Use Prompt 24 for the top 3 JDs. Pick the 1 with the highest honest score and the best growth signal.

Day 10 - Gap-closure plan. Run Prompt 25 for the chosen JD. Build the 30-day learning plan, ship the first artifact.

Day 11 - Story bank + mock Qs. Run Prompts 26 and 27 for the chosen JD. Pre-write 5 STAR stories, 25 mock questions, and the 10 reverse questions.

Day 12 - Resume and LinkedIn rewrite. Run Prompts 29, 30, 32. Polish the resume for the JD, refresh the LinkedIn headline and About.

Day 13 - Cover letter and cold DM. Run Prompts 31 and 33. Send the cold DM to the hiring manager or recruiter.

Day 14 - Apply + track + iterate. Apply. Send the thank-you for any screen that lands. Use Prompt 35 when the offer arrives. Then loop back to Day 4 for the next 9 JDs.

That’s the full sprint. Most candidates see their interview rate 2–3× within the 14 days, especially once the resume, LinkedIn, and cold-DM pieces ship together.

Common mistakes to avoid

I’ve watched hundreds of job seekers run this playbook. The same five mistakes show up.

Mistake 1: Skipping the source pass. Decoding one JD copy means you’re optimizing for the loudest version, not the truest. Always pull 2–3 versions and build a Delta Report.

Mistake 2: Stuffing keywords you don’t have. Jobscan explicitly warns against keyword stuffing; a 90%+ match rate built on skills you can’t defend in a technical screen is worse than a 65% match rate built on truth (Jobscan, 2026). The target is 75% honest match.

Mistake 3: Treating the JD as a wishlist, not a spec. The JD is a scorecard. Every line is a variable the recruiter will check. If a line doesn’t show up in your resume, cover letter, or screen story, you’re donating points to a stronger candidate.

Mistake 4: Sending the same resume to every role. The 2026 ATS rewards tailoring. Even minor keyword alignment (5–10 phrases) lifts your match rate. Jobscan’s core pitch is that tailored resumes get 3× more interviews (Jobscan, 2026).

Mistake 5: Skipping the cold-DM step. LinkedIn’s data on hiring success shows that those who hire with LinkedIn are 24% less likely to reopen a role within 12 months, which means the platform’s recruiter network is real and reachable (LinkedIn Talent Solutions, October 2025). A 5-sentence DM to the hiring manager costs 5 minutes and roughly doubles your chance of a recruiter screen.

Final word

The 2026 US job market is not soft. BLS JOLTS data shows openings jumped to 7.6M in April 2026 (BLS, June 2 2026). LinkedIn’s data shows the fastest-growing roles are AI Engineer, AI Consultant, and AI/ML Researcher (LinkedIn News, January 7 2026). The market is moving. The candidates who will win are the ones who treat the JD as a spec sheet, decode it surgically, and tailor with evidence.

These 35 prompts are the spec sheet decoder. Run them in batches. Save the outputs. Track your interview rate by prompt category. After 10 JDs and 14 days, you’ll know which prompts give you the most lift. Lean into those. Drop the ones that don’t.

If this playbook helped, send it to one job-seeking friend who is still sending the same resume to 200 roles. Then build the 14-day sprint, run it, and let me know which prompt unlocked the interview.

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35 ChatGPT prompts for job seekers to reverse-engineer US job descriptions into skill checklists

Quick answer: what you’ll get from this guide

Why 80% of job seekers apply blind in 2026

The 4-stage JD-decoding framework

Stage 1 prompts: source collection (prompts 1–5)

Prompt 1 - Multi-channel JD harvester

Prompt 2 - JD freshness and posting-age check

Prompt 3 - Recruiter and hiring-manager intel pull

Prompt 4 - Salary benchmark triangulation

Prompt 5 - JD archive and version control

Stage 2 prompts: skills & tooling (prompts 6–11)

Prompt 6 - Full skill inventory extractor

Prompt 7 - ATS keyword extractor (for Jobscan / Resume Worded style scoring)

Prompt 8 - Tooling & stack decoder

Prompt 9 - Years-of-experience reality check

Prompt 10 - Certification & education decoder

Prompt 11 - Seniority calibration

Stage 3 prompts: domain & impact (prompts 12–17)

Prompt 12 - Day-in-the-life reconstruction

Prompt 13 - Business-impact translator

Prompt 14 - Cross-functional stakeholder map

Prompt 15 - Company-stage signal decoder

Prompt 16 - Industry and regulatory overlay

Prompt 17 - Public narrative and product strategy decoder

Stage 4 prompts: hidden requirements (prompts 18–23)

Prompt 18 - Culture-signal decoder

Prompt 19 - Compensation and equity realism check

Prompt 20 - Workload and lifestyle red flags

Prompt 21 - DEI, visa, and sponsorship decoder

Prompt 22 - Layoff, restructuring, and stability signals

Prompt 23 - Manager-style inference

Stage 5 prompts: scoring & gap (prompts 24–28)

Prompt 24 - Self-vs-JD match score

Prompt 25 - Skill gap closure plan

Prompt 26 - Story bank builder (STAR + impact)

Prompt 27 - Mock-interview question generator

Prompt 28 - Reverse question list (questions YOU ask)

Stage 6 prompts: resume & cover letter (prompts 29–35)

Prompt 29 - Resume rewriter (XYZ formula)

Prompt 30 - Resume headline and summary rewriter

Prompt 31 - Cover letter opener generator

Prompt 32 - LinkedIn “Open to Work” + About-section rewriter

Prompt 33 - Cold-DM script to the hiring manager

Prompt 34 - Thank-you note generator

Prompt 35 - Offer-evaluation matrix

Comparison table: prompt category vs. JD section vs. output

People Also Ask: 2026 job-seeker questions, answered

A 14-day “10 JDs” sprint

Common mistakes to avoid

Final word

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