infrasity-labs Resume Tailoring Skill
Priority hierarchy: See
references/priority-hierarchy.mdfor conflict resolution.
Create compelling, tailored resumes that make it obvious you're the right candidate for a specific job.
File Structure
scripts/
tailor-resume.md # Resume tailoring subagent prompt
The profile template is at references/profile.md.
Data Directory
Resolve the data directory using references/data-directory.md.
Workflow
Step 0: Check Prerequisites
Resolve the data directory, then check prerequisites per references/prerequisites.md. Resume is required; profile is strongly recommended. If the user proceeds without a profile, set a flag to present all assumptions for verification (see Step 3a below).
If $ARGUMENTS is a URL, continue to Step 1.
Otherwise, ask for a job URL.
Step 1: Get Job Details
Accept a job URL from the user (from $ARGUMENTS or by asking).
Use Claude in Chrome MCP tools to fetch the job posting per references/browser-setup.md.
Parse and extract:
- Job title and level (IC vs. manager, seniority)
- Company name and what they do
- Responsibilities - what the job actually involves day-to-day
- Requirements - must-have qualifications
- Nice-to-haves - preferred qualifications
- Keywords - industry terms, tools, methodologies mentioned
- Team context - who they report to, team size, cross-functional partners
- Company stage/size indicators
Create a job folder at DATA_DIR/jobs/[company-slug]-[date]/ and save the parsed job posting to posting.md.
If the page can't be loaded or parsed, ask the user to paste the job description directly.
Step 2: Analyze Match
Before writing, map the candidate's experience to the job:
Level match: Confirm the candidate's experience level matches the role. A VP-level candidate applying for a Director role should lean on strategic impact. A Director applying for VP should emphasize scope and leadership growth.
Requirement mapping: For each job requirement, identify the strongest evidence from the work history profile:
- Direct experience ("Led SEO strategy" → job asks for SEO experience)
- Analogous experience ("Scaled marketplace from 1M to 10M users" → job asks for growth experience)
- Transferable skills ("Managed 30-person team" → job asks for leadership)
Gap identification: Note any requirements where the candidate has no clear match. These should NOT be fabricated - instead, find adjacent experience that demonstrates capability.
Keyword alignment: Identify the job posting's language and terminology to mirror in the resume.
Compelling narrative: Determine the 2-3 sentence story of why this person is the obvious choice. What's the throughline?
Step 3: Generate Tailored Resume
Create the tailored resume following these principles:
Structure:
- Header: Name, contact info, LinkedIn (same as original)
- Summary/Profile: 2-3 sentences positioning the candidate specifically for THIS role. Not generic - reference the company and role context directly.
- Experience: All roles from the resume, but with bullet points rewritten, reordered, and selectively emphasized
- Skills: Reorganized to lead with what the job asks for
- Education: Same as original
Bullet point principles:
- Lead each role with the bullets most relevant to the target job
- Rewrite bullets to mirror the job posting's language where authentic
- Include metrics and quantified impact (from work history profile)
- Remove or de-emphasize bullets that aren't relevant to this specific role
- Add bullets from the work history profile that weren't on the original resume but ARE relevant to this job
- Each bullet should start with a strong action verb
- Each bullet should show: what you did → how you did it → what the impact was
Level-matching:
- For executive roles: emphasize strategy, P&L ownership, board interaction, team building, cross-functional leadership
- For director roles: emphasize program ownership, team management, operational excellence, stakeholder management
- For IC roles: emphasize hands-on execution, technical depth, individual contributions, collaboration
Writing rules (CRITICAL — target Flesch score above 90):
- Write like a sharp executive, not a language model. Short sentences. Plain words.
- Every sentence gets one idea. If a sentence has "and" connecting two unrelated clauses, split it.
- Never use emdashes. Use commas, periods, colons, semicolons, or parentheses instead.
- Vary sentence structure. Not every bullet should follow the exact same pattern.
- No preamble clauses. Bad: "Leveraging deep expertise in marketplace dynamics, led..." Good: "Led..."
- No stacking adjectives. Bad: "cross-functional, data-driven, customer-centric approach". Pick one.
- No filler phrases: "demonstrating ability to", "showcasing expertise in", "with a track record of", "needed to drive", "spanning", "leveraging", "utilizing"
- No compound noun piles: "AI-driven product opportunity identification and execution" — just say what you did
- Summaries must be 2-3 SHORT sentences. Each sentence under 20 words. No run-on sentences connecting multiple capabilities with commas and "and".
Strict accuracy rules (CRITICAL):
- ONLY use information explicitly stated on the resume or in the work history profile
- NEVER assume business model (B2B vs B2C), revenue type, or company stage unless stated
- NEVER infer scope beyond what's written (e.g., don't add "P&L ownership" if resume says "revenue targets")
- NEVER add responsibilities, skills, or functional areas the candidate didn't mention
- NEVER assume cross-functional partnerships that aren't listed
- When the resume is ambiguous, use conservative language or omit the detail entirely
- If you need to frame experience differently for the target role, only reframe what IS there, never invent what ISN'T
What NOT to do:
- Don't fabricate experience or skills the candidate doesn't have
- Don't use generic buzzwords that aren't backed by specific experience
- Don't make the resume longer than 2 pages
- Don't change job titles or dates
- Don't remove roles (gaps look suspicious)
- Don't assume anything about the candidate's business, scope, or responsibilities that isn't explicitly documented
Step 3b: Critique and Rewrite (MANDATORY — do this before presenting)
Before showing the resume to the user, review every line and fix AI-sounding writing. Go sentence by sentence and ask:
- Is this sentence doing too much? If it has more than one comma-separated clause, split it into separate sentences or bullet points.
- Would a real person say this? Read it out loud. If it sounds like a LinkedIn post or a ChatGPT response, rewrite it.
- Is there filler? Cut any phrase that doesn't add information. "Demonstrating ability to identify and execute on AI-driven product opportunities from ideation through production" → "Built an AI product from idea to production."
- Are there stacked buzzwords? "Cross-functional, data-driven, customer-centric leadership" → pick the one that matters for this job and give a concrete example.
- Is the summary under control? Max 3 sentences. Each under 20 words. No sentence should list more than 2 things.
Common AI patterns to kill:
- "I combine X with Y, Z, and the W needed to..." → Split into separate statements
- "...demonstrating [abstract quality]" → Delete or replace with the actual result
- "...spanning [long list]" → Pick the most relevant 1-2 items
- "Led [action], [action], and [action] across [scope]" → One action per bullet
- Any bullet over 2 lines is probably trying to do too much — split it
- Gerund clauses tacked onto the end: "...delivering X while maintaining Y" → Two sentences
Test: After rewriting, re-read the summary and first 3 bullets. If any sentence takes more than one breath to read out loud, it's too long. Shorten it.
Output:
Save the tailored resume to DATA_DIR/jobs/[company-slug]-[date]/resume.md
Present the resume to the user with a brief explanation:
Here's your tailored resume for [Role] at [Company].
**Key changes I made:**
- [What was reordered/emphasized and why]
- [What bullets were rewritten and why]
- [What was added from your work history]
**The narrative:** [2-3 sentence pitch for why you're the right person]
The resume is saved to: DATA_DIR/jobs/[folder]/resume.md
Step 3a: Verify Assumptions (if no profile exists)
If no work history profile was available, present the user with a list of every assumption made:
Before we finalize, here are the assumptions I made. Please correct
any that are wrong:
1. [Company] - I assumed [X]. Is that right?
2. [Role scope] - I described your scope as [Y]. Accurate?
3. [Business model] - I framed this as [Z]. Correct?
...
Wait for the user to verify or correct before finalizing. Apply all corrections to the resume AND save them to DATA_DIR/profile.md so they persist.
Step 4: Iterate
Ask if the user wants to adjust anything:
- Tone (more technical, more strategic, more metrics-heavy)
- Emphasis (highlight certain roles or skills more)
- Length (condense to 1 page, expand detail in certain areas)
- Specific bullet points to rephrase
Apply changes and re-save.
Step 5: Update Profile (ALWAYS)
Every time the user corrects a factual detail, update DATA_DIR/profile.md immediately:
- Business model corrections (e.g., "Proficiently is B2C, not B2B")
- Scope corrections (e.g., "I had revenue targets, not P&L ownership")
- Responsibility corrections (e.g., "I didn't manage candidate workflows")
- Any other clarification about roles, teams, or accomplishments
This prevents the same mistakes on future resumes. If the profile is still a blank template, create a new one with whatever the user has told you so far. Use the structure from references/profile.md but fill in only what you know for certain.
Response Format
Structure user-facing output with these sections:
- Tailored Resume — the full resume text
- Tailoring Notes — key changes made (reordered bullets, rewritten sections, added content from profile) and the narrative pitch
- What's Next — suggest iterating on tone/emphasis, or writing a cover letter using the cover-letter skill