Getting it into your agent
It runs from inside its repository, so the clone comes first — what it calls does not travel with the file alone.
git clone --depth 1 https://github.com/varunr89/resume-tailoring-skillnpx agentmods add skills/varunr89/resume-tailoring-skill/resume-tailoringWrote this? Show the measurements
A badge with what this costs and how it scanned, read live from this page, so it follows the numbers instead of freezing them. Markdown for a README, HTML for a documentation site or a project page.
[](https://agentmods.dev/skills/varunr89/resume-tailoring-skill/resume-tailoring)<a href="https://agentmods.dev/skills/varunr89/resume-tailoring-skill/resume-tailoring"><img src="https://agentmods.dev/badge/skills/varunr89/resume-tailoring-skill/resume-tailoring/github.svg" alt="Measured on agentmods" height="20"></a>Or the 80×15 button, for a site that already has a row of RSS and ATOM ones. Only the verdict fits; the numbers stay here.
<a href="https://agentmods.dev/skills/varunr89/resume-tailoring-skill/resume-tailoring"><img src="https://agentmods.dev/badge/skills/varunr89/resume-tailoring-skill/resume-tailoring.svg" alt="Reviewed on agentmods" width="80" height="20"></a>What it costs to keep this loaded
Counted locally with the o200k_base tokenizer, which is exact for GPT models; Claude uses its own tokenizer and its counts differ. Treat this as one consistent yardstick across the catalogue rather than a bill. Prices are per million input tokens.
| Model | Per session | Once invoked |
|---|---|---|
| Fable 5.1 | $0.00045 | $0.08531 |
| Opus 5 | $0.00023 | $0.04265 |
| Sonnet 5 | $0.00009 | $0.01706 |
| Haiku 4.5 | $0.00005 | $0.00853 |
Grade A, and why
resume-tailoring scanned grade A with 0 findings against 26 rules in 11 categories — prompt injection, anti-refusal, data exfiltration, privilege escalation, supply chain, agent snooping, system-prompt leakage, SSRF and excessive agency — measured 11d ago.
A static scan of the body, not an audit. Every finding is printed with the line that produced it so you can judge whether it matters here. A mod is markdown that instructs an agent; that is exactly why what it instructs is worth reading.
Nothing flagged
None of the 26 patterns this scan looks for appear in this file: no shell pipes, no recursive deletes, no credential paths, no hidden text, no instruction-override or anti-refusal phrasing, no agent-config snooping. That is not a guarantee, it is the absence of the things that are checkable.
Copies of this mod
1 near-identical copy found in the catalogue:
- resume-tailoring — 100% identical, 0 lines differ
How it starts
The opening of the file, as written. The whole thing — 1,320 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Resume Tailoring Skill
Overview
Generates high-quality, tailored resumes optimized for specific job descriptions while maintaining factual integrity. Builds resumes around the holistic person by surfacing undocumented experiences through conversational discovery.
Core Principle: Truth-preserving optimization - maximize fit while maintaining factual integrity. Never fabricate experience, but intelligently reframe and emphasize relevant aspects.
Mission: A person's ability to get a job should be based on their experiences and capabilities, not on their resume writing skills.
When to Use
Use this skill when:
- User provides a job description and wants a tailored resume
- User has multiple existing resumes in markdown format
- User wants to optimize their application for a specific role/company
- User needs help surfacing and articulating undocumented experiences
DO NOT use for:
- Generic resume writing from scratch (user needs existing resume library)
- Cover letters (different skill)
- LinkedIn profile optimization (different skill)
Quick Start
Required from user:
- Job description (text or URL)
- Resume library location (defaults to
resumes/in current directory)
Workflow:
- Build library from existing resumes
- Research company/role
- Create template (with user checkpoint)
- Optional: Branching experience discovery
- Match content with confidence scoring
- Generate MD + DOCX + PDF + Report
- User review → Optional library update
Implementation
See supporting files:
research-prompts.md- Structured prompts for company/role researchmatching-strategies.md- Content matching algorithms and scoringbranching-questions.md- Experience discovery conversation patterns
Workflow Details
Multi-Job Detection
Triggers when user provides:
- Multiple JD URLs (comma or newline separated)
- Phrases: "multiple jobs", "several positions", "batch", "3 jobs"
- List of companies/roles: "Microsoft PM, Google TPM, AWS PM"
What this file has done since we first saw it
Hashed on every crawl. A supply-chain change to an agent config is a question of when, not whether, so the history is kept rather than the latest state alone.
- 11d ago First seen · 1,320 lines · 45 tokens per session scan A c4d233bb4d9b
resume-tailoring is a skill published in the GitHub repository varunr89/resume-tailoring-skill (735 stars, last pushed 6mo ago), licensed MIT. It adds 45 tokens to every session and 8,531 once invoked, about $0.0002 per session on Opus 5. A static security scan graded it A with 0 findings. No closer match exists in the catalogue, so it is treated as the original; first seen 2026-08-30.
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