Borrowing it
Nothing to install: this file belongs to dhanushk-offl/resume-parser. Take a copy, put it at the same path in your own repository, and replace the rules that are about this project with yours.
curl -O https://raw.githubusercontent.com/dhanushk-offl/resume-parser/master/AGENTS.mdgit clone --depth 1 https://github.com/dhanushk-offl/resume-parserWrote 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/instructions/dhanushk-offl/resume-parser/agents-md)<a href="https://agentmods.dev/instructions/dhanushk-offl/resume-parser/agents-md"><img src="https://agentmods.dev/badge/instructions/dhanushk-offl/resume-parser/agents-md/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/instructions/dhanushk-offl/resume-parser/agents-md"><img src="https://agentmods.dev/badge/instructions/dhanushk-offl/resume-parser/agents-md.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 | $0.00533 | $0.00533 |
| Opus 5.5 | $0.00213 | $0.00213 |
| Sonnet 5.5 | $0.00107 | $0.00107 |
| Haiku 4.5 | $0.00053 | $0.00053 |
Grade A, and why
resume-parser AGENTS.md 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 1mo 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.
How it starts
The opening of the file, as written. The whole thing — 84 lines — stays where its author put it; the contents beside it link to each section on GitHub.
AGENTS.md — Agent Configuration for Resume Parser Skill
Skill Name
resume-parser-ats
Description
Deeply parses resume PDFs using the OpenResume 4-step algorithm, extracts structured information (Name, Email, Phone, Education, Work Experience, Skills, etc.), evaluates ATS compatibility, and provides actionable improvement suggestions.
Install
npx skills add dhanushk-offl/resume-parser
Capabilities
Tools
| Tool | Description |
|---|---|
parse_resume |
Accepts a resume PDF file path or raw text, runs the 4-step parsing algorithm, and returns structured resume data. |
analyze_resume |
Parses the resume and additionally computes an ATS compatibility score with per-field extraction confidence ratings. |
suggest_improvements |
Parses the resume, identifies issues, and returns structured, prioritized suggestions for fixing formatting, content, and ATS readability. |
When to Use This Skill
- When a user asks to parse, review, or analyze a resume
- When a user asks "is my resume ATS-friendly?"
- When a user asks for resume improvement suggestions
- When a user wants to compare what an ATS sees vs. what they intended
- When a user uploads or references a resume PDF
Input Formats
parse_resume
{
"input": {
"filePath": "/path/to/resume.pdf",
"rawText": "Optional: raw text if PDF not available"
}
}
analyze_resume
{
"input": {
"filePath": "/path/to/resume.pdf",
"rawText": "Optional: raw text if PDF not available",
"strictness": "moderate"
}
}
suggest_improvements
{
"input": {
"filePath": "/path/to/resume.pdf",
"rawText": "Optional: raw text if PDF not available",
"focusAreas": ["ats", "content", "formatting", "structure"]
}
}
Output Format
All tools return a structured JSON response:
{
"success": true,
"data": { ... },
"metadata": {
"parserVersion": "1.1.1",
"stepsCompleted": [1, 2, 3, 4],
"warnings": []
}
}
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.
- 1mo ago First seen · 84 lines · 533 tokens per session scan A 45d666e0a9ee
resume-parser AGENTS.md is an instructions file published in the GitHub repository dhanushk-offl/resume-parser (5 stars, last pushed 4mo ago), licensed MIT. It adds 533 tokens to every session, about $0.0021 per session on Opus 5.5. 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 2026-08-31.
Other instructions, from other repositories
vscode buildNext.instructions.md
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