resume-parser AGENTS.md

resume-parser AGENTS.md is an instructions file for Codex, OpenCode from dhanushk-offl/resume-parser. It costs 533 tokens per session, scanned A, original, MIT.

An agent skill for reading resume PDFs or text, extracting details such as contact information, education, work history, and skills, and checking how well the resume can be read by applicant-tracking systems.

In plain words
What is it for?
Use it to parse resumes, assess applicant-tracking-system compatibility, and receive prioritized suggestions for improving their formatting and content.
Why use it?
It helps compare the intended resume with the structured information an applicant-tracking system may extract and identifies problems that could reduce readability.

Instructions file for CodexOpenCode

Install

Getting it into your agent

One page per mod, every tool's command on it. A separate URL per tool would split the same page into five that compete with each other.

agentmods
npx agentmods add instructions/dhanushk-offl/resume-parser/agents-md
Clone the repo
git clone --depth 1 https://github.com/dhanushk-offl/resume-parser

Made for: Codex, OpenCode.

Wrote 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.

agentmods badge for resume-parser AGENTS.md

README.md
[![agentmods](https://agentmods.dev/badge/instructions/dhanushk-offl/resume-parser/agents-md.svg)](https://agentmods.dev/instructions/dhanushk-offl/resume-parser/agents-md)
Your own site
<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="Measured on agentmods" height="20"></a>
Per session 533 This file is loaded in full into every session.
When invoked 533 The same file — it is already loaded in full.
Security scan A 0 findings. Scan, not verified.
Origin original No closer match found in the catalogue.
Token cost

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.

ModelPer sessionOnce invoked
Fable 5 $0.00533 $0.00533
Opus 5 $0.00267 $0.00267
Sonnet 5 $0.00107 $0.00107
Haiku 4.5 $0.00053 $0.00053

Measured 5d ago against content hash 45d666e0a9ee, method: parsed. Prices are Anthropic first-party input rates as of 2026-08-30, from the pricing page.

Security

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 5d 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.

AGENTS.md · 84 lines

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": []
  }
}

Read the full file on GitHub · 84 lines

Changes

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.

  1. 5d ago First seen · 84 lines · 533 tokens per session scan A 45d666e0a9ee

Subscribe to this mod's changes

resume-parser AGENTS.md is an instructions file published in the GitHub repository dhanushk-offl/resume-parser (5 stars, last pushed 3mo ago), licensed MIT. It adds 533 tokens to every session, about $0.0027 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 2026-08-31.

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