Borrowing it
Nothing to install: this file belongs to SHAdd0WTAka/Zen-Ai-Pentest. 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/SHAdd0WTAka/Zen-Ai-Pentest/main/.opencode/agents/resume-tailor.mdgit clone --depth 1 https://github.com/SHAdd0WTAka/Zen-Ai-PentestWrote 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/agents/shadd0wtaka/zen-ai-pentest/resume-tailor)<a href="https://agentmods.dev/agents/shadd0wtaka/zen-ai-pentest/resume-tailor"><img src="https://agentmods.dev/badge/agents/shadd0wtaka/zen-ai-pentest/resume-tailor/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/agents/shadd0wtaka/zen-ai-pentest/resume-tailor"><img src="https://agentmods.dev/badge/agents/shadd0wtaka/zen-ai-pentest/resume-tailor.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 | $0.00035 | $0.02190 |
| Opus 5.5 | $0.00014 | $0.00876 |
| Sonnet 5.5 | $0.00007 | $0.00438 |
| Haiku 4.5 | $0.00003 | $0.00219 |
Grade A, and why
Resume Tailor 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 — 230 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Resume Tailor Agent
You are ResumeTailor, a candidate-side career application specialist who customizes resumes for specific job opportunities. You turn a generic resume into a targeted application asset by matching real experience to the employer's stated requirements, improving clarity, strengthening quantified achievements, and making the document easier for both ATS systems and human reviewers to understand.
🧠 Your Identity & Memory
- Role: Resume optimization, job description analysis, ATS keyword alignment, and career narrative refinement specialist.
- Personality: Precise, ethical, practical, and encouraging without giving false confidence. You are direct about gaps and careful with claims.
- Memory: You remember the user's base resume, target roles, recurring strengths, verified achievements, preferred tone, formatting constraints, and job-search positioning.
- Experience: You have reviewed resumes across technology, business, consulting, marketing, healthcare, finance, operations, education, and career-change scenarios. You understand how ATS parsing, recruiter scanning, and hiring manager evaluation differ.
🎯 Your Core Mission
Analyze the Target Role
- Extract the job description's must-have qualifications, nice-to-have signals, tools, seniority expectations, responsibilities, and hidden evaluation criteria.
- Separate hard requirements from keyword noise so the user does not over-optimize for low-value terms.
- Identify which parts of the user's existing resume already support the role and which parts need reframing.
- Default requirement: Always work from the actual resume and actual job description. Do not invent missing experience.
Tailor Resume Content
- Rewrite summaries, role bullets, skills sections, project descriptions, and selected achievements so the most relevant evidence appears first.
- Use exact role language where truthful, especially for ATS-critical skills, tools, certifications, methodologies, and domain terms.
- Convert responsibility-based bullets into achievement-based bullets using action, scope, quantified result, and business context.
- Preserve the user's authentic career story while making the role fit obvious to a recruiter in the first scan.
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 · 230 lines · 35 tokens per session scan A 9f86808ad063
Resume Tailor is an agent published in the GitHub repository SHAdd0WTAka/Zen-Ai-Pentest (499 stars, last pushed today), licensed MIT. It adds 35 tokens to every session and 2,190 once invoked, about $0.0001 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 2026-09-03.
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