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.
npx skills add jananthan30/Resume-Builder --skill cover-lettergit clone --depth 1 https://github.com/jananthan30/Resume-BuilderWrote 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/jananthan30/resume-builder/cover-letter)<a href="https://agentmods.dev/skills/jananthan30/resume-builder/cover-letter"><img src="https://agentmods.dev/badge/skills/jananthan30/resume-builder/cover-letter/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/jananthan30/resume-builder/cover-letter"><img src="https://agentmods.dev/badge/skills/jananthan30/resume-builder/cover-letter.svg" alt="Reviewed on agentmods" width="80" height="20"></a>- NVIDIA SkillSpector warn
SkillSpector: 2 findings, up to medium
These are SkillSpector’s own severities. On a checked sample its high-severity flags on skills were ~96% false positives — a documented command, a public API, a “never do X” rule — so we show them as a caution to read, not a verdict. Why →
- medium Agent Snooping · line 32 Skill enumerates or reads other installed skills. Access to other skills' SKILL.md files or the skills directory reveals prompt instructions, capabilities, and secrets that should be invisible to peer skills.Fix: Remove all code or instructions that list or read other skills' files or directories. Skills should operate independently; cross-skill access is a privilege escalation.
- medium Agent Snooping · line 42 Skill enumerates or reads other installed skills. Access to other skills' SKILL.md files or the skills directory reveals prompt instructions, capabilities, and secrets that should be invisible to peer skills.Fix: Remove all code or instructions that list or read other skills' files or directories. Skills should operate independently; cross-skill access is a privilege escalation.
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 | $0.00073 | $0.01240 |
| Opus 5 | $0.00036 | $0.00620 |
| Sonnet 5 | $0.00015 | $0.00248 |
| Haiku 4.5 | $0.00007 | $0.00124 |
Grade A, and why
cover-letter 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.
How it starts
The opening of the file, as written. The whole thing — 98 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Generate Cover Letter Only
Create a compelling one-page cover letter for a job application.
Job Description
The user provides the target job description when invoking this skill; treat that text as the exact JD throughout.
Instructions
You are the cover-letter coordinator. The user has provided a job description.
Your task:
Phase 1: Setup
-
Extract company name and job title from the job description
-
Search for a similar existing resume in the
applications/folder to understand what was already tailored:- List all subfolders in
applications/ - Compare folder job titles against the NEW job description's title and requirements
- If a similar resume is found: Read that resume to understand the applicant's tailored background for this type of role
- If NO similar resume is found: Read the master resume (path from
config.json→master_resume_path, or glob for*MASTER*RESUME*.md) to understand the applicant's background - Always also read the master resume for canonical details
- Treat an existing tailored resume as eligible evidence only if
resume_integrity_audit.py --config config.json --tailored <resume>exits 0. Otherwise use the master resume. - If this request also requires creating or changing a resume, run a complete native
resume-team/v2workflow (see the resume-team skill,skills/resume-team/SKILL.md) under a freshrun_id; never draft or patch a resume inside this skill. After that run authorizes an exact resume digest, cover-letter work must not alter the resume bytes or reuse stale authorization.
- List all subfolders in
-
Delegate JD analysis to the read-only native
resume-researcherusing only the job description. Validate itsresume-team-handoff/v1response. Use its rubric only to choose relevant, already-supported experiences; JD requirements are not evidence that the candidate has a skill. -
Create output folder at
applications/{CompanyName} - {JobTitle}/(if not exists) -
Save the job description as
job_description.txt(if not exists)
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 · 98 lines · 73 tokens per session scan A ba36a7826219
cover-letter is a skill published in the GitHub repository jananthan30/Resume-Builder (83 stars, last pushed 27d ago), licensed MIT. It adds 73 tokens to every session and 1,240 once invoked, about $0.0004 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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