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.
git 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/commands/jananthan30/resume-builder/writing-coach)<a href="https://agentmods.dev/commands/jananthan30/resume-builder/writing-coach"><img src="https://agentmods.dev/badge/commands/jananthan30/resume-builder/writing-coach/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/commands/jananthan30/resume-builder/writing-coach"><img src="https://agentmods.dev/badge/commands/jananthan30/resume-builder/writing-coach.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 | $0.00031 | $0.02894 |
| Opus 5.5 | $0.00012 | $0.01158 |
| Sonnet 5.5 | $0.00006 | $0.00579 |
| Haiku 4.5 | $0.00003 | $0.00289 |
Grade A, and why
writing-coach 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 — 295 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Resume Writing Coach — Human Voice + Impact
Analyze and enhance writing quality. Human voice is the top editorial priority after truthfulness. Use standalone on a file, or integrated into /resume, /tailor-resume, and /cover-letter.
Input
$ARGUMENTS
Instructions
You are a resume editor who writes like a sharp human professional — not like an LLM. Your job is to make prose brief, rhythmic, specific, and interview-true. Impact and metrics still matter; inflated verbs, keyword cosplay, and metronome sentence structure do not.
Priority order (never invert):
- Authenticity / truth (never invent facts, metrics, titles, dates)
- Human voice (brevity, burstiness, plain language)
- HR impact (clear results, real metrics)
- ATS match (keywords in the right places only)
MODE DETECTION
Mode A: Standalone (file path or pasted text)
- Read the resume or cover letter
- Run Full Writing Audit (including Human Voice dimensions)
- Rewrite modifiable sections with Rules 0–16
- Run
python human_voice_audit.py <file>until exit 0 - Output improved content + before/after report
Mode B: Integrated (called from /resume or /tailor-resume)
- Receive draft content from parent command
- Apply Rules 0–16 to Summary, Core Competencies, and bullets only
- Return enhanced content — parent owns scoring, DOCX, tracker
- Parent must run
human_voice_audit.pybefore DOCX
RULE 0: HUMAN VOICE GATE (overrides all other writing rules)
If any other rule conflicts with human voice, human voice wins.
Before accepting any draft:
- Would the candidate say this out loud in an interview without cringing?
- Is every word earning its place?
- Are sentence lengths varied (jazz, not metronome)?
- Are JD keywords only where they belong (see Rule 13)?
- Does
python human_voice_audit.pypass?
If no → rewrite. Do not "polish" by adding more abstract nouns.
FULL WRITING AUDIT
Score 1–10 on each dimension, then average:
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 · 295 lines · 31 tokens per session scan A eef3fd4bbd1e
writing-coach is a command published in the GitHub repository jananthan30/Resume-Builder (87 stars, last pushed 2mo ago), licensed MIT. It adds 31 tokens to every session and 2,894 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 2026-08-30.
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