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 agentmods add commands/jananthan30/resume-builder/resumegit clone --depth 1 https://github.com/jananthan30/Resume-BuilderWhat 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 | $0.00025 | $0.10148 |
| Opus 5 | $0.00013 | $0.05074 |
| Sonnet 5 | $0.00005 | $0.02030 |
| Haiku 4.5 | $0.00003 | $0.01015 |
Grade A, and why
resume scanned grade A with 2 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 yesterday.
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.
Makes network callslowCapability
Not a fault in itself. Listed so you know the mod talks to something, and to what.
curl -s http://localhost:8100/health Runs shell commandslowCapability
Expected in a hook, worth knowing in a rule or an instructions file.
result = subprocess.run( How it starts
The opening of the file, as written. The whole thing — 842 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Resume Builder — Native Four-Role Team + Triple Scoring
Generate a tailored resume AND cover letter using Codex parallel tool execution with scoring-aware optimization. Every editorial decision maps to ATS (7 components) and HR (6 factors) scoring weights.
Job Description
$ARGUMENTS
CANDIDATE-FIT PREFLIGHT (MANDATORY FIRST GATE)
Before scorer startup, research, resume development, role/team invocation, output
or application-directory creation, DOCX generation, or tracker work, resolve
master_resume_path from config.json and save this exact job description to a
private temporary UTF-8 file. Screen only that configured master resume—never a
previously tailored resume. Generate one safe run_id, one safe case_id, and one
strict ISO as_of_date, then run:
python candidate_fit_preflight.py --resume <configured-master-resume> --job-description <private-exact-JD.txt> --run-id <run_id> --case-id <case_id> --as-of-date <YYYY-MM-DD> --json
Require exit 0 plus a valid candidate-fit-policy-v3 report bound to the same
IDs, date, master SHA-256, and exact-JD SHA-256. Canonically hash it as
candidate_fit_report_digest. Proceed only when threshold is exactly 70.0,
score >= 70, extraction_trustworthy is true, hard_knockouts is empty,
passed is true, and codes is empty. Exit 1, a score below 70 (including
60–69), or any hard knockout is REJECTED:CANDIDATE_FIT; stop with no team/role
invocation and no application directory, draft, DOCX, or tracker mutation. Exit
2 or an unavailable, malformed, stale, non-canonical, or digest-mismatched
report is FAILED:CANDIDATE_FIT_PREFLIGHT and fails closed. There is no automatic
or manual workflow bypass. ATS/HR baselines remain advisory and cannot override
candidate fit.
Instructions
You are the coordinator, not the resume author. The user has provided a job description above. You will:
- Pass the fixed candidate-fit gate against the configured master resume
- Internalize both advisory scoring engines before writing a single word
- Deconstruct the JD into a scoring blueprint
- Delegate drafting to the native
resume-writerwith least-authority context - Diagnose gaps by component weight, not guesswork
- Require an independent
resume-auditor, boundedresume-editorcorrections, and three deterministic authorization votes
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.
- yesterday First seen · 842 lines · 25 tokens per session scan A 5b0938b53325
resume is a command published in the GitHub repository jananthan30/Resume-Builder (76 stars, last pushed 17d ago), licensed MIT. It adds 25 tokens to every session and 10,148 once invoked, about $0.0001 per session on Opus 5. A static security scan graded it A with 2 findings (makes network calls, runs shell commands). No closer match exists in the catalogue, so it is treated as the original; first seen 2026-08-30.
Other commands, from other repositories
apply
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setup
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outcome
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add-portal
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add-template
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gmail-sync
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