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/job-fitgit 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 | $0.00014 | $0.01025 |
| Opus 5 | $0.00007 | $0.00513 |
| Sonnet 5 | $0.00003 | $0.00205 |
| Haiku 4.5 | $0.00001 | $0.00103 |
Grade A, and why
job-fit 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 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.
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 — 95 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Job Fit Pre-Screen — Deterministic GO/NO-GO Gate
Evaluate the configured master resume against this exact job description before any resume work begins.
Input
$ARGUMENTS
CANDIDATE-FIT PREFLIGHT (MANDATORY FIRST GATE)
-
Read
config.jsonand resolve its exactmaster_resume_path. This configured master is the only resume allowed in the assessment. Never use a previous tailored resume, application resume, or “best match” template. -
Put the exact job description in a private temporary UTF-8 file. Do not create an application/output directory, resume draft, DOCX, or tracker row.
-
Generate one safe
run_id, one safecase_id, and one strict ISO calendaras_of_date, then capture the sole intended machine output from: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 -
Parse only the JSON report. Require
schema_version: "1.0.0",policy_version: "candidate-fit-policy-v3",scorer_version: "evidence-match-v1", the exact run/case IDs and date, exact master/JD SHA-256 digests, exactthreshold: 70.0, all seven named component scores, a booleanextraction_trustworthy,hard_knockouts,passed, and orderedcodes. Recompute the canonical JSON SHA-256 and display it ascandidate_fit_report_digest. -
Proceed status is valid only when the process exits
0,score >= 70, extraction is trustworthy,hard_knockoutsis empty,passedis true, andcodesis empty. No dimension, recommendation, ATS score, HR score, or user preference can compensate for a failed condition. -
Exit
1, any score below 70, or any hard knockout isREJECTED:CANDIDATE_FIT. Exit2or an unavailable, malformed, non-canonical, stale, or digest-mismatched report isFAILED:CANDIDATE_FIT_PREFLIGHT. Both fail closed and authorize no tailoring, role/native-team invocation, output, DOCX, or tracker operation.
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 · 95 lines · 14 tokens per session scan A d35cbdbcb1ed
job-fit is a command published in the GitHub repository jananthan30/Resume-Builder (76 stars, last pushed 17d ago), licensed MIT. It adds 14 tokens to every session and 1,025 once invoked, about $0.0001 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.
Other commands, from other repositories
apply
You are orchestrating a two-agent job application workflow. The job posting is provided below as $ARGUMENTS (either a URL or pasted text).
setup
You are running the onboarding setup for the AI Job Search framework. Your goal is to collect the user's professional information and populate all profile files so the /apply workflow works out of the box.
outcome
You are recording what happened to a job application: progress updates (interview invitations, stages completed, offers) and final resolutions (hired, rejected, no response). The data lands in two places the framework already reads but nothing systematically writes.
add-portal
You are helping the user build a job-portal search skill for a job board in their market. The repo ships worked examples of the pattern (four Danish portals plus the country-agnostic linkedin-search and freehire-search), and the README invites users elsewhere to build equivalents — this command turns that invitation…
add-template
You are helping the user register their own CV or cover letter template with the AI Job Search framework — LaTeX, Typst, or any other toolchain that compiles to PDF from the command line. The framework ships with moderncv (banking style) for CVs and a custom cover.cls for cover letters. This command lets the user swap…
gmail-sync
You are scanning the user's Gmail for status signals on tracked job applications (interview invites, assessment links, offers, rejections) and, once approved, writing the detected changes into jobsearchtracker.csv and documents/applications/ /outcome.md - the same two places /outcome writes to, in the same schema.