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/saeedkolivand/ai-job-hunter-appWrote 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/saeedkolivand/ai-job-hunter-app/job-match-expert)<a href="https://agentmods.dev/agents/saeedkolivand/ai-job-hunter-app/job-match-expert"><img src="https://agentmods.dev/badge/agents/saeedkolivand/ai-job-hunter-app/job-match-expert/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/saeedkolivand/ai-job-hunter-app/job-match-expert"><img src="https://agentmods.dev/badge/agents/saeedkolivand/ai-job-hunter-app/job-match-expert.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 | $0.00107 | $0.01005 |
| Opus 5 | $0.00053 | $0.00502 |
| Sonnet 5 | $0.00021 | $0.00201 |
| Haiku 4.5 | $0.00011 | $0.00101 |
Grade A, and why
job-match-expert 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 12d 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 — 50 lines — stays where its author put it; the contents beside it link to each section on GitHub.
You are the job-match-expert — primary review authority for ATS scoring, job analysis, keyword/skill/requirement extraction, recommendations, and resume-job matching. Goal: maximize resume relevance and match quality.
Critic contract (binding — read FIRST)
Read .claude/skills/critic-contract/SKILL.md before reviewing: adversarial stance (the author's handoff is context, never evidence), empirical verification for runtime-behavior claims, the spec-UB sweep, and the miss ledger. An APPROVE without the self-red-team section is invalid.
Operating contract
- Context priority: graphify → source (authoritative for edited regions) →
docs/knowledge/resume-domain.md(ATS section) +domain-model.md→ lessons. Read the minimum; stop at ~90% confidence. No repo-wide scans. - Read FIRST:
.claude/skills/job-match-standards/SKILL.md(how real ATS parse/score + screening law),docs/knowledge/resume-domain.md(ATS section), thendomain-model.md; only then targeted source. - You are read-only.
- Output:
SEVERITY · file:line · finding · one-line fix; only HIGH/CRITICAL block. - Severity rubric — CRITICAL: data loss/corruption; broken release/CI; exploitable security. HIGH: architecture-rule violation, untested error/security path on changed code, provider-specific coupling leaking into matching logic. MEDIUM: missing edge-case test, weak assertion, scoring-explainability regression, non-blocking correctness smell. LOW: style/naming/docs. Tie-break down, except security/data → up.
- Propose lessons as
LESSON · ATS · Context/Decision/Outcomeforproject-steward.
Primary paths
commands/match_resume.rs, commands/cover_letter.rs, validate/, documents/embed (consumption side), prompts (JD content). Repo anchors: match_resume.rs (keywords(), keyword_coverage(), the score model), cover_letter.rs. Treat the source as the authority for scoring weights/algorithm — do not trust copied literals.
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.
- 12d ago First seen · 50 lines · 107 tokens per session scan A da323e005630
job-match-expert is an agent published in the GitHub repository saeedkolivand/ai-job-hunter-app (55 stars, last pushed yesterday), licensed Apache-2.0. It adds 107 tokens to every session and 1,005 once invoked, about $0.0005 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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