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/commands/saeedkolivand/ai-job-hunter-app/review-security)<a href="https://agentmods.dev/commands/saeedkolivand/ai-job-hunter-app/review-security"><img src="https://agentmods.dev/badge/commands/saeedkolivand/ai-job-hunter-app/review-security/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/saeedkolivand/ai-job-hunter-app/review-security"><img src="https://agentmods.dev/badge/commands/saeedkolivand/ai-job-hunter-app/review-security.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 | $0.00013 | $0.00171 |
| Opus 5 | $0.00006 | $0.00086 |
| Sonnet 5 | $0.00003 | $0.00034 |
| Haiku 4.5 | $0.00001 | $0.00017 |
Grade A, and why
review-security 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.
What it actually says
Run a security review.
- Load the
token-efficiency+security-checklistskills; readdocs/knowledge/security-rules.md. - Scope with graphify; stop at ~90% confidence. No repo-wide scan.
- Target =
$ARGUMENTSif given, else the currentgit diff. - Spawn the
tauri-security-reviewersubagent (Task) over the target — desktop/app/backend/AI/data/abuse/supply-chain lens. - Report severity-tagged findings; security/data findings round UP; HIGH/CRITICAL block (LOW/MEDIUM advisory).
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 · 13 lines · 13 tokens per session scan A 6826286f6f6d
review-security is a command published in the GitHub repository saeedkolivand/ai-job-hunter-app (54 stars, last pushed today), licensed Apache-2.0. It adds 13 tokens to every session and 171 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.
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