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 skills/deonmenezes/mantishack/codeql-auditnpx skills add deonmenezes/mantishack --skill codeql-auditgit clone --depth 1 https://github.com/deonmenezes/mantishackWrote 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/skills/deonmenezes/mantishack/codeql-audit)<a href="https://agentmods.dev/skills/deonmenezes/mantishack/codeql-audit"><img src="https://agentmods.dev/badge/skills/deonmenezes/mantishack/codeql-audit.svg" alt="Measured on agentmods" 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 | $0.00026 | $0.00304 |
| Opus 5 | $0.00013 | $0.00152 |
| Sonnet 5 | $0.00005 | $0.00061 |
| Haiku 4.5 | $0.00003 | $0.00030 |
Grade A, and why
codeql-audit 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 4d 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
Use codeql_create_database then codeql_analyze (mantis_codeql MCP server) when you need dataflow-aware SAST beyond what regex/pattern tools (semgrep, ast-grep) can prove -- CodeQL's query suites trace actual source-to-sink data flow through the codebase.
Workflow:
codeql_create_database({ source_root, language, database_path })once per target/language. This is slow (can take minutes on large repos); don't repeat it unless the source changed.codeql_analyze({ database_path, query_suite }). Defaultquery_suiteis"security-extended"; use"security-and-quality"only if the user wants broader quality findings too.- Treat every SARIF result as a
candidatewith a dataflow-backed path, which is stronger recall evidence than a plain grep match -- but it is still not a confirmed finding. CodeQL's own dataflow models can miss framework-specific sanitization; verify the path manually before validating. - If
codeqlreportsavailable: false, fall back tosemgrep_scanandprogram-analysis'ssource_sink_scan/ast_grep_scanfor recall, and tell the user CodeQL-grade dataflow coverage wasn't available for this run.
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.
- 4d ago First seen · 13 lines · 26 tokens per session scan A aa3ab0ae0b2f
codeql-audit is a skill published in the GitHub repository deonmenezes/mantishack (493 stars, last pushed 23d ago), licensed Apache-2.0. It adds 26 tokens to every session and 304 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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