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/paruff/ufawkesai/codeqlnpx skills add paruff/uFawkesAI --skill codeqlgit clone --depth 1 https://github.com/paruff/uFawkesAIWrote 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/paruff/ufawkesai/codeql)<a href="https://agentmods.dev/skills/paruff/ufawkesai/codeql"><img src="https://agentmods.dev/badge/skills/paruff/ufawkesai/codeql.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 | $0.00030 | $0.00425 |
| Opus 5 | $0.00015 | $0.00212 |
| Sonnet 5 | $0.00006 | $0.00085 |
| Haiku 4.5 | $0.00003 | $0.00042 |
Grade A, and why
codeql-analysis 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 today.
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
Skill: CodeQL Analysis
Load trigger:
"load codeql-analysis skill"> DORA: Cap 1 (AI Policy) Token cost: Low
Purpose
Run CodeQL queries to detect deep security vulnerabilities.
Responsibilities
- Build CodeQL database
- Run language-specific queries
- Validate results
Inputs
- Source code
Outputs
codeql.sarif
Language Queries
| Language | Query Pack | Focus |
|---|---|---|
| JavaScript/TypeScript | js-security-extended |
Injection, auth, crypto |
| Python | python-security-extended |
Injection, path traversal |
| Go | go-security-extended |
Injection, SSRF, crypto |
Query Suites
| Suite | Coverage |
|---|---|
security-extended |
Broad security coverage |
security-and-quality |
Security + code quality |
Validation Rules
- Database built successfully
- All query suites executed
- No critical CodeQL findings
- SARIF output valid
Output Format
{
"skill": "codeql-analysis",
"status": "pass | fail",
"languages": ["typescript", "python"],
"findings": {
"critical": 0,
"high": 0,
"medium": 2,
"low": 4
},
"results": []
}
Success Criteria
- No critical CodeQL findings
- All languages analyzed
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.
- today First seen · 77 lines · 30 tokens per session scan A 5774f58fad8b
codeql-analysis is a skill published in the GitHub repository paruff/uFawkesAI (2 stars, last pushed 11d ago), licensed MIT. It adds 30 tokens to every session and 425 once invoked, about $0.0002 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 2026-09-03.
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