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 skills add paruff/uFawkesAI --skill semgrepgit 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/semgrep)<a href="https://agentmods.dev/skills/paruff/ufawkesai/semgrep"><img src="https://agentmods.dev/badge/skills/paruff/ufawkesai/semgrep/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/skills/paruff/ufawkesai/semgrep"><img src="https://agentmods.dev/badge/skills/paruff/ufawkesai/semgrep.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 | $0.00037 | $0.00553 |
| Opus 5 | $0.00018 | $0.00277 |
| Sonnet 5 | $0.00007 | $0.00111 |
| Haiku 4.5 | $0.00004 | $0.00055 |
Grade A, and why
semgrep-ruleset-execution 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 8d 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
Skill: Semgrep Ruleset Execution
Load trigger:
"load semgrep-ruleset-execution skill"> DORA: Cap 1 (AI Policy) Token cost: Low
Purpose
Run Semgrep rulesets against Fawkes codebases.
Responsibilities
- Execute OWASP rules
- Execute custom Fawkes rules
- Validate findings
Inputs
- Semgrep config
Outputs
semgrep.json
Rulesets
| Ruleset | Purpose |
|---|---|
p/owasp-top-ten |
OWASP Top 10 vulnerabilities |
p/typescript |
TypeScript security patterns |
p/python |
Python security patterns |
p/go |
Go security patterns |
p/dockerfile |
Dockerfile best practices |
p/kubernetes |
K8s manifest security |
fawkes/custom |
Fawkes-specific patterns |
Fawkes Custom Rules
| Rule ID | Pattern | Severity |
|---|---|---|
fawkes-no-secrets-in-code |
Hardcoded API keys, tokens | Critical |
fawkes-no-plaintext-logs |
Secrets in log statements | High |
fawkes-secure-env |
Env vars with secrets | Medium |
fawkes-no-exec |
exec() with user input |
High |
Validation Rules
- All rulesets executed
- No critical findings
- Findings triaged
- SARIF output valid
Output Format
{
"skill": "semgrep-ruleset-execution",
"status": "pass | fail",
"rulesets_executed": 7,
"findings": {
"critical": 0,
"high": 1,
"medium": 3,
"low": 5,
"info": 2
},
"results": []
}
Success Criteria
- No critical findings
- All findings documented
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.
- 8d ago First seen · 84 lines · 37 tokens per session scan A b3fbf76de22f
semgrep-ruleset-execution is a skill published in the GitHub repository paruff/uFawkesAI (2 stars, last pushed 19d ago), licensed MIT. It adds 37 tokens to every session and 553 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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