Borrowing it
Nothing to install: this file belongs to mtarcure/claude-vibe-squad. Take a copy, put it at the same path in your own repository, and replace the rules that are about this project with yours.
curl -O https://raw.githubusercontent.com/mtarcure/claude-vibe-squad/main/.agents/skills/semgrep-rule-author/SKILL.mdgit clone --depth 1 https://github.com/mtarcure/claude-vibe-squadWrote 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/mtarcure/claude-vibe-squad/semgrep-rule-author)<a href="https://agentmods.dev/skills/mtarcure/claude-vibe-squad/semgrep-rule-author"><img src="https://agentmods.dev/badge/skills/mtarcure/claude-vibe-squad/semgrep-rule-author/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/mtarcure/claude-vibe-squad/semgrep-rule-author"><img src="https://agentmods.dev/badge/skills/mtarcure/claude-vibe-squad/semgrep-rule-author.svg" alt="Reviewed on agentmods" width="80" height="20"></a>- NVIDIA SkillSpector pass
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 | $0.00061 | $0.00504 |
| Opus 5 | $0.00030 | $0.00252 |
| Sonnet 5 | $0.00012 | $0.00101 |
| Haiku 4.5 | $0.00006 | $0.00050 |
Grade A, and why
semgrep-rule-author 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.
How it starts
The opening of the file, as written. The whole thing — 29 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Semgrep Rule Author
Turn a confirmed defect pattern into a Semgrep rule that finds its siblings without drowning the caller in false positives.
Steps
- Start from a confirmed instance, not from an idea. Write down the minimal vulnerable snippet and the minimal safe snippet that must not match.
- Decide the rule's shape: syntactic
patternfor a fixed misuse,patternswithpattern-inside/pattern-notfor context-dependent misuse, andmode: taintwithpattern-sources/pattern-sinkswhen the defect is a data-flow problem rather than a shape. - Prefer taint mode for injection classes. A syntactic rule for a data-flow bug produces the false-positive rate that gets rules disabled.
- Write
pattern-notclauses for the sanitizers and safe wrappers this codebase actually uses; generic sanitizer lists miss project-specific ones. - Use metavariables to bind the attacker-controlled value and
metavariable-patternto constrain it, so the rule expresses the condition rather than the syntax. - Set
severityand write amessagethat names the consequence and the fix, not the pattern. The message is what a reader acts on. - Test against a corpus: the known instances must all match, the known-safe snippets must not, and a full run over the repo must have a triageable hit count.
- Measure and record the false-positive rate on that run. A rule shipped without a measured rate is unverified.
- Version the rule with the defect class it came from, so
variant-analysiscan reuse it and future reviewers know its provenance.
Acceptance
- The rule was derived from a confirmed instance, with vulnerable and safe fixtures committed alongside.
- Data-flow defects use taint mode rather than syntactic matching.
- Project-specific sanitizers are excluded via
pattern-not. - All known instances match, all safe fixtures do not, and the repo-wide false-positive rate is measured and recorded.
- The message states consequence and fix, and the rule records its originating defect class.
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 · 29 lines · 61 tokens per session scan A e2ae1cde4269
semgrep-rule-author is a skill published in the GitHub repository mtarcure/claude-vibe-squad (148 stars, last pushed 2d ago), licensed MIT. It adds 61 tokens to every session and 504 once invoked, about $0.0003 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.
Other skills, from other repositories
cw-slice
Use before writing code for any Codewhale feature, upgrade, or refactor: find the existing owner of the behavior, bound the change to one reviewable slice, and fix the evidence bar before you start.
gh-find-prs
Survey open Codewhale PRs and triage each for mergeability and disposition against the real landing branch.
gh-compile-issues
Triage N GitHub issues into a coverage matrix: fetch each, check current code, classify already-done/quick-fix/design/defer with cited evidence.
review
Read-only correctness review with actionable findings first, tight file/line evidence, severity, and a concise residual-risk summary.
simplify
Improve clarity and reduce needless complexity after behavior is understood; preserve behavior and keep cleanup separate from correctness fixes.
review-team
Use when assigned a review or when an authored review boundary is reached.