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 d-o-hub/github-template-ai-agents --skill static-analysisgit clone --depth 1 https://github.com/d-o-hub/github-template-ai-agentsWrote 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/d-o-hub/github-template-ai-agents/static-analysis)<a href="https://agentmods.dev/skills/d-o-hub/github-template-ai-agents/static-analysis"><img src="https://agentmods.dev/badge/skills/d-o-hub/github-template-ai-agents/static-analysis/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/d-o-hub/github-template-ai-agents/static-analysis"><img src="https://agentmods.dev/badge/skills/d-o-hub/github-template-ai-agents/static-analysis.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 | $0.00102 | $0.01547 |
| Opus 5.5 | $0.00041 | $0.00619 |
| Sonnet 5.5 | $0.00020 | $0.00309 |
| Haiku 4.5 | $0.00010 | $0.00155 |
Grade A, and why
static-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 1mo 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 — 153 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Static Analysis & Linter Triage
Expert skill for managing static analysis, PR triage, and linting feedback loops across any programming language.
Quick Check
- Run pre-commit linters locally
- Classify CI lint failures by severity
- Auto-fix safe style/formatting issues
- Document every suppression with a valid reason
- File issues for complex architectural findings
When to Use
- Before committing changes (local linting).
- When CI quality gates or linting workflows fail.
- During PR reviews to triage static analysis findings.
- When integrating new languages or linters into a project.
Pre-commit Workflow
Always run local linters before pushing to minimize CI round-trips.
- Detect Changes: Identify files modified in the current session.
- Run Targeted Linters: Use tools like
markdownlint,shellcheck, or language-specific linters (e.g.,eslint,ruff) on changed files. - Verify Quality Gate: Run
./scripts/quality_gate.sh(if available) to ensure all local checks pass.
CI Integration
Read linter output from CI artifacts and PR annotations to identify regressions.
- Check CI Summary: Read
ci-summary.mdor GitHub Action logs. - Inspect Annotations: Look for line-specific comments from automated tools (Codacy, SonarCloud, GitHub Actions).
- Match to Source: Map CI errors back to local files and line numbers.
Agent Triage Workflow
Follow this structured process when responding to analysis findings:
- Classify Severity:
- Error: Must be fixed or formally suppressed. Blocks merge.
- Warning: Should be fixed if possible. Indicates potential future issues.
- Auto-fix Safe Findings:
- Immediately apply automated fixes for formatting (Prettier,
gofmt), imports (ruff,isort), or simple style rules.
- Immediately apply automated fixes for formatting (Prettier,
- Handle Complex Findings:
- If a fix is non-trivial or requires architectural changes, file a follow-up issue and document the technical debt.
- Suppressions:
- Never suppress an error without documenting why.
- Use the Required Comment Format.
What ships with it
1 file beside SKILL.md in the same directory: the scripts, references and assets a skill reads on demand. Not counted in the per-session cost; read them before you install if any of them is executable.
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.
- 1mo ago First seen · 153 lines · 102 tokens per session scan A a71f29e90e9f
static-analysis is a skill published in the GitHub repository d-o-hub/github-template-ai-agents (2 stars, last pushed yesterday), licensed MIT. It adds 102 tokens to every session and 1,547 once invoked, about $0.0004 per session on Opus 5.5. 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 2026-08-31.
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