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 jeffrigby/somepulp-agents --skill code-auditinggit clone --depth 1 https://github.com/jeffrigby/somepulp-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/jeffrigby/somepulp-agents/code-auditing)<a href="https://agentmods.dev/skills/jeffrigby/somepulp-agents/code-auditing"><img src="https://agentmods.dev/badge/skills/jeffrigby/somepulp-agents/code-auditing/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/jeffrigby/somepulp-agents/code-auditing"><img src="https://agentmods.dev/badge/skills/jeffrigby/somepulp-agents/code-auditing.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 | $0.00040 | $0.01049 |
| Opus 5.5 | $0.00016 | $0.00420 |
| Sonnet 5.5 | $0.00008 | $0.00210 |
| Haiku 4.5 | $0.00004 | $0.00105 |
Grade A, and why
code-auditing 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.
This is a copy
86% identical to code-auditing — 13 lines differ, which has more behind it and is treated as the original. This page carries a canonical link to it rather than competing with it.
How it starts
The opening of the file, as written. The whole thing — 157 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Code Auditing Skill
Comprehensive methodology for systematic code quality audits.
When to Use
- Comprehensive code quality audits
- Security vulnerability assessments
- Technical debt identification
- Pre-release code reviews
- Best practices verification
- Library and dependency audits
Audit Phases
Phase 0: Pre-Analysis Setup
- Check for project configuration files (package.json, tsconfig.json, etc.)
- Identify tech stack and main libraries
- Check for linting/formatting configs
- Run existing linting/testing commands as baseline
- Load documentation for identified core libraries
Phase 1: Discovery
- Find all code files by type
- Create tracking list for each file
- Group files by module/feature for contextual analysis
Phase 2: File-by-File Analysis
For each file, analyze for:
- Dead code (unused functions, variables, imports)
- Code smells and anti-patterns
- Custom implementations that could use established libraries
- Security vulnerabilities
- Performance issues
- Outdated patterns or deprecated APIs
- Missing error handling
- Overly complex functions
- Duplicate code
Phase 3: Best Practices Verification
For every library and framework:
- Retrieve official documentation
- Compare implementation against official patterns
- Identify deviations from recommendations
- Note outdated usage patterns
- Flag discouraged anti-patterns
Phase 4: Pattern Detection
Look for recurring issues:
- Common anti-patterns across files
- Duplicated logic that could be abstracted
- Inconsistent coding styles
- Missing error handling patterns
Phase 5: Library Recommendations
For custom implementations:
- Check if current libraries provide the functionality
- Search for mature ecosystem packages
- Verify library health (commits, issues, activity)
- Check compatibility with project setup
Phase 6: Comprehensive Report
Generate detailed report with:
- Executive summary
- Critical issues requiring immediate attention
- File-by-file findings
- Prioritized action plan
- Effort estimates
- Library recommendations
What ships with it
2 files 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 Changed 5f9523d20032
- 1mo ago First seen · 157 lines · 40 tokens per session scan A fa6fdd906cf9
code-auditing is a skill published in the GitHub repository jeffrigby/somepulp-agents (8 stars, last pushed 1mo ago), licensed MIT. It adds 40 tokens to every session and 1,049 once invoked, about $0.0002 per session on Opus 5.5. A static security scan graded it A with 0 findings. It is 86% identical to code-auditing, differing in 13 lines, and is treated as a copy.
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