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 charlesjones-dev/claude-code-plugins-dev --skill security-auditgit clone --depth 1 https://github.com/charlesjones-dev/claude-code-plugins-devWrote 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/charlesjones-dev/claude-code-plugins-dev/security-audit)<a href="https://agentmods.dev/skills/charlesjones-dev/claude-code-plugins-dev/security-audit"><img src="https://agentmods.dev/badge/skills/charlesjones-dev/claude-code-plugins-dev/security-audit/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/charlesjones-dev/claude-code-plugins-dev/security-audit"><img src="https://agentmods.dev/badge/skills/charlesjones-dev/claude-code-plugins-dev/security-audit.svg" alt="Reviewed on agentmods" width="80" height="20"></a>- NVIDIA SkillSpector warn
SkillSpector: 1 finding, up to medium
These are SkillSpector’s own severities. On a checked sample its high-severity flags on skills were ~96% false positives — a documented command, a public API, a “never do X” rule — so we show them as a caution to read, not a verdict. Why →
- medium Excessive Agency · line 85 Skill enables autonomous high-impact decisions without human-in-the-loop verification. Critical operations (destructive commands, financial transactions, data deletion) should require explicit user confirmation.Fix: Add human-in-the-loop confirmation for destructive, irreversible, or high-impact operations. Never auto-execute commands that modify files, send data, or alter system state.
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 | $0.00028 | $0.02019 |
| Opus 5.5 | $0.00011 | $0.00808 |
| Sonnet 5.5 | $0.00006 | $0.00404 |
| Haiku 4.5 | $0.00003 | $0.00202 |
Grade A, and why
security-audit 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 — 148 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Security Audit
Produce a defensible audit of the requested repository. Consistent coverage, evidence, and visible uncertainty matter more than finding counts or agreement between reviewers. This workflow cannot guarantee identical findings or the absence of vulnerabilities.
Instructions
You are the coordinator. Read methodology.md for the checks and decision rules, and artifacts.md for the versioned data contract and commands. Follow these stages in order:
- Establish scope and provenance. Honor the user's paths, exclusions, budget,
baseline selection, and existing authorization. Default to the current repository,
including application code, jobs, scripts, configuration, and dependencies. Resolve
the repository root explicitly; a supplied URL alone does not authorize an external
penetration test. Read applicable repository guidance. Record revision, relevant
dirty state, skill/plugin versions and hashes, exposed model/reviewer/tool identities,
budget, and restrictions. Use
unknownornot exposedfor unavailable information. Read the plugin manifest; distinguish a file not inspected from one verified missing. This skill is versioned with the plugin. Host file-access settings are operational context: missing Claude settings or a count of deny rules neither blocks the audit nor establishes an application flaw. Default to repository review plus practical bounded local checks. Inspect checked-in deployment configuration and external-service integration code, but do not require live infrastructure access, vendor dashboards, service provisioning, or end-to-end production tests unless requested. State this boundary up front; never narrow an explicitly requested scope to make the status complete. - Inventory attack surfaces. Use deterministic discovery where practical, then trace registration, framework conventions, shared middleware, and dynamic paths. Create surface IDs and applicable check obligations before reviewing candidates. Record discovery gaps, including unsupported languages and generated code. Expand the inventory as new paths emerge; searches alone cannot establish completeness.
- Discover candidates. Review assigned surface/check pairs using the methodology. Preserve every substantive candidate in the ledger, including uncertain ones. Do fresh discovery before reading prior findings when practical; record any earlier exposure. In blind evaluation, never read baselines or evaluator expectations.
- Verify and challenge. Perform a separate pass that actively attempts to disprove each candidate. Trace protections and practical reachability; use bounded local reproductions where useful. Record counterevidence, assumptions, validation results, and a reasoned disposition. Independent disagreement is evidence to investigate; consensus is not proof. Keep potentially serious unresolved issues conspicuous.
- Assess severity and priority. Apply the qualitative rubric to demonstrated impact and prerequisites. Record confidence separately. Consolidate duplicate root causes while retaining all entry points and materially different impacts. Hardening is separate from confirmed vulnerabilities. Artifact v1 deliberately supports no numeric security or CVSS scores, compliance percentages, or overall security grade.
- Reconcile previous findings. After fresh discovery, select the latest relevant baseline or the explicitly supplied reports. Account for every prior finding with evidence or an explicit unresolved status. Absence never implies fixed. Preserve IDs across severity changes; use the legacy mapping procedure in the methodology.
- Validate and render. Write matching timestamped JSON and Markdown artifacts to
<audited-repository>/docs/security/YYYY-MM-DD-HHMMSS-security-audit.{json,md}(repository-relative, never filesystem/docs/security). Record timezone; avoid overwriting earlier runs. Run the supplied validator and renderer. Inspect the rendered report for unsupported claims as well as structural errors. Use the default concise reading copy: summary and contents first, findings before coverage. Keep the full ledger and commands in JSON; do not append reviewer reports or raw records to Markdown. Follow the report guidance. Release all audit-owned reviewers before final handoff. Apply the stopping rule below before final handoff; validation passing is not completion.
What ships with it
4 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 · -538 lines · +3 tokens per session scan B → A e1df3532d304
- 1mo ago First seen · 686 lines · 25 tokens per session scan B 92ff7a370693
security-audit is a skill published in the GitHub repository charlesjones-dev/claude-code-plugins-dev (35 stars, last pushed 6d ago), licensed MIT. It adds 28 tokens to every session and 2,019 once invoked, about $0.0001 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 2026-08-30.
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