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 agentmods add skills/mr-tbot/auto-everything/auto-audit-securitynpx skills add mr-tbot/Auto-Everything --skill auto-audit-securitygit clone --depth 1 https://github.com/mr-tbot/Auto-EverythingWrote 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/mr-tbot/auto-everything/auto-audit-security)<a href="https://agentmods.dev/skills/mr-tbot/auto-everything/auto-audit-security"><img src="https://agentmods.dev/badge/skills/mr-tbot/auto-everything/auto-audit-security.svg" alt="Measured on agentmods" 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 | $0.00123 | $0.05241 |
| Opus 5 | $0.00062 | $0.02620 |
| Sonnet 5 | $0.00025 | $0.01048 |
| Haiku 4.5 | $0.00012 | $0.00524 |
Grade A, and why
auto-audit-security 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 yesterday.
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 — 356 lines — stays where its author put it; the contents beside it link to each section on GitHub.
/auto-audit-security
An adversarial security review of this codebase, plus an honest compliance-readiness assessment — findings first, fixes only when you approve them.
The boundary, stated once and never blurred: a code audit produces INPUT EVIDENCE to a compliance program. It never produces the compliance artifact. SOC 2 is an attestation engagement performed under SSAE 18 by an independent licensed CPA firm; ISO 27001 is certified by an accredited body. What this skill produces is a readiness assessment: which technical controls are evidenced in the code, which are missing, and what an auditor will ask for that no repository can answer.
Two facts worth getting right, because vendors routinely get them wrong:
- The Trust Services Criteria comprise 61 criteria, of which 18 are the privacy category. Higher counts in circulation (64, 80+) come from counting points of focus as criteria — they are explicitly not criteria.
- A SOC 2 report is restricted-use. SOC 3 is the general-use report. If the goal is something publishable on a marketing site, that is SOC 3, and confusing the two misdirects the whole effort.
Everything this skill generates is IPE — information produced by the entity. A service auditor will test its completeness and accuracy before relying on it, so every artifact must record how it was produced, over what population, and at what time.
Step 1 — Scope And Authorization
Establish before running anything:
- What is in scope — repo only, or deployed environments too? Which environments?
- Authorization for active testing, in writing. Static review of code you own needs none. Any active scan (ZAP, nuclei, fuzzing, credential testing) requires explicit written authorization naming the specific target, and must never be pointed at production, at shared infrastructure, or at a third party. Staging, a local instance, or not at all. Third-party-hosted components have their own testing policies and are frequently out of bounds regardless of who owns the account.
- Which frameworks matter — SOC 2, ISO 27001, HIPAA, PCI DSS, GDPR/CCPA, or none. Ask; do not assume, since the applicable set drives everything downstream.
- Where findings may be written. Not a public issue tracker. See Handling below.
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.
- yesterday Changed · +46 lines · +19 tokens per session 714ecdef666d
- 5d ago First seen · 310 lines · 104 tokens per session scan A 57805171a339
auto-audit-security is a skill published in the GitHub repository mr-tbot/Auto-Everything (7 stars, last pushed 3d ago), licensed MIT. It adds 123 tokens to every session and 5,241 once invoked, about $0.0006 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 2026-08-31.
Other skills, from other repositories
systematic-debugging
Use when encountering any bug, test failure, or unexpected behavior, before proposing fixes.
local-ai-agents
Build local-first AI agents that run entirely on a developer workstation with Microsoft Foundry Local and Qwen function-calling models. Covers Small Language Models (SLMs), the OpenAI-compatible local endpoint, sandboxed local tools, local RAG with Chroma, local MCP servers, hybrid cloud/local routing, and the…
chronicle
Analyze Copilot session history for standup reports, usage tips, session search, and session reindexing. Use when the user asks for a standup, daily summary, usage tips, workflow recommendations, wants to search or find past sessions by keyword/file/PR, wants to reindex their session store, or asks about deleting…
imagegen
Generate or edit raster images when the task benefits from AI-created bitmap visuals such as photos, illustrations, textures, sprites, mockups, or transparent-background cutouts. Use when Codex should create a brand-new image, transform an existing image, or derive visual variants from references, and the output…
chat-pet-sprite-creation
Use when creating or changing VS Code chat pet sprite art, sprite sheets, state animations, eye treatments, Stable/Insiders variants, or pet transitions under src/vs/workbench/contrib/chat/browser/widget/media/chatPet.
cpu-profile-analysis
Analyze V8/Chrome CPU profiles (.cpuprofile) and DevTools trace files (Trace-.json). Use when: profiling performance, investigating slow functions, comparing code paths, finding bottlenecks, analyzing timeToRequest, understanding call trees from sampling profiler data, analyzing layout/paint/rendering, investigating…