Getting it into your agent
It runs from inside its repository, so the clone comes first — what it calls does not travel with the file alone.
git clone --depth 1 https://github.com/XAIHT/Tlamatininpx agentmods add skills/xaiht/tlamatini/security_auditWrote 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/xaiht/tlamatini/security_audit)<a href="https://agentmods.dev/skills/xaiht/tlamatini/security_audit"><img src="https://agentmods.dev/badge/skills/xaiht/tlamatini/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/xaiht/tlamatini/security_audit"><img src="https://agentmods.dev/badge/skills/xaiht/tlamatini/security_audit.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 | $0.00059 | $0.01479 |
| Opus 5.5 | $0.00024 | $0.00592 |
| Sonnet 5.5 | $0.00012 | $0.00296 |
| Haiku 4.5 | $0.00006 | $0.00148 |
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 today.
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 — 114 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Security Audit
Current release: v1.90.0. Dated records below retain their original evidence dates.
HEADLESS IS FORBIDDEN. VISIBLE FOREGROUND EXECUTION ONLY. Every command, automated test, diagnostic, script, build, agent and browser must run in a visible foreground window on Angela's real desktop. Use forked CMD/PowerShell windows,
execute_forked_window: true, andheadless: false. Monitor live; if visibility cannot be confirmed, do not run. Read the mandatory execution policy.
Run a defensive, read-only security sweep over ${input.path}. This skill is
for authorized auditing of code you own or are permitted to test. Never use it
to evade detection or attack third-party systems.
Procedure
- Detect available scanners. Probe PATH (
where <tool>on Windows,which <tool>elsewhere) for each candidate. If${input.tools}is set, restrict to that subset. Skip any tool that is not installed — note it in the summary rather than failing. - Pick scanners by content. Run only what fits the target:
- Python present →
bandit -r "${input.path}" -f json(SAST) and, for dependency files,pip-audit -r <requirements file>orpip-auditin a project dir. - JS/TS present →
npx eslint "${input.path}" -f jsonif an eslint config exists. - Any language →
semgrep --config auto --json "${input.path}"when semgrep is installed (falls back to--config p/cioffline). - Secrets →
gitleaks detect --source "${input.path}" --report-format json(ortrufflehog filesystem) to catch committed credentials/keys. - Always run
ruff check "${input.path}" --output-format jsonwhen Python is present — its security-adjacent lint rules (S-prefixed) are cheap signal.
- Python present →
- Run each scanner via
chat_agent_executer. Capture stdout even on a non-zero exit code — most of these tools exit non-zero precisely because they found issues. Truncate any single tool's raw output to ~16000 chars before parsing. - Normalise findings into one shape:
{tool, file, line, severity, rule_id, message}. Map each tool's native severity ontocritical | high | medium | low. Treat any committed secret/credential ascritical. - Filter & count. Drop findings below
${input.min_severity}. Produceseverity_counts = {critical, high, medium, low}. - Summarise for action. Lead with the count of critical/high issues, name the top 3 things to fix first, and list which scanners were unavailable so the reader knows the coverage gaps.
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.
- today Changed b6f485ea12fc
- 2d ago Changed 6a07fd2311c8
- 3d ago Changed a894af648369
- 5d ago Changed · +3 lines b89016f9e010
- 29d ago Changed · +2 lines c7b867295211
- 1mo ago First seen · 109 lines · 59 tokens per session scan A a3cb157f02ad
security-audit is a skill published in the GitHub repository XAIHT/Tlamatini (15 stars, last pushed yesterday), licensed MIT. It adds 59 tokens to every session and 1,479 once invoked, about $0.0002 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.
Other skills, from other repositories
commit
Inspect git status, draft a commit message that matches the repo's style, and commit staged changes.
review
Review current code changes for bugs, regressions, test gaps, and project-guideline violations.
artifact-deploy
One-click deploy a user's pre-built app/artifact into their OWN AWS account and get a global public HTTPS link (Vercel-like), with a default TTL and promote-to-persistent. Use when the user says "deploy this", "ship this demo", "give me a public link", "share this externally", or "deploy to AWS".
explain-for
Explain a topic, code, error or design decision for one named audience (a 5-year-old, a manager, a designer, a grad student, a parent). Resolves who it is for, pins the ground truth first, then tunes vocabulary, analogy, tone and depth to that audience. Use when an audience is named.
papyrus-latex-suggestions
Propose inline replacement text (old -> new) as accept/reject suggestions, LaTeX 'suggesting mode' / track changes, rendered in the PDF. Use when the author wants concrete edit proposals to accept or reject. For remarks ABOUT the text rather than replacements, use papyrus-latex-comments.
pptagent
Create and revise editable PowerPoint presentations from a brief using HTML slide sources, rendering, and visual review. Use when the requested deliverable is a PPTX deck. The host authors the slides; text-only hosts can use an external visual reviewer.