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 tahirraufkeeyu/software-development-agent-stack--sdas --skill full-security-auditgit clone --depth 1 https://github.com/tahirraufkeeyu/software-development-agent-stack--sdasWrote 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/tahirraufkeeyu/software-development-agent-stack--sdas/full-security-audit)<a href="https://agentmods.dev/skills/tahirraufkeeyu/software-development-agent-stack--sdas/full-security-audit"><img src="https://agentmods.dev/badge/skills/tahirraufkeeyu/software-development-agent-stack--sdas/full-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/tahirraufkeeyu/software-development-agent-stack--sdas/full-security-audit"><img src="https://agentmods.dev/badge/skills/tahirraufkeeyu/software-development-agent-stack--sdas/full-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 | $0.00066 | $0.03119 |
| Opus 5 | $0.00033 | $0.01559 |
| Sonnet 5 | $0.00013 | $0.00624 |
| Haiku 4.5 | $0.00007 | $0.00312 |
Grade A, and why
full-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 9d 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 — 223 lines — stays where its author put it; the contents beside it link to each section on GitHub.
When to use
- Preparing for a release cut, external pentest, customer security questionnaire, or audit window (SOC2, ISO 27001, PCI).
- User says "run the full security sweep", "pre-release security check", "give me the pentest report", or "what's our security posture".
- Onboarding a new repository and establishing a baseline.
- Post-incident hardening where the team wants confirmation that no related findings remain.
Do not use this for a single-file review (use code-review) or for runtime incident triage (use incident-response). Do not use this as a substitute for a third-party pentest — this orchestrator produces internal evidence, not an attestation.
Chained skills
- secret-scanner — runs a deep sweep of the working tree and full git history for leaked credentials, writes findings to
security/findings/secrets.json. - dependency-audit — enumerates every manifest (
package-lock.json,poetry.lock,Gemfile.lock,go.sum,Cargo.lock,requirements.txt) and produces CVE findings insecurity/findings/dependencies.json. - security-audit — combined SAST + DAST + SCA pass, writes findings to
security/findings/audit.json. - container-scan — scans built images and their base layers; only runs if a
Dockerfile(orContainerfile) is present. Writessecurity/findings/container.json. - pentest-report — consumes all four JSON artifacts and produces a formal, dated report suitable for leadership or an external auditor.
Inputs
- Repository root (the working directory; default cwd).
- Optional: a released/candidate image reference (
ghcr.io/acme/api:1.4.0) to scan instead of building fromDockerfile. - Optional: a target environment URL if DAST should hit a staging deploy (
https://staging.acme.example). - Optional: a severity floor for the final report (defaults to
medium; findings below are listed but not counted toward overall risk).
Outputs
security/findings/secrets.json— raw secret-scanner output.security/findings/dependencies.json— raw dependency-audit output.security/findings/audit.json— raw security-audit output.security/findings/container.json— raw container-scan output (only if Dockerfile present).security/reports/pentest-report-<YYYY-MM-DD>.md— consolidated report with Executive Summary, Scope, Methodology, Findings (grouped by severity), Remediation Plan, and Appendices linking each raw JSON.
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.
- 9d ago First seen · 223 lines · 66 tokens per session scan A 4bcb8bea47de
full-security-audit is a skill published in the GitHub repository tahirraufkeeyu/software-development-agent-stack--sdas (18 stars, last pushed 4mo ago), licensed MIT. It adds 66 tokens to every session and 3,119 once invoked, about $0.0003 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 2026-08-30.
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…
next-cache-components-adoption
Turn on Cache Components in a Next.js app and resolve the blocking routes it surfaces. Use when the user wants to enable, adopt, or migrate to Cache Components, flip the cacheComponents flag, work through a flood of blocking-prerender / instant validation errors, run the cache-components-instant-false codemod, or…
next-cache-components-optimizer
Drive a Next.js route to instant navigation by setting up an agentic loop, under Cache Components / PPR, on initial load (hard navigation) and client-side navigation (soft navigation). Encode the goal as a failing @next/playwright instant() e2e and work it to green, one verified route at a time; the shipped test then…
next-partial-prefetching-adoption
Turn on Partial Prefetching in a Next.js app and work through the insights it surfaces. Use when the user wants to enable or adopt Partial Prefetching, flip the partialPrefetching flag, opt routes in with export const prefetch = 'partial', audit Link prefetch={true} behavior, preserve existing prefetched UI with…
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…