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 zircote-plugins/sdlc-quality --skill aigit clone --depth 1 https://github.com/zircote-plugins/sdlc-qualityWrote 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/zircote-plugins/sdlc-quality/ai)<a href="https://agentmods.dev/skills/zircote-plugins/sdlc-quality/ai"><img src="https://agentmods.dev/badge/skills/zircote-plugins/sdlc-quality/ai/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/zircote-plugins/sdlc-quality/ai"><img src="https://agentmods.dev/badge/skills/zircote-plugins/sdlc-quality/ai.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 | $0.00067 | $0.01408 |
| Opus 5.5 | $0.00027 | $0.00563 |
| Sonnet 5.5 | $0.00013 | $0.00282 |
| Haiku 4.5 | $0.00007 | $0.00141 |
Grade A, and why
ai 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 — 267 lines — stays where its author put it; the contents beside it link to each section on GitHub.
AI-Assisted Development Standards
Guidance for implementing AI-assisted development requirements including context configuration, workflow integration, and quality practices.
Tooling
Available Tools: If using Claude Code, the
pr-review-toolkitprovides AI-powered code review agents. Thefeature-devplugin offers guided feature development workflows.
AI Context Configuration
Context Files (MUST)
Projects using AI assistants MUST maintain context files:
| File | Purpose | Location |
|---|---|---|
CLAUDE.md |
Claude-specific instructions | Repository root |
.cursorrules |
Cursor AI configuration | Repository root |
AI_CONTEXT.md |
Generic AI context | Repository root |
.github/copilot-instructions.md |
GitHub Copilot | .github/ |
Context File Content (MUST)
AI context files MUST include:
| Section | Content |
|---|---|
| Project overview | Brief description and purpose |
| Architecture | Key patterns and structures |
| Conventions | Naming, formatting, style rules |
| Constraints | What AI should NOT do |
| Key files | Important files to understand |
Context File Template
# Project Context for AI Assistants
## Overview
Brief project description and purpose.
## Architecture
- Pattern: [MVC/Clean Architecture/etc.]
- Key directories and their purposes
- Core abstractions
## Conventions
- Naming: camelCase for functions, PascalCase for types
- Error handling: Use Result types
- Testing: Unit tests alongside source
## Constraints
- Do NOT modify configuration files without asking
- Do NOT add new dependencies without approval
- Always run tests after changes
## Key Files
- `src/lib.rs` - Main library entry
- `src/config.rs` - Configuration handling
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 First seen · 267 lines · 67 tokens per session scan A d141be768051
ai is a skill published in the GitHub repository zircote-plugins/sdlc-quality (11 stars, last pushed 27d ago), licensed MIT. It adds 67 tokens to every session and 1,408 once invoked, about $0.0003 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 2026-08-31.
Other skills, from other repositories
setup
Interactive project setup from the ai-project-template — replaces the static SETUPGUIDE.md with a guided, multi-step workflow.
template-guide
Navigate template conventions, audit compliance, and guide upgrades for ai-project-template repos.
cut-release
Cut a clean release — bump versions across all files, update changelog, create GitHub release.
merge-to-main
Babysit a PR through CI — create, monitor, fix failures, merge when green.
sota-devsecops
State-of-the-art DevSecOps and software supply chain security (2026). Applies when building or auditing CI/CD pipelines, GitHub Actions workflows, supply chain controls, SBOM generation, SAST/secret-scanning gates, dependency management, container builds, container/artifact registries, IaC (Terraform), GitOps…
repo-scaffold
Scaffold or standardize a production-ready repository structure with specs, source layout, tests, CI, agent context, config examples, release notes, and operational docs. Use when starting a new repo, turning a prototype into a maintainable project, adding missing repository foundations, or creating a repo skeleton…