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 cdeust/ai-architect-mcp --skill pr-reviewgit clone --depth 1 https://github.com/cdeust/ai-architect-mcpWrote 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/cdeust/ai-architect-mcp/pr-review)<a href="https://agentmods.dev/skills/cdeust/ai-architect-mcp/pr-review"><img src="https://agentmods.dev/badge/skills/cdeust/ai-architect-mcp/pr-review/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/cdeust/ai-architect-mcp/pr-review"><img src="https://agentmods.dev/badge/skills/cdeust/ai-architect-mcp/pr-review.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 | $0.00000 | $0.00194 |
| Opus 5 | $0.00000 | $0.00097 |
| Sonnet 5 | $0.00000 | $0.00039 |
| Haiku 4.5 | $0.00000 | $0.00019 |
Grade A, and why
pr-review 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 10d 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.
What it actually says
PR Review Skill
Purpose
Review pull requests with full codebase context — not just the diff.
When to Use
- Reviewing any pull request
- Assessing whether a PR's changes are complete
- Checking for unintended side effects
Operations
- Changes: Use
ai_architect_codebase_detect_changeson the PR diff - Impact: For each changed symbol, run impact analysis
- Context: Get 360° views for modified symbols
- Gaps: Identify symbols that should have been modified but weren't
- Processes: Check all affected execution processes have test coverage
Workflow
Detect changes → Impact per symbol → Check completeness → Identify gaps → Summarize risk
Output
- Change summary with blast radius
- Missing modifications (symbols that should have changed)
- Process coverage assessment
- Risk level for the PR
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.
- 10d ago First seen · 30 lines · 0 tokens per session scan A 7d2a8749f883
pr-review is a skill published in the GitHub repository cdeust/ai-architect-mcp (1 stars, last pushed 4mo ago), licensed MIT. It costs nothing until one of its globs matches a file; then it loads 194 tokens. 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
cleanup-audit
Audit codebase for dead code, unused exports, orphaned files, and stale manifests.
link-check
Verify @file references in AIWG skills and agents against the linking contract — per-file or corpus-wide, with optional auto-fix.
receiving-code-review
Use when receiving code review feedback, before implementing suggestions, especially if feedback seems unclear or technically questionable - requires technical rigor and verification, not performative agreement or blind implementation.
requesting-code-review
Guides dispatching a code-reviewer subagent to verify work before proceeding. Use when completing tasks, implementing major features, or before merging to verify work meets requirements.
besimple-broccoli-blind
Non-interactive wrapper: plan-sketch -> auto-pick recommended options -> plan-write -> plan-critique-loop -> implement-from-plan -> claude-simplify-wrapper -> dedup -> code-review-loop. No PR creation and no Linear comments.
code-review-loop
Iterative review+fix loop for BASESHA..HEAD: generate findings, apply accepted fixes, run checks, commit, and re-review up to 3 iterations or until clean.