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 Codagent-AI/agent-skills --skill review-approachgit clone --depth 1 https://github.com/Codagent-AI/agent-skillsWrote 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/codagent-ai/agent-skills/review-approach)<a href="https://agentmods.dev/skills/codagent-ai/agent-skills/review-approach"><img src="https://agentmods.dev/badge/skills/codagent-ai/agent-skills/review-approach/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/codagent-ai/agent-skills/review-approach"><img src="https://agentmods.dev/badge/skills/codagent-ai/agent-skills/review-approach.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 | $0.00077 | $0.00558 |
| Opus 5 | $0.00039 | $0.00279 |
| Sonnet 5 | $0.00015 | $0.00112 |
| Haiku 4.5 | $0.00008 | $0.00056 |
Grade A, and why
review-approach 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 — 59 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Review Approach
Review the completed proposal, specifications, design, and test plan together before task planning. Determine whether they form a coherent, implementation-ready definition with sound behavioral, technical, and testing decisions.
Read every definition artifact and relevant repository instructions. Inspect affected code, tests, and established patterns enough to judge feasibility and fit. Treat omissions as findings when an implementer or tester would otherwise have to invent a consequential decision.
Review focus
Trace important user flows and system interactions end to end. Look for material:
- contradictions, scope drift, dropped commitments, terminology drift, or incompatible assumptions;
- missing or untestable behavior, boundaries, state transitions, failure handling, permissions, data lifecycle, compatibility, or migration decisions;
- unclear ownership, component boundaries, data flow, concurrency, recovery, security, operability, rollout, or observability;
- testing strategy that conflicts with the definition, misses important integration or critical journeys, uses the wrong test layer, leaves acceptance substitutes ambiguous, or relies on unstated human judgment;
- avoidable coupling, complexity, maintenance burden, irreversible commitments, weak rationale, or overlooked alternatives.
Apply judgment rather than mechanically filling a checklist. Do not review task decomposition, implementation code quality, formatting, or parser mechanics except where they prevent the definition from being usable. Do not relitigate whether the approved feature should exist, broaden its scope, or invent optional features.
Report
For each consequential finding, cite the exact artifact section and repository evidence, classify it as a cross-artifact inconsistency, missing decision, or challenged decision, explain the concrete risk, and recommend a resolution or small set of real alternatives with a preferred choice.
Rank findings by impact and end with a direct readiness assessment. Say explicitly when the approach is sound and no consequential gap remains. Do not edit artifacts.
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 · 59 lines · 77 tokens per session scan A de9c1adc98f1
review-approach is a skill published in the GitHub repository Codagent-AI/agent-skills (30 stars, last pushed 1mo ago), licensed MIT. It adds 77 tokens to every session and 558 once invoked, about $0.0004 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…
insight-error-page
Write or audit an insight-kind error page for the Next.js dev overlay. Use when creating a new errors/ .mdx page, auditing an existing one, or checking that a page matches the framework fix cards. Covers page structure, title alignment, FixCard cards with Copy prompt button, code snippets, terminology verification…
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…