review

review is a skill for Claude Code, Codex from rmjosea/agentic-sdlc-kit. It costs 67 tokens per session (669 once invoked), scanned A, original, MIT.

A non-editing workflow for assessing a completed or ongoing code change against its requirements and engineering standards.

In plain words
What is it for?
Use it for code review, implementation verification, acceptance review, or independent pre-merge assessment.
Why use it?
It bases conclusions on the actual diff and executed checks, helping find missing behaviour, regressions, and unsupported claims before merging.

Skill for Claude CodeCodex

Install

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.

agentmods
npx agentmods add skills/rmjosea/agentic-sdlc-kit/review
Any agent
npx skills add rmjosea/agentic-sdlc-kit --skill review
Clone the repo
git clone --depth 1 https://github.com/rmjosea/agentic-sdlc-kit

Made for: Claude Code, Codex.

Wrote 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.

agentmods badge for review

README.md
[![agentmods](https://agentmods.dev/badge/skills/rmjosea/agentic-sdlc-kit/review.svg)](https://agentmods.dev/skills/rmjosea/agentic-sdlc-kit/review)
Your own site
<a href="https://agentmods.dev/skills/rmjosea/agentic-sdlc-kit/review"><img src="https://agentmods.dev/badge/skills/rmjosea/agentic-sdlc-kit/review.svg" alt="Measured on agentmods" height="20"></a>
Per session 67 Skills are progressive disclosure: only the name and description are preloaded; the body loads when the skill is used.
When invoked 669 The whole file, excluding the scripts and references it only reads on demand.
Security scan A 0 findings. Scan, not verified.
Origin original No closer match found in the catalogue.
Token cost

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.

ModelPer sessionOnce invoked
Fable 5 $0.00067 $0.00669
Opus 5 $0.00034 $0.00334
Sonnet 5 $0.00013 $0.00134
Haiku 4.5 $0.00007 $0.00067

Measured 4d ago against content hash 72d14b60c1e9, method: parsed. Prices are Anthropic first-party input rates as of 2026-08-30, from the pricing page.

Security

Grade A, and why

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 4d 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.

.agents/skills/review/SKILL.md · 88 lines

How it starts

The opening of the file, as written. The whole thing — 88 lines — stays where its author put it; the contents beside it link to each section on GitHub.

Review an Implementation

Review the actual diff and observed behavior. Do not rely on the implementer's summary as evidence.

Review is non-mutating by default. Report findings without editing unless the user explicitly asks for fixes.

State whether the review is independent or a self-review. Treat only a fresh session or agent that did not implement the change as independent. High-risk work reviewed only by its implementer must receive blocked, not approved.

Establish scope

  1. Resolve and record the fixed base/head or equivalent working-tree scope.
  2. Capture committed and uncommitted changes within that scope.
  3. Locate the authoritative intent: spec, accepted request, issue, contract, or reproduced prior behavior; then locate any plan and repository guidance.
  4. Identify checks that can verify the acceptance criteria.

If no spec exists, verify against the available authoritative intent. Do not invent missing intent; mark product conformance not applicable only when no reliable source exists.

Axis 1: intent conformance

Check:

  • required behavior and acceptance criteria;
  • traceability from available source items to tasks and evidence;
  • missing, partial, or extra behavior;
  • business rules, failures, and edge cases;
  • externally observable quality constraints;
  • unexplained deviation from confirmed scope.

Axis 2: engineering quality

Check:

  • correctness and regression risk;
  • simplicity and unnecessary abstraction;
  • unrelated or overly broad changes;
  • data integrity and compatibility;
  • trust boundaries, authorization, secrets, and unsafe effects;
  • error handling, recovery, and observability;
  • tests, static checks, and documentation;
  • maintainability within repository conventions.

Read references/security.md only when the change handles authentication, authorization, untrusted input, secrets, personal data, payments, external actions, or another trust boundary.

Validate

Run relevant checks when safe and available. Distinguish:

Read the full file on GitHub · 88 lines

Files

What ships with it

2 files beside SKILL.md in the same directory: the scripts, references and assets a skill reads on demand. Not counted in the per-session cost; read them before you install if any of them is executable.

Changes

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.

  1. 4d ago First seen · 88 lines · 67 tokens per session scan A 72d14b60c1e9

Subscribe to this mod's changes

review is a skill published in the GitHub repository rmjosea/agentic-sdlc-kit (2 stars, last pushed 1mo ago), licensed MIT. It adds 67 tokens to every session and 669 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 2026-08-31.

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