Agent skill

Post-Feature Review

by jsmastery-pro in jsmastery-pro/jsm-agent-skill

Compares a finished feature with its plan, the project's architecture and design rules, and production-readiness checks, then reports issues without fixing them.

MITAuto-check passedDevelopment

Install Post-Feature Review

skills CLI
$ npx skills add jsmastery-pro/jsm-agent-skill --skill review -a claude-code

Project install by default; add -g for ~/.claude/skills/.

GitHub CLI
$ gh skill install jsmastery-pro/jsm-agent-skill review --agent claude-code

Project scope by default; add --scope user for a personal install. Needs GitHub CLI 2.90.0 or later (public preview).

Manual copy
$ git clone --depth 1 https://github.com/jsmastery-pro/jsm-agent-skill.git skills-src && mkdir -p .claude/skills && cp -r skills-src/skills/review .claude/skills/review && rm -rf skills-src

Use ~/.claude/skills/ instead of .claude/skills for a personal install. The folder must contain SKILL.md.

Claude Code skills documentation · loads skills from .claude/skills/

Facts

Skill name
review
GitHub stars
218
Token cost
~1.3k tokens
SKILL.md length
669 words
Files
1
Skills in repo
5
Repo updated
First seen
Licence
MIT

At a glance

Compares a finished feature with its plan, the project's architecture and design rules, and production-readiness checks, then reports issues without fixing them.

  • Works in 4 steps: Understand What Should Have Been Built → Review in Three Layers → Report What You Found → …
  • Finishing a feature and wanting a check before moving to the next one
  • SKILL.md covers What This Skill Does Not Do, Step 1 — Understand What…, Step 2 — Review in Three Layers and Step 3 — Report What You Found, plus 3 more sections
  • Instructions only: no scripts, shell commands, URLs or credentials in SKILL.md

What it does

Run after each feature is built, this skill is a review pass that never edits code. It first sets the benchmark by reading the implementation plan from `/architect` if there is one, the original feature description and any context files on architecture boundaries, code standards and design rules. With no plan, it asks the developer what the feature was meant to do before judging anything.

The review has three layers. The first checks the code against the plan and flags what was planned but missing and what was built but never requested. The second looks for drift from the system: misplaced responsibilities such as UI logic in API routes, hardcoded values where design tokens belong, naming and error handling that differ from project norms, and new patterns where an existing one fits. The third covers production readiness. Findings are reported so the developer decides what to fix.

When your agent uses it

  • Finishing a feature and wanting a check before moving to the next one
  • Verifying that generated code stayed inside the planned scope
  • Looking for architecture or design-system violations in AI-written changes

Example prompts

  • “Review the checkout feature we just built against the plan before I merge.”
  • “Check whether the new settings page follows our design tokens and architecture boundaries.”
  • “Run a post-build review of the notifications work and just report the issues.”

Requirements

  • A feature description or implementation plan to review against

Workflow steps

4 steps, taken from the step headings in SKILL.md.

  1. Understand What Should Have Been Built
  2. Review in Three Layers
  3. Report What You Found
  4. Let the Developer Decide

What it can do on your machine

Read from SKILL.md and the folder at commit fd85d6a. It shows what the files ask for, not the result of running them.

  • Tool permissions

    Pre-approves nothing: there is no allowed-tools line, so your agent's usual permission prompts apply.

    From allowed-tools in the SKILL.md frontmatter.

  • Runs code

    No scripts in the folder and no shell commands in SKILL.md.

    From the folder's file list and the shell code blocks in SKILL.md.

  • Network

    No URLs in SKILL.md.

    From URLs in SKILL.md, links to its own repository left out.

  • Credentials

    Names no API keys, tokens, secrets or passwords.

    From names ending in _API_KEY, _TOKEN, _SECRET, _KEY or _PASSWORD in SKILL.md.

Context cost

Post-Feature Review loads about 1.3k tokens when it runs. Until then it costs about 53 tokens; SKILL.md has 669 words of instructions outside code blocks.

Always · name and description, kept in context so the agent knows when to use it
~53
When it runs · the whole SKILL.md, loaded when a task matches
~1.3k

Estimates: characters ÷ 4, the usual rule of thumb; real counts depend on the model's tokenizer. Scripts and assets cost tokens only if the agent reads them.

Safety

Auto-check passed

The automated check found no risky patterns in SKILL.md.

Automated static check — not a guarantee. Review scripts before installing. It scans the text of SKILL.md for risky patterns (piping downloads into a shell, reading credential files, hidden Unicode, destructive commands); files beside SKILL.md are not scanned.

SKILL.md

The full file from jsmastery-pro/jsm-agent-skill at commit fd85d6a, republished under its MIT licence (© jsmastery-pro). 669 words, ~1,281 tokens.

Download SKILL.mdSave it as .claude/skills/review/SKILL.md (or your agent's skills folder).
name
review
description
After building a feature, verify it matches what was planned, respects the system architecture and design standards, and is ready for production. Reports issues clearly so the developer decides what to fix.

Building is not done when the code runs. It is done when the code is correct.

AI moves fast. Fast means things get built that work on the surface but drift from the architecture, violate the design system, or miss edge cases that matter. This skill catches those things before they compound into bigger problems.

Run this after every feature. Before you move on.

What This Skill Does Not Do

It does not fix anything. It reports what it finds and lets the developer decide what matters and what to do about it. Fixing without understanding is how problems get buried, not solved.


Step 1 — Understand What Should Have Been Built

Before reviewing anything, establish the benchmark.

Read in this order:

  • The implementation plan from /architect if one exists
  • The feature description or task that was given
  • Any relevant context files — architecture boundaries, code standards, design rules

If no plan exists, ask the developer to describe what the feature was supposed to do before reviewing. You cannot verify correctness without knowing what correct looks like.


Step 2 — Review in Three Layers

Layer 1 — Does it match the plan?

Compare what was built against what was planned.

Check:

  • Every part of the feature description — is it all there?
  • The decisions made during planning — are they reflected in the code?
  • The scope — did the implementation stay within bounds or add things that were not asked for?

Flag anything that was planned but missing. Flag anything that was built but not planned.

Layer 2 — Does it respect the system?

This is where AI drift most commonly happens. The feature works, but it violates rules that the project depends on.

Check:

  • Architecture boundaries — does code in the right place own the right responsibilities? No UI logic in API routes. No DB calls in components. Whatever the project's boundaries are — are they respected?
  • Design system — are the correct tokens, classes, and patterns used? Any hardcoded values that should be variables? Any raw color classes that should use the design system?
  • Code standards — naming conventions, file organisation, TypeScript strictness, error handling patterns — do they match what the project established?
  • Existing patterns — does this feature introduce a new pattern when an existing one should have been used?
Layer 3 — Is it production ready?

Check:

  • Error handling — what happens when things go wrong? Are errors caught and handled or does the feature silently fail?
  • Edge cases — empty states, loading states, missing data — are these handled?
  • Console errors — any errors or warnings in the browser or terminal?
  • Obvious bugs — anything that would clearly break for a real user?

Show full SKILL.md (240 more words)Show less

Step 3 — Report What You Found

After completing all three layers, produce a clear report. Do not bury issues. Do not soften them. Report honestly so the developer can make informed decisions.

## Review — [Feature Name]

### Layer 1 — Plan alignment
[PASS / ISSUES FOUND]
[List any gaps between what was planned and what was built]

### Layer 2 — System integrity
[PASS / ISSUES FOUND]
[List any architecture, design, or code standard violations]

### Layer 3 — Production readiness
[PASS / ISSUES FOUND]
[List any error handling gaps, edge cases, or obvious bugs]

### Summary
[X] issues found across [Y] layers.

[If no issues: "No issues found. This feature is ready to ship."]
[If issues: "Resolve the above before moving to the next feature."]

Step 4 — Let the Developer Decide

After presenting the report, stop. Do not start fixing. Do not suggest fixes unless the developer asks.

Wait for the developer to:

  • Ask you to fix a specific issue
  • Tell you an issue is intentional and can be ignored
  • Confirm everything is resolved and ready to move on

The developer owns the quality decision. You inform it.


Severity Guide

Not all issues are equal. Use this to help the developer prioritise:

Critical — fix before moving on

  • Architecture boundary violations that will break future features
  • Missing error handling that causes silent failures
  • Functionality that was planned but completely missing

Important — fix soon

  • Design system drift that will cause UI inconsistency
  • Code standard violations that will compound across the codebase
  • Edge cases that a real user will encounter

Minor — fix when convenient

  • Naming inconsistencies that do not affect behaviour
  • Missing optimisations
  • Style issues that do not affect the design system

Label each issue with its severity so the developer can triage quickly.


The Standard

The question this skill answers is not "does it work?"

The question is "is it correct?"

Working and correct are not the same thing. A feature can work today and break the project tomorrow. Review exists to catch the difference.

© jsmastery-pro, MIT. Rendered from Markdown: HTML in the file is shown as text, images as links, and headings moved down two levels. Raw file

Files

Just SKILL.md in skills/review of jsmastery-pro/jsm-agent-skill.

Open the folder on GitHubat commit fd85d6a

Compare with similar skills

Post-Feature Review next to the 5 skills that share the most tags, products or categories with it. Stars are the repository's; “used in” counts other GitHub owners with a copy.

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Dignified Python Standardsdocling-project/docling69k—~1.5kAutomated safety check: PassApache-2.0
Clean Code GuardamElnagdy/guard-skills1.3k2 repos~4.3kAutomated safety check: PassMIT
Archify Reviewtt-a1i/archify81k—~415Automated safety check: PassMIT

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Categories

Questions about Post-Feature Review

What does Post-Feature Review do?

Compares a finished feature with its plan, the project's architecture and design rules, and production-readiness checks, then reports issues without fixing them. Run after each feature is built, this skill is a review pass that never edits code. It first sets the benchmark by reading the implementation plan from `/architect` if there is one, the original feature description and any context files on architecture boundaries, code standards and design rules.

When should I use Post-Feature Review?

Post-Feature Review fits situations like: finishing a feature and wanting a check before moving to the next one; verifying that generated code stayed inside the planned scope; looking for architecture or design-system violations in AI-written changes.

How do I install Post-Feature Review in Claude Code?

Run `npx skills add jsmastery-pro/jsm-agent-skill --skill review -a claude-code`. Or copy the skill folder (skills/review in jsmastery-pro/jsm-agent-skill) into .claude/skills/review in your project. Claude Code loads it when a task matches its description.

How do I install Post-Feature Review in Codex?

Run `npx skills add jsmastery-pro/jsm-agent-skill --skill review -a codex`. Or copy the skill folder (skills/review in jsmastery-pro/jsm-agent-skill) into .agents/skills/review in your project. Codex loads it when a task matches its description.

Can I use Post-Feature Review in Cursor, Gemini CLI or GitHub Copilot?

Cursor, Gemini CLI, GitHub Copilot and OpenCode also load SKILL.md folders. With the skills CLI, run `npx skills add jsmastery-pro/jsm-agent-skill --skill review -a cursor` (or -a gemini-cli, github-copilot or opencode for the others). To copy it by hand, put the folder in .cursor/skills/review, .gemini/skills/review, .github/skills/review and .opencode/skills/review in your project.

What does Post-Feature Review need to run?

SKILL.md names no scripts, command-line tools or credentials: Post-Feature Review is instructions for the agent only. Our summary lists: A feature description or implementation plan to review against.

Does Post-Feature Review access the network?

SKILL.md contains no URLs. Any network use would come from the scripts or tools the agent runs. This is read from the text; nothing was executed.

Is Post-Feature Review safe to install?

Our automated static check of SKILL.md found no risky patterns, such as piping downloads into a shell, reading credential files or hidden Unicode. It is not a guarantee. Review the folder before installing.

What licence does Post-Feature Review use?

Post-Feature Review is published under the MIT licence (the repository's licence). It allows redistribution, so the full SKILL.md is shown on this page.

How many tokens does Post-Feature Review use?

About 1.3k tokens (SKILL.md is roughly 5.1k characters). Agents keep only the skill's name and description in context until a task matches; then they load SKILL.md in full.

What are the alternatives to Post-Feature Review?

Skills that share tags, products or a category with Post-Feature Review: WooCommerce Code Review (woocommerce/woocommerce, 11k stars), Skill Doli Code Review (Dolibarr/dolibarr, 7.7k stars), Dignified Python Standards (docling-project/docling, 69k stars) and Clean Code Guard (amElnagdy/guard-skills, 1.3k stars). The comparison table on this page puts their stars, adoption, token cost, safety result and licence side by side.

Who maintains Post-Feature Review?

jsmastery-pro (a GitHub organization) maintains it in jsmastery-pro/jsm-agent-skill, which has 218 GitHub stars. The repository holds 5 skills in this directory. The repository was last updated on July 9, 2026.

Source: jsmastery-pro/jsm-agent-skill on GitHub. Facts on this page come from the repository at the commit we read; the author's words are quoted as theirs.