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self-review

Catch drift between design and delivery before it ships.

Agent Skills compatible — works with Claude Code, Cursor, Codex, OpenClaw, and any supporting platform.

License: MIT

Usage · Install · Example Output

Who Is This For

Anyone producing work with intent.

  • Developers: Are you building what you designed? Does the code match the spec?
  • Content creators: Does the final cut match the script? Did you capture your editing lessons?
  • Designers: Does the mockup address the user need? Is there a simpler layout?
  • Researchers: Do the conclusions follow from the method? Is the progress tracking accurate?
  • Teams: Are design, delivery, and documentation in sync across contributors?

You don't need formal documents to use Self-Review. If your "design" is a mental model and your "progress" is a git log — that's enough. The 4 pillars are questions to ask, not documents to write.

Not for: line-by-line code review, automated CI gates, or linting. Self-Review checks alignment between intent and delivery — it does not evaluate code style, syntax, or formatting.

Why This Exists

Anyone who ships work in stages faces the same problem: things drift.

The design says one thing, the deliverable does another. Progress tracking says "done" but the artifact is half-finished. You learned a better method last week but the old pattern is still everywhere.

Self-Review forces a structured pause. It scans your project across 4 pillars and checks 6 dimensions of alignment between them. It works for anything with deliverables — code, content, research, design.

It's especially powerful as an AI agent skill — agents are goal-seeking and don't naturally pause to reflect. But the framework works for any creator reviewing their own work.

Report-only — it flags issues, never auto-fixes. You stay in control.

What Makes It Different

Scope-aware auditing. Self-Review reads your Progress to lock the current phase before checking anything. Items are classified as in-scope, deferred, or out-of-scope — only in-scope work gets audited. "Phase 2 hasn't started yet" is never a finding.

Artifact verification, not just existence checks. The artifact check runs your builds, executes CLI commands, and verifies output — not just that files exist, but that they actually work. "Tests pass" means it ran the tests.

Design introspection. Evaluates your design for clarity, value, scope, and simplicity before checking alignment. Asks whether the goal is well-defined, the scope is right-sized, and whether a simpler approach exists.

Currency and assumptions check. Searches the web with current-year queries to verify your design assumptions still hold. Flags when a key assumption has been invalidated or when a community solution has dissolved the problem you're solving custom.

Principled judgment. Every finding is evaluated against 6 explicit principles (3 theoretical + 3 engineering), embedded as check questions directly in each dimension. Audits are consistent and reviewable.

Cross-platform quality standards. Discovers your project's instruction files across platforms — CLAUDE.md, AGENTS.md, .cursorrules, .cursor/rules/, CONTRIBUTING.md — and uses them as additional quality gates. Also layers rules from installed domain skills.

Standard recommendations. When recurring issues have no corresponding standard, Self-Review drafts the standard text, specifies the exact file path where it should be persisted (platform-aware), and explains why it's worth adding.

Implicit anchor inference. No dedicated design docs? No progress.md? Infers from commit messages, PR descriptions, TODO comments, git log timelines, and code patterns before skipping any pillar.

Skill deposit detection. Evaluates whether lessons learned during execution are worth capturing as reusable skills, with specific deposit criteria and clear recommendations.

Works for everything. Code, content, research, video production, documentation — anything with a design intent and deliverables.

Usage

Say /self-review, self-review, audit, or 审视一下.

Self-Review discovers anchors in 4 pillars, locks scope, runs all 6 dimensions with artifact verification (minimum level depends on artifact type), and outputs a structured report with file paths and line numbers.

Install

npx skills add motiful/self-review

Or manually:

git clone https://github.com/motiful/self-review ~/skills/self-review

# Claude Code
ln -sfn ~/skills/self-review ~/.claude/skills/self-review

# Other platforms (Cursor, Codex, Windsurf, etc.)
ln -sfn ~/skills/self-review ~/.agents/skills/self-review

Example Output

Self-Review produces a structured report covering design introspection, scope lock, and all 6 dimensional checks with specific findings and evidence.

Full examples — includes a real self-audit and a hypothetical video project audit

The Framework

Self-Review is built on 6 audit principles (3 from Feynman's criteria for good theories + 3 engineering constraints), applied across 4 pillars (Design, Artifact, Skill, Progress) in all 6 pillar-pair dimensions.

Principles, pillars, dimensions, and verification depth

What's Inside

SKILL.md              — Audit process, execution procedure, and rules
references/
└── dimensions.md     — Detailed checks for all 6 dimensions
docs/
├── examples.md       — Sample audit outputs
└── framework.md      — Principles, pillars, and dimensions explained

Contributing

Issues, suggestions, and PRs welcome at github.com/motiful/self-review.

License

MIT


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About

Structured alignment audit for AI agents and creators. Checks drift across 4 pillars and 6 dimensions — from design currency to artifact verification. Report-only, never auto-fixes.

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