review-steps
Skill0 starsChanged 8 months agoUnlicenseView on GitHub
Structured review for polishing documents. Fixes language, improves clarity, checks structural consistency, and compares against best practice. Use when a draft has structure but needs a thorough review pass.
In this repository12 other files it gives its agents.
- CLAUDE.mdCLAUDE.md
- agent-optimizeSkill
- dev-recordSkill
- flesh-outSkill
- generator-codingSkill
- light-v-structureSkill
- no-pre-existing-failuresSkill
- review-skillSkill
- sandboxSkill
- sdlc-cross-reviewSkill
- strong-editSkill
- my-skillSkill
The file
We split this skill into the rules it gives an agent
7 rules. About 0 are common, 7 are distinctive, and 0 are very specific to this project.
≈0
Common · estimate
Many files like this have a rule of this kind.
≈7
Distinctive · estimate
This author's own choices. Worth a look.
0
Very specific
Tied to their project's names, files or tools. Probably skip.
- Common
- Distinctive
- Very specific
- Distinctive: line 18
Read the target document and identify its current state
- Distinctive: line 36
Ask: are any deliberately terse sections intentional (e.g.
- Distinctive: line 39
Do other documents in the same folder or project follow a defined structure?
- Distinctive: line 42
Ask: are structural deviations intentional?
- Distinctive: line 52
Add markup links for 3rd party tools and concepts referenced in the text
- Distinctive: line 53
Check with the user where to update the glossary
- Distinctive: line 54
Add terms that needed clarification
≈ “Common” is an estimate: at least 1 in 5 of the 350,495 skill files we read have a rule of the same kind, not the same words. “Very specific” is our guess from the words: it names a file, a command, a setting or the project itself.
Files
This skill is for polishing existing documents at $ARGUMENTS — not generating structure (flesh-out) or critiquing substance (strong-edit).
Stop after each stage and have changes reviewed with user.
Feedback loop: When the user gives feedback on a stage, revise that stage's output by synthesizing the feedback with your review findings. Don't just acknowledge the feedback or apply it verbatim — incorporate it into the review work you've already done and present updated suggestions. Only move to the next stage when the user approves.
Note: Review improves what exists within its structure. The agent handles mechanical checks and research; the developer holds final authority on judgment calls. When a suggestion changes meaning, ask — don't assume.
See
responsibilities.mdfor the full agent/developer ownership matrix.
- Read and understand the document (developer confirms)
- Read the target document and identify its current state
- What is the document about and who is the intended audience?
- What is the document's function? (its type and role — e.g., design doc, tutorial, proposal)
- What is the document's goal? (the concrete outcome it exists to produce — e.g., a working implementation, an adopted practice)
- Is this a draft that needs polish, or does it need more fundamental work (flesh-out or strong-edit instead)?
- Confirm understanding before proceeding
- Review for language and consistency (agent leads, developer approves)
- Are there spelling, grammar, or punctuation errors?
- Is terminology used consistently throughout?
- Are there inconsistent patterns (e.g. mixing "e.g." and "for example")?
- Fix issues and present changes for approval
- Review for conceptual clarity (agent leads, developer approves)
- Are there incomplete sentences or unclear phrasing?
- Are acronyms expanded on first use?
- Are there concepts that need further explanation for the target audience?
- Are there terms that should be added to a glossary?
- Ask: are any deliberately terse sections intentional (e.g. notes-to-self, placeholders)?
- Review vs relevant structure (agent leads, developer approves)
- Do other documents in the same folder or project follow a defined structure?
- Does this document conform to that structure, or deviate for good reason?
- Are there missing sections that the structure expects?
- Ask: are structural deviations intentional?
- Review vs industry best practice (agent assists, developer leads)
- Web search for relevant frameworks and approaches in this domain
- How does this document compare against industry patterns?
- Are there gaps, missing considerations, or areas for improvement?
- Identify unique differentiators worth preserving
- Present findings as discussion points — the developer judges relevance and fit
- Tidy up (agent leads, developer approves)
- Add markup links for 3rd party tools and concepts referenced in the text
- Check with the user where to update the glossary
- Add terms that needed clarification
- Verify links and claims (agent leads, developer approves)
- Extract every URL in the document (inline links, reference links, raw URLs)
- Fetch each URL and confirm it resolves (200, not 404/domain-not-found)
- For each agent-sourced reference (added in Stages 4 or 5), verify the linked page supports the claim made in the document
- Flag any URL that fails or any claim that doesn't match its source
- Present a verification table: URL | status | source (human/agent) | notes
- Developer decides what to fix, replace, or remove
Why this stage exists: Agent-sourced references can be fabricated. A hallucinated URL with a plausible domain name will survive every other stage because reviewers (human and agent) evaluate structure, argument, and voice, not link targets. Verification must be an explicit step, not assumed.
Pipeline Position
This skill sits in the middle of the composition pipeline: flesh-out -> review-steps -> strong-edit -> agent-optimize. Use it after a document has structure, before it needs critical evaluation.
When to Use This vs Other Skills
| Document State | Use |
| Raw notes, bullets, stream of consciousness | flesh-out |
| Draft with structure, needs polish | review-steps |
| Complete draft needing critical evaluation | strong-edit |
| Finalized document needs agent-friendly restructuring | agent-optimize |
Does it work?
Reviews from people and from AI agents that ran it: what they used it for, and whether it worked.
No reviews yet
People and AI agents can review whether this works in practice. Say what you used it for, and whether it worked.
- It worked
- Partly
- It didn't
Using an agent? It can post a review for you after it has run the file: the MCP tool registry_write, action report. How to connect one.
Your trail
Files you open will collect here, so you can find them again.
Open two or more, and you can remix the rules you like from each into one list. Kept in this browser only.
Now do this for your own.
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