skill-improve▌
Donchitos/Claude-Code-Game-Studios · updated Apr 16, 2026
MDX-style export adds YAML metadata + attribution linking explainx.ai and this canonical listing URL.
### Skill Improve
- ›description: "Improve a skill using a test-fix-retest loop. Runs static checks, proposes targeted fixes, rewrites the skill, re-tests, and keeps or reverts based on score change."
- ›argument-hint: "[skill-name]"
- ›allowed-tools: Read, Glob, Grep, Write, Bash
| name | skill-improve |
| description | "Improve a skill using a test-fix-retest loop. Runs static checks, proposes targeted fixes, rewrites the skill, re-tests, and keeps or reverts based on score change." |
| argument-hint | "[skill-name]" |
| user-invocable | true |
| allowed-tools | Read, Glob, Grep, Write, Bash |
Skill Improve
Runs an improvement loop on a single skill: test → fix → retest → keep or revert.
Phase 1: Parse Argument
Read the skill name from the first argument. If missing, output usage and stop:
Usage: /skill-improve [skill-name]
Example: /skill-improve tech-debt
Verify .claude/skills/[name]/SKILL.md exists. If not, stop with:
"Skill '[name]' not found."
Phase 2: Baseline Test
Run /skill-test static [name] and record the baseline score:
- Count of FAILs
- Count of WARNs
- Which specific checks failed (Check 1–7)
Display to the user:
Static baseline: [N] failures, [M] warnings
Failing: Check 4 (no ask-before-write), Check 5 (no handoff)
If baseline is 0 FAILs and 0 WARNs, note it and proceed to Phase 2b.
Phase 2b: Category Baseline
Look up the skill's category: field in CCGS Skill Testing Framework/catalog.yaml.
If no category: field is found, display:
"Category: not yet assigned — skipping category checks."
and skip to Phase 3.
If category is found, run /skill-test category [name] and record the category baseline:
- Count of FAILs
- Count of WARNs
- Which specific category rubric metrics failed
Display to the user:
Category baseline: [N] failures, [M] warnings ([category] rubric)
If BOTH static and category baselines are 0 FAILs and 0 WARNs, stop: "This skill already passes all static and category checks. No improvements needed."
Phase 3: Diagnose
Read the full skill file at .claude/skills/[name]/SKILL.md.
For each failing or warning static check, identify the exact gap:
- Check 1 fail → which frontmatter field is missing
- Check 2 fail → how many phases found vs. minimum required
- Check 3 fail → no verdict keywords anywhere in the skill body
- Check 4 fail → Write or Edit in allowed-tools but no ask-before-write language
- Check 5 warn → no follow-up or next-step section at the end
- Check 6 warn →
context: forkset but fewer than 5 phases found - Check 7 warn → argument-hint is empty or doesn't match documented modes
For each failing or warning category check (if category was assigned in Phase 2b), identify the exact gap in the skill's text. For example:
- If G2 fails (gate mode, full directors not spawned): skill body never references all 4 PHASE-GATE director prompts
- If A2 fails (authoring, no per-section May-I-write): skill asks once at the end, not before each section write
- If T3 fails (team, BLOCKED not surfaced): skill doesn't halt dependent work on blocked agent
Show the full combined diagnosis to the user before proposing any changes.
Phase 4: Propose Fix
Write a targeted fix for each failure and warning. Show the proposed changes as clearly marked before/after blocks. Only change what is failing — do not rewrite sections that are passing.
Ask: "May I write this improved version to .claude/skills/[name]/SKILL.md?"
If the user says no, stop here.
Phase 5: Write and Retest
Record the current content of the skill file (for revert if needed).
Write the improved skill to .claude/skills/[name]/SKILL.md.
Re-run /skill-test static [name] and record the new static score.
If a category was assigned, also re-run /skill-test category [name] and record the new category score.
Display the comparison:
Static: Before [N] failures, [M] warnings → After [N'] failures, [M'] warnings
Category: Before [N] failures, [M] warnings → After [N'] failures, [M'] warnings (if applicable)
Combined change: improved / no change / worse
Phase 6: Verdict
Count the combined failure total: static FAILs + category FAILs + static WARNs + category WARNs.
If combined score improved (combined failure count is lower than baseline): Report: "Score improved. Changes kept." Show a summary of what was fixed in each dimension.
If combined score is the same or worse:
Report: "Combined score did not improve."
Show what changed and why it may not have helped.
Ask: "May I revert .claude/skills/[name]/SKILL.md using git checkout?"
If yes: run git checkout -- .claude/skills/[name]/SKILL.md
Phase 7: Next Steps
- Run
/skill-test static allto find the next skill with failures. - Run
/skill-improve [next-name]to continue the loop on another skill. - Run
/skill-test auditto see overall coverage progress.
How to use skill-improve on Cursor
AI-first code editor with Composer
Prerequisites
Before installing skills in Cursor, ensure your development environment meets these requirements:
- ›Cursor installed and configured on your development machine
- ›Node.js version 16.0+ with npm package manager (verify with
node --version) - ›Active project directory or workspace where you want to add skill-improve
Execute installation command
Execute the skills CLI command in your project's root directory to begin installation:
The skills CLI fetches skill-improve from GitHub repository Donchitos/Claude-Code-Game-Studios and configures it for Cursor.
Select Cursor when prompted
The CLI will show a list of available agents. Use arrow keys to navigate and space to select Cursor:
Verify installation
Confirm successful installation by checking the skill directory location:
Reload or restart Cursor to activate skill-improve. Access the skill through slash commands (e.g., /skill-improve) or your agent's skill management interface.
Security & Verification Notice
We perform automated surface-level scans (Gen AI Scanner, Socket, Snyk) during installation. These checks detect common vulnerabilities but do not guarantee complete security. Always review skill source code and verify the publisher's reputation before production use.
Skills execute code in your development environment. Always verify the publisher's identity, review recent commits, and test in isolated environments before production deployment.
List & Monetize Your Skill
Submit your Claude Code skill and start earning
Use Cases▌
Task Automation & Efficiency
Automate repetitive workflows and reduce manual effort
Example
Generate reports, summarize documents, draft communications
Save 3-5 hours per week on routine tasks
Knowledge Enhancement
Learn new skills, understand complex topics, get expert guidance
Example
Explain concepts, provide examples, suggest learning resources
Accelerate learning and skill development by 2x
Quality Improvement
Enhance output quality through reviews, suggestions, and refinements
Example
Review drafts, suggest improvements, catch errors
Improve work quality by 30-40% with less effort
Implementation Guide▌
Prerequisites
- ›Claude Desktop or compatible AI client with skill support
- ›Clear understanding of task or problem to solve
- ›Willingness to iterate and refine outputs
Time Estimate
15-45 minutes depending on use case complexity
Installation Steps
- 1.Install skill using provided installation command
- 2.Test with simple use case relevant to your work
- 3.Evaluate output quality and relevance
- 4.Iterate on prompts to improve results
- 5.Integrate into regular workflow if valuable
Common Pitfalls
- ⚠Expecting perfect results without iteration
- ⚠Not providing enough context in prompts
- ⚠Using skill for tasks outside its intended scope
- ⚠Accepting outputs without review and validation
Best Practices▌
✓ Do
- +Start with clear, specific prompts
- +Provide relevant context and constraints
- +Review and refine all outputs before using
- +Iterate to improve output quality
- +Document successful prompt patterns
✗ Don't
- −Don't use without understanding skill limitations
- −Don't skip validation of outputs
- −Don't share sensitive information in prompts
- −Don't expect skill to replace human judgment
💡 Pro Tips
- ★Be specific about desired format and style
- ★Ask for multiple options to choose from
- ★Request explanations to understand reasoning
- ★Combine AI efficiency with human expertise
When to Use This▌
✓ Use When
Use when skill capabilities match your task, clear ROI on time saved, and you can validate outputs. Best for repetitive tasks, learning, and quality improvement.
✗ Avoid When
Avoid when task requires deep expertise you can't validate, involves sensitive decisions, or when learning process is more valuable than speed of completion.
Learning Path▌
- 1Familiarize yourself with skill capabilities and limitations
- 2Start with low-risk, non-critical tasks
- 3Progress to more complex and valuable use cases
- 4Build expertise through regular use and experimentation
Discussion
Product Hunt–style comments (not star reviews)- No comments yet — start the thread.
Ratings
4.8★★★★★68 reviews- ★★★★★Chinedu Mehta· Dec 24, 2024
Registry listing for skill-improve matched our evaluation — installs cleanly and behaves as described in the markdown.
- ★★★★★Naina Kim· Dec 20, 2024
skill-improve reduced setup friction for our internal harness; good balance of opinion and flexibility.
- ★★★★★Alexander Patel· Dec 16, 2024
Solid pick for teams standardizing on skills: skill-improve is focused, and the summary matches what you get after install.
- ★★★★★Ishan Robinson· Dec 12, 2024
Solid pick for teams standardizing on skills: skill-improve is focused, and the summary matches what you get after install.
- ★★★★★Chinedu Verma· Dec 8, 2024
We added skill-improve from the explainx registry; install was straightforward and the SKILL.md answered most questions upfront.
- ★★★★★Naina Choi· Dec 8, 2024
skill-improve reduced setup friction for our internal harness; good balance of opinion and flexibility.
- ★★★★★Chinedu Robinson· Nov 27, 2024
skill-improve fits our agent workflows well — practical, well scoped, and easy to wire into existing repos.
- ★★★★★Neel Yang· Nov 27, 2024
skill-improve has been reliable in day-to-day use. Documentation quality is above average for community skills.
- ★★★★★Alexander Dixit· Nov 15, 2024
Keeps context tight: skill-improve is the kind of skill you can hand to a new teammate without a long onboarding doc.
- ★★★★★Li Chawla· Nov 11, 2024
skill-improve has been reliable in day-to-day use. Documentation quality is above average for community skills.
showing 1-10 of 68