YOU MUST EXECUTE THIS WORKFLOW. Do not just describe it.
Works with
AI-first code editor with Composer
Before installing skills in Cursor, ensure your development environment meets these requirements:
node --versioncomplexityExecute the skills CLI command in your project's root directory to begin installation:
Fetches complexity from boshu2/agentops and configures it for Cursor.
The CLI shows a list of agents. Use arrow keys and space to select Cursor:
Confirm successful installation by checking the skill directory location:
Restart Cursor to activate complexity. Access via /complexity in your agent's command palette.
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 environment. Always review source, verify the publisher, and test in isolation before production.
Submit your Claude Code skill and start earning
Create detailed user stories, acceptance criteria, and feature specs
Example
Generate user stories for 'password reset feature' with acceptance criteria, edge cases, and test scenarios
Reduce spec writing time by 50%, ensure comprehensive coverage
Research competitors, compare features, identify gaps
Example
Analyze 5 competitor products, create feature comparison matrix, suggest differentiation opportunities
Complete competitive research in 2 hours instead of 2 days
Evaluate features using frameworks (RICE, ICE, Kano) and create prioritized backlogs
Example
Score 20 feature ideas using RICE framework, generate prioritized roadmap with rationale
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YOU MUST EXECUTE THIS WORKFLOW. Do not just describe it.
Analyze code complexity to identify refactoring targets.
Given /complexity [path]:
If path provided: Use it directly.
If no path: Use current directory or recent changes:
git diff --name-only HEAD~5 2>/dev/null | grep -E '\.(py|go)$' | head -10
# Check for Python files
ls *.py **/*.py 2>/dev/null | head -1 && echo "Python detected"
# Check for Go files
ls *.go **/*.go 2>/dev/null | head -1 && echo "Go detected"
For Python (using radon):
# Check if radon is installed
which radon || pip install radon
# Run cyclomatic complexity
radon cc <path> -a -s
# Run maintainability index
radon mi <path> -s
For Go (using gocyclo):
# Check if gocyclo is installed
which gocyclo || go install github.com/fzipp/gocyclo/cmd/gocyclo@latest
# Run complexity analysis
gocyclo -over 10 <path>
Cyclomatic Complexity Grades:
| Grade | CC Score | Meaning |
|---|---|---|
| A | 1-5 | Low risk, simple |
| B | 6-10 | Moderate, manageable |
| C | 11-20 | High risk, complex |
| D | 21-30 | Very high risk |
| F | 31+ | Untestable, refactor now |
List functions/methods that need attention:
Write to: .agents/complexity/YYYY-MM-DD-<target>.md
# Complexity Report: <Target>
**Date:** YYYY-MM-DD
**Language:** <Python/Go>
**Files Analyzed:** <count>
## Summary
- Average CC: <score>
- Highest CC: <score> in <function>
- Functions over threshold: <count>
## Refactor Targets
### Critical (CC > 20)
| Function | File | CC | Recommendation |
|----------|------|-----|----------------|
| <name> | <file:line> | <score> | <how to simplify> |
### High (CC 11-20)
| Function | File | CC | Recommendation |
|----------|------|-----|----------------|
| <name> | <file:line> | <score> | <how to simplify> |
## Refactoring Recommendations
1. **<Function>**: <specific suggestion>
- Extract: <what to extract>
- Simplify: <how to simplify>
## Next Steps
- [ ] Address critical complexity first
- [ ] Create issues for high complexity
- [ ] Consider refactoring sprint
Tell the user:
/refactor <function> to address critical complexity targetsSimplifying High Complexity:
User says: /complexity src/
What happens:
src/ directoryradon cc src/ -a -s for cyclomatic complexityradon mi src/ -s for maintainability index.agents/complexity/2026-02-13-src.mdprocess_request() functionResult: Complexity report identifies process_request() (CC: 28) as critical refactor target with specific extraction recommendations.
User says: /complexity
What happens:
git diff --name-only HEAD~5gocyclo -over 10 ./... on projectHandleWebhook() function with complexity 34Result: Critical function identified for immediate refactoring with actionable extraction plan.
| Problem | Cause | Solution |
|---|---|---|
| Tool not installed (radon/gocyclo) | Missing dependency | Agent auto-installs: pip install radon for Python or go install github.com/fzipp/gocyclo/cmd/gocyclo@latest for Go. Verify install path in $PATH. |
| No complexity issues found | Threshold too high or genuinely simple code | Lower threshold: try gocyclo -over 5 or check if path includes actual implementation files vs tests. |
| Report shows functions without recommendations | Generic analysis without codebase context | Read the high-CC functions to understand structure, then provide specific refactoring suggestions based on actual code patterns. |
| Mixed language project | Multiple languages in target path | Run analysis separately per language: /complexity src/python/ then /complexity src/go/, combine reports manually. |
Make data-driven prioritization decisions faster
Draft PRDs, status updates, and stakeholder presentations
Example
Create executive summary of Q3 roadmap, monthly progress report, feature launch announcement
Save 3-5 hours/week on communication overhead
Prerequisites
Time Estimate
30-60 minutes to see productivity improvements
Steps
Common Pitfalls
✓ Do
✗ Don't
💡 Pro Tips
✓ Use when
Use for user story writing, competitive research, roadmap prioritization, stakeholder communication, and PRD drafting. Best for reducing repetitive documentation and research work.
✗ Avoid when
Avoid for strategic product vision (requires deep customer empathy), pricing decisions (needs market and financial expertise), or when face-to-face customer discovery is more valuable than speed.
mattpocock/skills
parcadei/continuous-claude-v3
cursor/plugins
ailabs-393/ai-labs-claude-skills
pproenca/dot-skills
mattpocock/skills
Useful defaults in complexity — fewer surprises than typical one-off scripts, and it plays nicely with `npx skills` flows.
Registry listing for complexity matched our evaluation — installs cleanly and behaves as described in the markdown.
I recommend complexity for anyone iterating fast on agent tooling; clear intent and a small, reviewable surface area.
Solid pick for teams standardizing on skills: complexity is focused, and the summary matches what you get after install.
complexity has been reliable in day-to-day use. Documentation quality is above average for community skills.
We added complexity from the explainx registry; install was straightforward and the SKILL.md answered most questions upfront.
complexity fits our agent workflows well — practical, well scoped, and easy to wire into existing repos.
complexity is among the better-maintained entries we tried; worth keeping pinned for repeat workflows.
complexity fits our agent workflows well — practical, well scoped, and easy to wire into existing repos.
We added complexity from the explainx registry; install was straightforward and the SKILL.md answered most questions upfront.
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