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Before installing skills in Cursor, ensure your development environment meets these requirements:
node --versionworkflow-patternsExecute the skills CLI command in your project's root directory to begin installation:
Fetches workflow-patterns from wshobson/agents 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 workflow-patterns. Access via /workflow-patterns 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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Guide for implementing tasks using Conductor's TDD workflow, managing phase checkpoints, handling git commits, and executing the verification protocol that ensures quality throughout implementation.
Follow these 11 steps for each task:
Read plan.md and identify the next pending [ ] task. Select tasks in order within the current phase. Do not skip ahead to later phases.
Update plan.md to mark the task as [~]:
- [~] **Task 2.1**: Implement user validation
Commit this status change separately from implementation.
Write tests that define the expected behavior before writing implementation:
Example:
def test_validate_user_email_valid():
user = User(email="[email protected]")
assert user.validate_email() is True
def test_validate_user_email_invalid():
user = User(email="invalid")
assert user.validate_email() is False
Write the minimum code necessary to make tests pass:
With green tests, improve the code:
Check test coverage meets the 80% target:
pytest --cov=module --cov-report=term-missing
If coverage is below 80%:
If implementation deviated from plan or introduced new dependencies:
Create a focused commit for the task:
git add -A
git commit -m "feat(user): implement email validation
- Add validate_email method to User class
- Handle empty and malformed emails
- Add comprehensive test coverage
Task: 2.1
Track: user-auth_20250115"
Commit message format:
Add rich task summary as git note:
git notes add -m "Task 2.1: Implement user validation
Summary:
- Added email validation using regex pattern
- Handles edge cases: empty, no @, no domain
- Coverage: 94% on validation module
Files changed:
- src/models/user.py (modified)
- tests/test_user.py (modified)
Decisions:
- Used simple regex over email-validator library
- Reason: No external dependency for basic validation"
Update plan.md to mark task complete with commit SHA:
- [x] **Task 2.1**: Implement user validation `abc1234`
Commit the plan status update:
git add conductor/tracks/*/plan.md
git commit -m "docs: update plan - task 2.1 complete
Track: user-auth_20250115"
When all tasks in a phase are complete, execute the verification protocol:
List all files modified since the last checkpoint:
git diff --name-only <last-checkpoint-sha>..HEAD
For each modified file:
Execute complete test suite:
pytest -v --tb=short
All tests must pass before proceeding.
Create checklist of manual verifications:
## Phase 1 Verification Checklist
- [ ] User can register with valid email
- [ ] Invalid email shows appropriate error
- [ ] Database stores user correctly
- [ ] API returns expected response codes
Present verification checklist to user:
Phase 1 complete. Please verify:
1. [ ] Test suite passes (automated)
2. [ ] Coverage meets target (automated)
3. [ ] Manual verification items (requires human)
Respond with 'approved' to continue, or note issues.
Do NOT proceed without explicit approval.
After approval, create checkpoint commit:
git add -A
git commit -m "checkpoint: phase 1 complete - user-auth_20250115
Verified:
- All tests passing
- Coverage: 87%
- Manual verification approved
Phase 1 tasks:
- [x] Task 1.1: Setup database schema
- [x] Task 1.2: Implement user model
- [x] Task 1.3: Add validation logic"
Update plan.md checkpoints table:
## Checkpoints
| Phase | Checkpoint SHA | Date | Status |
| ------- | -------------- | ---------- | -------- |
| Phase 1 | def5678 | 2025-01-15 | verified |
| Phase 2 | | | pending |
Before marking any task complete, verify these gates:
If applicable:
<type>(<scope>): <subject>
<body>
<footer>
Types:
feat: New featurefix: Bug fixrefactor: Code change without feature/fixtest: Adding testsdocs: Documentationchore: MaintenanceAttach detailed notes to commits:
git notes add -m "<detailed summary>"
View notes:
git log --show-notes
Benefits:
Always record the commit SHA when completing tasks:
- [x] **Task 1.1**: Setup schema `abc1234`
- [x] **Task 1.2**: Add model `def5678`
This enables:
Checkpoints create restore points for semantic reversion:
Create checkpoint after:
Include in checkpoint commit:
For reverting:
# Revert to end of Phase 1
git revert --no-commit <phase-2-commits>...
git commit -m "revert: rollback to phase 1 checkpoint"
For review:
# See what changed in Phase 2
git diff <phase-1-sha>..<phase-2-sha>
During implementation, deviations from the plan may occur. Handle them systematically:
Scope Addition Discovered requirement not in original spec.
Scope Reduction Feature deemed unnecessary during implementation.
[-] (skipped) with reasonTechnical Deviation Different implementation approach than planned.
Requirement Change Understanding of requirement changes during work.
When completing a task with deviation:
- [x] **Task 2.1**: Implement validation `abc1234`
- DEVIATION: Used library instead of custom code
- Reason: Better edge case handling
- Impact: Added email-validator to dependencies
If tests fail after reaching GREEN:
If user rejects a checkpoint:
If task cannot proceed:
[!] with blocker descriptionRED: Write test for model creation and validation
GREEN: Implement model class with fields
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
ailabs-393/ai-labs-claude-skills
pproenca/dot-skills
workflow-patterns fits our agent workflows well — practical, well scoped, and easy to wire into existing repos.
I recommend workflow-patterns for anyone iterating fast on agent tooling; clear intent and a small, reviewable surface area.
Keeps context tight: workflow-patterns is the kind of skill you can hand to a new teammate without a long onboarding doc.
workflow-patterns fits our agent workflows well — practical, well scoped, and easy to wire into existing repos.
Registry listing for workflow-patterns matched our evaluation — installs cleanly and behaves as described in the markdown.
Useful defaults in workflow-patterns — fewer surprises than typical one-off scripts, and it plays nicely with `npx skills` flows.
workflow-patterns reduced setup friction for our internal harness; good balance of opinion and flexibility.
workflow-patterns has been reliable in day-to-day use. Documentation quality is above average for community skills.
Solid pick for teams standardizing on skills: workflow-patterns is focused, and the summary matches what you get after install.
I recommend workflow-patterns for anyone iterating fast on agent tooling; clear intent and a small, reviewable surface area.
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