tdd-migrate▌
parcadei/continuous-claude-v3 · updated Apr 8, 2026
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Orchestrate TDD migrations with agents doing all work. Main context stays clean.
TDD Migrate
Orchestrate TDD migrations with agents doing all work. Main context stays clean.
When to Use
- "Port X from Python to TypeScript"
- "Create N adapters following existing pattern"
- "Migrate module to new architecture"
- "TDD implementation of multiple similar items"
Parameters
/tdd-migrate <source_path> <target_path> --pattern <reference> --items "item1,item2,item3"
source_path: Path to analyze (existing code)target_path: Where to create new codepattern: Reference file/pattern to followitems: Comma-separated list of things to create
Workflow
Phase 0: YAML TODO List
│
▼
Phase 1: TLDR Analysis ─────────────────┐
│ │
▼ │ Parallel scouts
Phase 2: Write Failing Tests ───────────┤ per item
│ │
▼ │
Phase 3: Implement (minimal) ───────────┤
│ │
▼ │
Phase 4: Build + Pass Tests ────────────┘
│
▼
Phase 5: QLTY Check ────────────────────┐
│ │ Parallel
Phase 6: Review Agent Validates ────────┘
│
▼
Phase 7: TLDR Diff (new vs reference)
│
▼
Phase 8: Fix Issues (if any)
│
▼
Complete
Key Principles
-
Main context = orchestration only
- Never read files directly (use scout)
- Never implement directly (use kraken/spark)
- Never run tests directly (use validator)
- Only pipe context and coordinate
-
Agents do ALL work
Task Agent Explore/analyze scout Write tests + implement kraken Quick fixes spark Run tests/validate validator Code review critic -
Parallel where independent
- All items can be implemented in parallel if independent
- Review + QLTY run in parallel
- TLDR analysis runs in parallel with planning
-
Review after each major step
- After implementation: critic reviews
- After fixes: validator re-validates
Instructions
Step 0: Create YAML TODO
Write a YAML plan file to thoughts/shared/plans/<name>-tdd.yaml:
---
title: <Migration Name>
date: <today>
type: implementation-plan
approach: TDD (test → build → pass → review)
items:
- name: item1
file: <target_path>/item1.ts
test: <target_path>/__tests__/item1.test.ts
deps: []
- name: item2
# ...
reference: <pattern_file>
workflow:
per_item:
1: Write failing test
2: Implement minimal
3: Build
4: Pass test
5: QLTY check
6: Review
final:
7: Integration test
8: TLDR diff
Step 1: Launch Scout Agents (parallel)
Task (scout): Analyze <source_path> with TLDR
Task (scout): Analyze <pattern> to understand structure
Task (scout): Read migration handoff if exists
Step 2: Launch Kraken Agents (parallel per item)
For each item, launch ONE kraken that does full TDD:
Task (kraken): Implement <item> using TDD workflow
1. Read pattern file
2. Write failing test
3. Implement
4. Run: bun test <test_file>
5. Run: qlty check <impl_file>
Step 3: Review + Validate (parallel)
Task (critic): Review all new files against pattern
Task (validator): Run full test suite
Task (validator): QLTY check all files
Step 4: Fix Issues
If critic/validator found issues:
Task (spark): Fix <specific issue>
Task (validator): Re-validate
Step 5: TLDR Diff
Task (validator): TLDR diff new files vs reference
- tldr structure <new_file> --lang <lang>
- tldr structure <reference> --lang <lang>
- Compare patterns
Step 6: Update Continuity
Update ledger with completed work.
Example: Rigg Adapters
/tdd-migrate /Users/cosimo/Documents/rigg/src/sdk/providers \
/Users/cosimo/Documents/rigg/src/sdk/providers \
--pattern lmstudio.ts \
--items "xai,cerebras,togetherai,deepinfra,perplexity"
Resulted in:
- 5 parallel kraken agents
- 39 tests passing
- All adapters working
- ~15 minutes total
Anti-Patterns (AVOID)
| Bad | Good |
|---|---|
| Read files in main context | Launch scout agent |
| Write code in main context | Launch kraken/spark agent |
| Run tests in main context | Launch validator agent |
| Skip review | Always launch critic |
| Sequential items | Parallel krakens |
| Fix in main context | Launch spark |
Agent Prompts
Scout (analysis)
Explore <path> to understand:
1. Structure/patterns
2. Interfaces/types
3. Dependencies
Return actionable summary for implementation.
Kraken (TDD)
Implement <item> using TDD:
1. Read <pattern> for structure
2. Write failing test to <test_path>
3. Implement minimal to <impl_path>
4. Run: <test_command>
5. Run: qlty check <impl_path>
Report: status, issues, files created.
Critic (review)
Review <files> against <pattern>:
1. Pattern compliance
2. Type safety
3. Missing registrations
4. Security issues
DO NOT edit. Report issues only.
Spark (fix)
Fix <specific issue>:
1. Read <file>
2. Make minimal edit
3. Verify fix
Validator (test)
Validate <files>:
1. Run <test_command>
2. Run qlty check
3. Report pass/fail/issues
Success Criteria
- All tests pass
- QLTY reports no issues
- Critic found no critical issues
- TLDR diff shows pattern compliance
- All items registered/exported properly
How to use tdd-migrate 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 tdd-migrate
Execute installation command
Execute the skills CLI command in your project's root directory to begin installation:
The skills CLI fetches tdd-migrate from GitHub repository parcadei/continuous-claude-v3 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 tdd-migrate. Access the skill through slash commands (e.g., /tdd-migrate) 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▌
User Story & Requirements Generation
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
Competitive Analysis
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
Roadmap Prioritization
Evaluate features using frameworks (RICE, ICE, Kano) and create prioritized backlogs
Example
Score 20 feature ideas using RICE framework, generate prioritized roadmap with rationale
Make data-driven prioritization decisions faster
Stakeholder Communication
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
Implementation Guide▌
Prerequisites
- ›Claude Desktop or compatible AI client
- ›Access to product documentation and roadmap tools (Jira, Notion, etc.)
- ›Understanding of product management frameworks (RICE, Jobs-to-be-Done, etc.)
- ›Stakeholder contact information and communication channels
Time Estimate
30-60 minutes to see productivity improvements
Installation Steps
- 1.Install product management skill
- 2.Start with user story generation for known feature
- 3.Progress to competitive analysis: research 2-3 competitors
- 4.Use for roadmap prioritization: apply RICE/ICE scoring
- 5.Draft stakeholder communications and refine based on feedback
- 6.Build template library for recurring PM tasks
- 7.Share effective prompts with product team
Common Pitfalls
- ⚠Not validating competitive research—verify facts before sharing
- ⚠Accepting user stories without involving engineering team
- ⚠Over-relying on frameworks without qualitative judgment
- ⚠Not customizing outputs to company culture and communication style
- ⚠Skipping stakeholder validation of generated requirements
Best Practices▌
✓ Do
- +Validate research and competitive analysis with real data
- +Collaborate with engineering when generating technical requirements
- +Customize frameworks and templates to your company context
- +Use skill for first drafts, refine with stakeholder input
- +Document successful prompt patterns for PM tasks
- +Combine AI efficiency with human judgment and intuition
✗ Don't
- −Don't publish competitive analysis without fact-checking
- −Don't finalize user stories without engineering review
- −Don't make prioritization decisions solely on AI scoring
- −Don't skip customer validation of generated requirements
- −Don't ignore company-specific context and culture
💡 Pro Tips
- ★Provide context: company goals, constraints, customer feedback
- ★Ask for alternatives: 'Show 3 ways to prioritize this roadmap'
- ★Request stakeholder-specific formatting: 'Executive summary vs. engineering spec'
- ★Use skill for 70% generation + 30% customization to company needs
When to Use This▌
✓ 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.
Learning Path▌
- 1Basic: user stories, feature specs, status updates
- 2Intermediate: competitive analysis, prioritization frameworks, PRDs
- 3Advanced: product strategy, go-to-market planning, OKR setting
- 4Expert: product vision, market positioning, business model innovation
Discussion
Product Hunt–style comments (not star reviews)- No comments yet — start the thread.
Ratings
4.7★★★★★44 reviews- ★★★★★Ama Garcia· Dec 28, 2024
tdd-migrate fits our agent workflows well — practical, well scoped, and easy to wire into existing repos.
- ★★★★★Valentina Dixit· Dec 16, 2024
Registry listing for tdd-migrate matched our evaluation — installs cleanly and behaves as described in the markdown.
- ★★★★★Zaid Dixit· Dec 4, 2024
Useful defaults in tdd-migrate — fewer surprises than typical one-off scripts, and it plays nicely with `npx skills` flows.
- ★★★★★William Diallo· Dec 4, 2024
I recommend tdd-migrate for anyone iterating fast on agent tooling; clear intent and a small, reviewable surface area.
- ★★★★★Ama Liu· Nov 23, 2024
We added tdd-migrate from the explainx registry; install was straightforward and the SKILL.md answered most questions upfront.
- ★★★★★Kwame Sanchez· Nov 23, 2024
Solid pick for teams standardizing on skills: tdd-migrate is focused, and the summary matches what you get after install.
- ★★★★★Lucas Tandon· Nov 11, 2024
tdd-migrate has been reliable in day-to-day use. Documentation quality is above average for community skills.
- ★★★★★Aisha Ndlovu· Nov 7, 2024
tdd-migrate reduced setup friction for our internal harness; good balance of opinion and flexibility.
- ★★★★★Michael Ramirez· Oct 26, 2024
We added tdd-migrate from the explainx registry; install was straightforward and the SKILL.md answered most questions upfront.
- ★★★★★Li Shah· Oct 14, 2024
tdd-migrate reduced setup friction for our internal harness; good balance of opinion and flexibility.
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