TDD Migrate

SkillAI & models

Lets your agent run test-driven development workflows for database migrations without filling up its context.

Available today. Use it from your connected AI after setup.

Connect ahel once, and every AI you use reads what you have installed.

Then ask your AI: use the TDD Migrate skill

About this capability

TDD workflow for migrations - orchestrate agents, zero main context growth

What this skill tells your AI

The instructions your AI receives, as published by parcadei/continuous-claude-v3 in .claude/skills/tdd-migrate/SKILL.md and read by ahel’s review.

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 code
  • pattern: Reference file/pattern to follow
  • items: 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

  1. 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
  2. Agents do ALL work

    TaskAgent
    Explore/analyzescout
    Write tests + implementkraken
    Quick fixesspark
    Run tests/validatevalidator
    Code reviewcritic
  3. Parallel where independent

    • All items can be implemented in parallel if independent
    • Review + QLTY run in parallel
    • TLDR analysis runs in parallel with planning
  4. 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)

BadGood
Read files in main contextLaunch scout agent
Write code in main contextLaunch kraken/spark agent
Run tests in main contextLaunch validator agent
Skip reviewAlways launch critic
Sequential itemsParallel krakens
Fix in main contextLaunch 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

Signals

GitHub stars
4k
Forks
300
Last commit
Jan 2026
Advanced
Catalog kind
skill
Gateway key
tdd-migrate
Source
github.com/parcadei/continuous-claude-v3