跳到正文
cccskills
免费在 GitHub 公开

tdd-migration-pipeline

Coordinate code migrations and rewrites through delegated agents. Define expected behavior, write tests before implementation, review failure risks, and build in stages in a separate directory, then validate the result against the original system.

中文简介正在准备中。当前显示英语简介。

原文查看原文说明

Orchestrator-only workflow for migrating/rewriting codebases with full TDD and agent delegation

查看安装方法

适用场景

  • Migrate code to another language or framework
  • Rewrite a system with tests written first
  • Refactor extensively while preserving expected behavior
  • Review migration risks and validate the final result

包含的文件(1)

  • SKILL.md5.7 KB

SKILL.md(原文)

安装前可以查看交给 AI 代理的指令内容。

TDD Migration Pipeline

Orchestrator-only workflow for migrating or rewriting codebases. You do NOT read files, write code, or validate anything yourself. You only instruct agents and pipe context (paths, not contents).

When to Use

  • Migrating codebase from one language/framework to another
  • Rewriting a system with TDD guarantees
  • Large-scale refactoring with behavioral contracts
  • When you want zero context growth in the orchestrator

Core Principles

  1. ZERO orchestrator execution - only instruct and pipe context
  2. All work done by agents - you never read/write/validate
  3. Context window stays flat - pass paths, not contents
  4. New code in separate directory - never modify source

Your Constraints

  • Never say "let me read..." or "looking at..."
  • Only say "Agent X: do Y with Z"
  • Your context should NOT grow during execution
  • All agents must use qlty and tldr skills

Pipeline Phases

Phase 1: SPEC

Instruct spec-agent (use scout or architect):
- Analyze {source_path} using tldr-skill
- Output: spec.md with behavioral contracts, types, edge cases

Agent prompt template:

Analyze the codebase at {source_path} using tldr commands (tldr structure, tldr extract, tldr calls).
Create spec.md with:
- All behavioral contracts (what each function/class promises)
- Input/output types
- Edge cases and invariants
- Dependencies between components
Write to: {target_dir}/spec.md

Phase 2: FAILING TESTS

Instruct test-agent (use arbiter):
- Read spec.md
- Write failing tests in {target_dir}/tests/
- Tests should define expected behavior before implementation

Instruct review-agent (use critic):
- Validate tests cover spec completely
- No gaps in behavioral coverage

Phase 3: ADVERSARIAL (x3 iterations)

Instruct premortem-agent (use premortem skill):
- Review spec + tests
- Identify failure modes, race conditions, edge cases
- DO NOT ASK - just add mitigations directly to spec
- Run 3 passes with fresh perspective each time

Key: Each pass should find NEW issues, not repeat previous ones.

Phase 4: PHASED PLAN

Instruct planner-agent (use architect or plan-agent):
- Input: spec.md + tests + mitigations
- Output: phased-plan.yaml
- Requirements:
  - Dependency-ordered phases
  - Each phase = one testable unit
  - Clear inputs/outputs per phase

Phase 5: BUILD LOOP (per phase)

For each phase in phased-plan.yaml:

  Instruct builder-agent (use kraken or spark):
  - Write code to pass tests for this phase
  - Use qlty for quality checks
  - Run tests after each change

  Instruct review-agent (use critic or judge):
  - Validate implementation matches spec
  - Check for regressions in previous phases
  - Verify no breaking changes

Phase 6: INTEGRATION VALIDATION

Instruct integration-agent (use atlas or validator):
- Use tldr to diff against {reference_repo}
- Check for:
  - No race conditions
  - No hangs or deadlocks
  - No breaking changes vs original
  - All behavioral contracts preserved
- Output: validation-report.md

Invocation

When invoking this workflow, specify:

SOURCE: {path to source code}
TARGET_DIR: {new folder for migrated code}
TARGET_LANG: {typescript|python|go|rust|etc}
REFERENCE_REPO: {url or path for final diff comparison}
SKILLS: [tldr-code, qlty-check, {domain-specific}]

Agent Mapping

PhaseAgent TypeSubagent
Specresearchscout or architect
Testsvalidatearbiter
Reviewreviewcritic or judge
Premortemreviewpremortem skill
Planplanarchitect or plan-agent
Buildimplementkraken (large) or spark (small)
Integrationvalidateatlas or validator

Example Orchestration

# Phase 1
Task(scout): "Analyze /src/old-system using tldr structure and tldr extract.
              Create spec.md at /migration/spec.md with all behavioral contracts."

# Phase 2
Task(arbiter): "Read /migration/spec.md. Write failing tests to /migration/tests/
               that define expected behavior."

Task(critic): "Review /migration/spec.md vs /migration/tests/.
              Report any behavioral gaps."

# Phase 3 (x3)
Task(premortem): "Review /migration/spec.md and /migration/tests/.
                 Identify failure modes. Add mitigations directly to spec. Pass 1/3."
[repeat with "Pass 2/3", "Pass 3/3"]

# Phase 4
Task(architect): "From /migration/spec.md and /migration/tests/,
                 create /migration/phased-plan.yaml with dependency-ordered phases."

# Phase 5 (loop)
Task(kraken): "Implement phase 1 from /migration/phased-plan.yaml.
              Code goes in /migration/src/. Run tests after."

Task(critic): "Review /migration/src/ against /migration/spec.md.
              Check for spec compliance and regressions."
[repeat for each phase]

# Phase 6
Task(atlas): "Run full integration tests on /migration/src/.
             Use tldr to diff against /src/old-system.
             Output /migration/validation-report.md."

Anti-Patterns (DO NOT)

  • Reading files into your context ("let me check the code...")
  • Writing code directly ("I'll implement this function...")
  • Validating anything yourself ("looking at the tests, I see...")
  • Modifying the source directory
  • Skipping the adversarial phase
  • Running build without tests first

Success Criteria

  • All tests pass
  • qlty reports clean
  • tldr diff shows no breaking changes
  • No race conditions or hangs
  • validation-report.md confirms behavioral equivalence

评价

还没有评价。欢迎分享你的使用感受。

评论

无需登录即可发表。欢迎分享使用感受、提问,或说明在哪些环境下无法运行。

还没有评论。来写第一条吧。

提交后会立即公开。请勿填写邮箱、电话等个人信息。URL 最多 2 个。

0 / 1000 字

此表单受 reCAPTCHA 保护,适用 Google 的隐私权政策和服务条款。

同一仓库的技能

Coordinate background agents through saved files, keeping lengthy work transcripts out of the main conversation. It defines how to pass results between agents, monitor progress, and verify completed work with tests.

中文简介正在准备中。当前显示英语简介。

  • Keeping long agent transcripts out of the main conversation
  • Passing research and plans between agents through files
  • Checking for stalled background agents
parcadei/Continuous-Claude-v339462026年1月27日 更新

Delegate implementation, file reading, and testing to separate agents, then bring concise summaries back to the main conversation. The rules explain when delegation helps and when a small edit is better handled directly.

中文简介正在准备中。当前显示英语简介。

  • Implementing a feature across multiple files
  • Completing a specific phase of an implementation plan
  • Delegating feature development and testing
parcadei/Continuous-Claude-v339462026年1月27日 更新

Organize implementation work across research, planning, validation, implementation, and review agents. Each stage passes files to the next, while implementation starts with failing tests and the main conversation coordinates the workflow.

中文简介正在准备中。当前显示英语简介。

  • Dividing implementation work among specialized agents
  • Checking a plan against research before implementation
  • Writing failing tests before implementing changes
parcadei/Continuous-Claude-v339462026年1月27日 更新

Connect Agentica SDK agents to Claude Code CLI through a proxy, an intermediary server. Use setup and debugging guidance to address file permissions, streamed responses, result formatting, and agents reporting success without performing the requested operations.

中文简介正在准备中。当前显示英语简介。

  • Connecting Agentica agents to Claude Code tools
  • Investigating file write and edit permission errors
  • Debugging streaming and REPL response formats
parcadei/Continuous-Claude-v339462026年1月27日 更新

Consult Agentica APIs when building workflows where multiple AI agents cooperate. This reference covers eleven coordination patterns, agent tracking, shared state, handoffs, and ways to combine results, with pointers to detailed API specifications.

中文简介正在准备中。当前显示英语简介。

  • Choose a coordination pattern for multiple agents
  • Check pattern constructors and methods
  • Implement custom coordination patterns
parcadei/Continuous-Claude-v339462026年1月27日 更新

Write clearer instructions for Agentica and REPL agents by specifying roles, file operations, and output formats. Includes templates for dividing research, coordinating specialists, reviewing solutions, and passing results between agents through files.

中文简介正在准备中。当前显示英语简介。

  • Clarifying instructions for reading and editing files
  • Dividing research among multiple agents
  • Passing findings and plans between agents
parcadei/Continuous-Claude-v339462026年1月27日 更新

查看 parcadei 的全部技能

报告此技能的问题