tapd-story-pipeline

Automates single TAPD story implementation from clarification through git commit.

840|261|Updated Apr 18, 2019
One-click install
npx skills add https://github.com/TencentBlueKing/bk-bcs --skill tapd-story-pipeline
Or copy as Structured Prompt for Agent
Please help me install this Agent Skill.
Skill: tapd-story-pipeline
Source: https://github.com/TencentBlueKing/bk-bcs/tree/main/.agents/skills/tapd-story-pipeline
Command: npx skills add https://github.com/TencentBlueKing/bk-bcs --skill tapd-story-pipeline

SYSTEM DOCUMENTATION & REQUIREMENTS

💡 This Skill includes scripts (resource) and references (resource) components.

What problem does it solve?

Manually driving a single requirement from a TAPD ticket to committed code involves many disconnected steps: technical clarification, planning, task breakdown, TDD implementation, multi-dimensional validation, and committing. This Skill orchestrates that entire flow as a resumable state machine with checkpoints, retries, and rollback reentry.

Core Features & Use Cases

  • Six-stage pipeline: Chains specify, plan, tasks, implement, validate, and commit sub-skills, each dispatched to specialized subagents (tech-lead, backend/frontend-developer, code-reviewer, qa-engineer).
  • Checkpoint and reentry protocol: Supports confirm, blocked, fail, and abort checkpoints with semantic commands (approve, reject, answer, retry, abort), attempt limits, and code-preserved rollbacks tracked in meta.yaml.
  • Cost and stats tracking: Collects subagent token/credit usage via PostToolUse hooks into cost-events.jsonl, reconciles at commit time, and writes change statistics plus a Conventional Commits message before updating the TAPD story status.
  • Use Case: A developer says "implement story #1234567890, workspace 20000001"; the pipeline pulls the requirement via TAPD MCP, generates spec/plan/tasks, pauses for human review, then implements with TDD, runs four parallel validation reports, and commits the code.

Quick Start

Ask the assistant to implement a TAPD requirement by saying "help me implement story #1234567890 in workspace 20000001" and follow the checkpoint prompts to approve or answer questions.

Frequently Asked Questions about tapd-story-pipeline

High-intent search queries and answers about installing and using this skill.

FAQPage Schema
How do I implement a TAPD story automatically with an AI pipeline?

Invoke the pipeline with the story ID and workspace ID, for example by saying implement story #1234567890 in workspace 20000001. The pipeline pulls the requirement via TAPD MCP, runs specify, plan, and tasks stages, then pauses at a confirm checkpoint for your review before implementing and committing.

What stages does the single story development pipeline run?

It runs six stages in order: specify (technical clarification and spec.md), plan (development plan and research), tasks (task breakdown and analysis), implement (TDD coding), validate (architecture, security, code review, and test coverage checks), and commit (statistics, commit message, git commit, TAPD status update).

How do I resume the pipeline after it exits at a checkpoint?

Re-invoke the pipeline with a semantic command matching the checkpoint: approve or reject for confirm checkpoints, answer after filling questions.md for blocked checkpoints, retry after fixing content files for fail checkpoints, or abort to stop. The pipeline reads meta.yaml and continues from the recorded phase.

Does the pipeline support fullstack requirements with frontend and backend code?

Yes. When the specify stage classifies the story as fullstack, the implement stage runs two serial rounds: backend-developer first, then frontend-developer using the plan.md API contract as the authoritative interface. Validation fixes are routed to the appropriate developer agent by affected file paths.

What happens when validation finds problems in the implemented code?

If all findings are attributed to the code itself, an in-place fix subagent runs and the four validation checks repeat, up to three rounds per attempt. If findings trace back to insufficient spec or plan, the pipeline rolls back to the upstream phase while preserving the code and records unresolved findings for differential fixing.

Why are the cost statistics in meta.yaml all zero?

Zero cost totals mean the PostToolUse hook is not installed in the host IDE settings, so cost-events.jsonl is never written. Merge the hook configuration from the skill's scripts/settings.json into the project's .claude/settings.json; the pipeline still works normally without it, only cost tracking is affected.