planning — for Claude Code planning, hospital-management-system-v3, community, for Claude Code, ide skills, Feature, Pipeline, Generate, quality, through

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关于此技能

适用场景: Ideal for AI agents that need feature planning pipeline. 本地化技能摘要: # Feature Planning Pipeline Generate quality plans through systematic discovery, synthesis, verification, and decomposition. This AI agent skill supports Claude Code, Cursor, and Windsurf workflows.

功能特性

Feature Planning Pipeline
Generate quality plans through systematic discovery, synthesis, verification, and decomposition.
----------------- ---------------------------------------- -----------------------------------
0. Worktree Setup bd worktree Isolated feature branch
1. Discovery Parallel sub-agents, gkg, Librarian, exa Discovery Report

# 核心主题

thanhquan3010 thanhquan3010
[0]
[0]
更新于: 3/14/2026

Killer-Skills Review

Decision support comes first. Repository text comes second.

Reference-Only Page Review Score: 10/11

This page remains useful for teams, but Killer-Skills treats it as reference material instead of a primary organic landing page.

Original recommendation layer Concrete use-case guidance Explicit limitations and caution Quality floor passed for review
Review Score
10/11
Quality Score
64
Canonical Locale
en
Detected Body Locale
en

适用场景: Ideal for AI agents that need feature planning pipeline. 本地化技能摘要: # Feature Planning Pipeline Generate quality plans through systematic discovery, synthesis, verification, and decomposition. This AI agent skill supports Claude Code, Cursor, and Windsurf workflows.

核心价值

推荐说明: planning helps agents feature planning pipeline. Feature Planning Pipeline Generate quality plans through systematic discovery, synthesis, verification, and decomposition. This AI agent skill supports Claude

适用 Agent 类型

适用场景: Ideal for AI agents that need feature planning pipeline.

赋予的主要能力 · planning

适用任务: Applying Feature Planning Pipeline
适用任务: Applying Generate quality plans through systematic discovery, synthesis, verification, and decomposition
适用任务: Applying ----------------- ---------------------------------------- -----------------------------------

! 使用限制与门槛

  • 限制说明: Skip worktree only if : Quick fix on main that won't create new beads.
  • 限制说明: After PR merges: Skip worktree only if : Quick fix on main that won't create new beads
  • 限制说明: Requires repository-specific context from the skill documentation

Why this page is reference-only

  • - Current locale does not satisfy the locale-governance contract.

Source Boundary

The section below is imported from the upstream repository and should be treated as secondary evidence. Use the Killer-Skills review above as the primary layer for fit, risk, and installation decisions.

评审后的下一步

先决定动作,再继续看上游仓库材料

Killer-Skills 的主价值不应该停在“帮你打开仓库说明”,而是先帮你判断这项技能是否值得安装、是否应该回到可信集合复核,以及是否已经进入工作流落地阶段。

实验室 Demo

Browser Sandbox Environment

⚡️ Ready to unleash?

Experience this Agent in a zero-setup browser environment powered by WebContainers. No installation required.

Boot Container Sandbox

常见问题与安装步骤

以下问题与步骤与页面结构化数据保持一致,便于搜索引擎理解页面内容。

? FAQ

planning 是什么?

适用场景: Ideal for AI agents that need feature planning pipeline. 本地化技能摘要: # Feature Planning Pipeline Generate quality plans through systematic discovery, synthesis, verification, and decomposition. This AI agent skill supports Claude Code, Cursor, and Windsurf workflows.

如何安装 planning?

运行命令:npx killer-skills add thanhquan3010/hospital-management-system-v3/planning。支持 Cursor、Windsurf、VS Code、Claude Code 等 19+ IDE/Agent。

planning 适用于哪些场景?

典型场景包括:适用任务: Applying Feature Planning Pipeline、适用任务: Applying Generate quality plans through systematic discovery, synthesis, verification, and decomposition、适用任务: Applying ----------------- ---------------------------------------- -----------------------------------。

planning 支持哪些 IDE 或 Agent?

该技能兼容 Cursor, Windsurf, VS Code, Trae, Claude Code, OpenClaw, Aider, Codex, OpenCode, Goose, Cline, Roo Code, Kiro, Augment Code, Continue, GitHub Copilot, Sourcegraph Cody, and Amazon Q Developer。可使用 Killer-Skills CLI 一条命令通用安装。

planning 有哪些限制?

限制说明: Skip worktree only if : Quick fix on main that won't create new beads.;限制说明: After PR merges: Skip worktree only if : Quick fix on main that won't create new beads;限制说明: Requires repository-specific context from the skill documentation。

安装步骤

  1. 1. 打开终端

    在你的项目目录中打开终端或命令行。

  2. 2. 执行安装命令

    运行:npx killer-skills add thanhquan3010/hospital-management-system-v3/planning。CLI 会自动识别 IDE 或 AI Agent 并完成配置。

  3. 3. 开始使用技能

    planning 已启用,可立即在当前项目中调用。

! 参考页模式

此页面仍可作为安装与查阅参考,但 Killer-Skills 不再把它视为主要可索引落地页。请优先阅读上方评审结论,再决定是否继续查看上游仓库说明。

Upstream Repository Material

The section below is imported from the upstream repository and should be treated as secondary evidence. Use the Killer-Skills review above as the primary layer for fit, risk, and installation decisions.

Upstream Source

planning

# Feature Planning Pipeline Generate quality plans through systematic discovery, synthesis, verification, and decomposition. This AI agent skill supports

SKILL.md
Readonly
Upstream Repository Material
The section below is imported from the upstream repository and should be treated as secondary evidence. Use the Killer-Skills review above as the primary layer for fit, risk, and installation decisions.
Supporting Evidence

Feature Planning Pipeline

Generate quality plans through systematic discovery, synthesis, verification, and decomposition.

Pipeline Overview

USER REQUEST → Worktree Setup → Discovery → Synthesis → Verification → Decomposition → Validation → Track Planning → Ready Plan
PhaseToolOutput
0. Worktree Setupbd worktreeIsolated feature branch
1. DiscoveryParallel sub-agents, gkg, Librarian, exaDiscovery Report
2. SynthesisOracleApproach + Risk Map
3. VerificationSpikes via MULTI_AGENT_WORKFLOWValidated Approach + Learnings
4. Decompositionfile-beads skill.beads/*.md files
5. Validationbv + OracleValidated dependency graph
6. Track Planningbv --robot-planExecution plan with parallel tracks

Phase 0: Worktree Setup (Mandatory)

Why: Beads are tracked in git. Without worktrees, branch switching causes conflicts when PRs merge.

Always create a worktree before creating beads for a feature:

bash
1# From main repo root 2bd worktree create .worktrees/<feature-name> --branch feature/<feature-name> 3cd .worktrees/<feature-name>

This creates a redirect file so all beads operations share the main repo's .beads/ database. No merge conflicts when PR lands.

After PR merges:

bash
1cd <main-repo> 2git pull 3bd worktree remove .worktrees/<feature-name>

Skip worktree only if: Quick fix on main that won't create new beads.

Phase 1: Discovery (Parallel Exploration)

Launch parallel sub-agents to gather codebase intelligence:

Task() → Agent A: Architecture snapshot (gkg repo_map)
Task() → Agent B: Pattern search (find similar existing code)
Task() → Agent C: Constraints (package.json, tsconfig, deps)
Librarian → External patterns ("how do similar projects do this?")
exa → Library docs (if external integration needed)

Discovery Report Template

Save to history/<feature>/discovery.md:

markdown
1# Discovery Report: <Feature Name> 2 3## Architecture Snapshot 4 5- Relevant packages: ... 6- Key modules: ... 7- Entry points: ... 8 9## Existing Patterns 10 11- Similar implementation: <file> does X using Y pattern 12- Reusable utilities: ... 13- Naming conventions: ... 14 15## Technical Constraints 16 17- Node version: ... 18- Key dependencies: ... 19- Build requirements: ... 20 21## External References 22 23- Library docs: ... 24- Similar projects: ...

Phase 2: Synthesis (Oracle)

Feed Discovery Report to Oracle for gap analysis:

oracle(
  task: "Analyze gap between current codebase and feature requirements",
  context: "Discovery report attached. User wants: <feature>",
  files: ["history/<feature>/discovery.md"]
)

Oracle produces:

  1. Gap Analysis - What exists vs what's needed
  2. Approach Options - 1-3 strategies with tradeoffs
  3. Risk Assessment - LOW / MEDIUM / HIGH per component

Risk Classification

LevelCriteriaVerification
LOWPattern exists in codebaseProceed
MEDIUMVariation of existing patternInterface sketch, type-check
HIGHNovel or external integrationSpike required

Risk Indicators

Pattern exists in codebase? ─── YES → LOW base
                            └── NO  → MEDIUM+ base

External dependency? ─── YES → HIGH
                     └── NO  → Check blast radius

Blast radius >5 files? ─── YES → HIGH
                       └── NO  → MEDIUM

Save to history/<feature>/approach.md:

markdown
1# Approach: <Feature Name> 2 3## Gap Analysis 4 5| Component | Have | Need | Gap | 6| --------- | ---- | ---- | --- | 7| ... | ... | ... | ... | 8 9## Recommended Approach 10 11<Description> 12 13### Alternative Approaches 14 151. <Option A> - Tradeoff: ... 162. <Option B> - Tradeoff: ... 17 18## Risk Map 19 20| Component | Risk | Reason | Verification | 21| ----------- | ---- | ---------------- | ------------ | 22| Stripe SDK | HIGH | New external dep | Spike | 23| User entity | LOW | Follows existing | Proceed |

Phase 3: Verification (Risk-Based)

For HIGH Risk Items → Create Spike Beads

Spikes are mini-plans executed via MULTI_AGENT_WORKFLOW:

bash
1bd create "Spike: <question to answer>" -t epic -p 0 2bd create "Spike: Test X" -t task --blocks <spike-epic> 3bd create "Spike: Verify Y" -t task --blocks <spike-epic>

Spike Bead Template

markdown
1# Spike: <specific question> 2 3**Time-box**: 30 minutes 4**Output location**: .spikes/<spike-id>/ 5 6## Question 7 8Can we <specific technical question>? 9 10## Success Criteria 11 12- [ ] Working throwaway code exists 13- [ ] Answer documented (yes/no + details) 14- [ ] Learnings captured for main plan 15 16## On Completion 17 18Close with: `bd close <id> --reason "YES: <approach>" or "NO: <blocker>"`

Execute Spikes

Use the MULTI_AGENT_WORKFLOW:

  1. bv --robot-plan to parallelize spikes
  2. Task() per spike with time-box
  3. Workers write to .spikes/<feature>/<spike-id>/
  4. Close with learnings: bd close <id> --reason "<result>"

Aggregate Spike Results

oracle(
  task: "Synthesize spike results and update approach",
  context: "Spikes completed. Results: ...",
  files: ["history/<feature>/approach.md"]
)

Update approach.md with validated learnings.

Phase 4: Decomposition (file-beads skill)

Load the file-beads skill and create beads with embedded learnings:

bash
1skill("file-beads")

Bead Requirements

Each bead MUST include:

  • Spike learnings embedded in description (if applicable)
  • Reference to .spikes/ code for HIGH risk items
  • Clear acceptance criteria
  • File scope for track assignment

Example Bead with Learnings

markdown
1# Implement Stripe webhook handler 2 3## Context 4 5Spike bd-12 validated: Stripe SDK works with our Node version. 6See `.spikes/billing-spike/webhook-test/` for working example. 7 8## Learnings from Spike 9 10- Must use `stripe.webhooks.constructEvent()` for signature verification 11- Webhook secret stored in `STRIPE_WEBHOOK_SECRET` env var 12- Raw body required (not parsed JSON) 13 14## Acceptance Criteria 15 16- [ ] Webhook endpoint at `/api/webhooks/stripe` 17- [ ] Signature verification implemented 18- [ ] Events: `checkout.session.completed`, `invoice.paid`

Phase 5: Validation

Run bv Analysis

bash
1bv --robot-suggest # Find missing dependencies 2bv --robot-insights # Detect cycles, bottlenecks 3bv --robot-priority # Validate priorities

Fix Issues

bash
1bd dep add <from> <to> # Add missing deps 2bd dep remove <from> <to> # Break cycles 3bd update <id> --priority X # Adjust priorities

Oracle Final Review

oracle(
  task: "Review plan completeness and clarity",
  context: "Plan ready. Check for gaps, unclear beads, missing deps.",
  files: [".beads/"]
)

Phase 6: Track Planning

This phase creates an execution-ready plan so the orchestrator can spawn workers immediately without re-analyzing beads.

Step 1: Get Parallel Tracks

bash
1bv --robot-plan 2>/dev/null | jq '.plan.tracks'

Step 2: Assign File Scopes

For each track, determine the file scope based on beads in that track:

bash
1# For each bead, check which files it touches 2bd show <bead-id> # Look at description for file hints

Rules:

  • File scopes must NOT overlap between tracks
  • Use glob patterns: packages/sdk/**, apps/server/**
  • If overlap unavoidable, merge into single track

Step 3: Generate Agent Names

Assign unique adjective+noun names to each track:

  • BlueLake, GreenCastle, RedStone, PurpleBear, etc.
  • Names are memorable identifiers, NOT role descriptions

Step 4: Create Execution Plan

Save to history/<feature>/execution-plan.md:

markdown
1# Execution Plan: <Feature Name> 2 3Epic: <epic-id> 4Generated: <date> 5 6## Tracks 7 8| Track | Agent | Beads (in order) | File Scope | 9| ----- | ----------- | --------------------- | ----------------- | 10| 1 | BlueLake | bd-10 → bd-11 → bd-12 | `packages/sdk/**` | 11| 2 | GreenCastle | bd-20 → bd-21 | `packages/cli/**` | 12| 3 | RedStone | bd-30 → bd-31 → bd-32 | `apps/server/**` | 13 14## Track Details 15 16### Track 1: BlueLake - <track-description> 17 18**File scope**: `packages/sdk/**` 19**Beads**: 20 211. `bd-10`: <title> - <brief description> 222. `bd-11`: <title> - <brief description> 233. `bd-12`: <title> - <brief description> 24 25### Track 2: GreenCastle - <track-description> 26 27**File scope**: `packages/cli/**` 28**Beads**: 29 301. `bd-20`: <title> - <brief description> 312. `bd-21`: <title> - <brief description> 32 33### Track 3: RedStone - <track-description> 34 35**File scope**: `apps/server/**` 36**Beads**: 37 381. `bd-30`: <title> - <brief description> 392. `bd-31`: <title> - <brief description> 403. `bd-32`: <title> - <brief description> 41 42## Cross-Track Dependencies 43 44- Track 2 can start after bd-11 (Track 1) completes 45- Track 3 has no cross-track dependencies 46 47## Key Learnings (from Spikes) 48 49Embedded in beads, but summarized here for orchestrator reference: 50 51- <learning 1> 52- <learning 2>

Validation

Before finalizing, verify:

bash
1# No cycles in the graph 2bv --robot-insights 2>/dev/null | jq '.Cycles' 3 4# All beads assigned to tracks 5bv --robot-plan 2>/dev/null | jq '.plan.unassigned'

Output Artifacts

ArtifactLocationPurpose
Discovery Reporthistory/<feature>/discovery.mdCodebase snapshot
Approach Documenthistory/<feature>/approach.mdStrategy + risks
Spike Code.spikes/<feature>/Reference implementations
Spike LearningsEmbedded in beadsContext for workers
Beads.beads/*.mdExecutable work items
Execution Planhistory/<feature>/execution-plan.mdTrack assignments for orchestrator

Quick Reference

Tool Selection

NeedTool
Codebase structuremcp__gkg__repo_map
Find definitionsmcp__gkg__search_codebase_definitions
Find usagesmcp__gkg__get_references
Semantic searchmcp__morph_mcp__warpgrep_codebase_search
External patternslibrarian
Library docsmcp__MCP_DOCKER__resolve-library-idmcp__MCP_DOCKER__get-library-docs
Web researchmcp__MCP_DOCKER__web_search_exa
Gap analysisoracle
Create beadsskill("file-beads") + bd create
Validate graphbv --robot-*

Common Mistakes

  • Skipping discovery → Plan misses existing patterns
  • No risk assessment → Surprises during execution
  • No spikes for HIGH risk → Blocked workers
  • Missing learnings in beads → Workers re-discover same issues
  • No bv validation → Broken dependency graph

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