ln-220-story-coordinator

安装量: 112
排名: #7639

安装

npx skills add https://github.com/levnikolaevich/claude-code-skills --skill ln-220-story-coordinator

Universal Story management coordinator that delegates CREATE/REPLAN operations to specialized workers after building IDEAL Story plan.

When to Use This Skill

Use when:

  • Decompose Epic to User Stories (5-10 Stories covering Epic scope)

  • Update existing Stories when Epic requirements change

  • Rebalance Story scopes within Epic

  • Add new Stories to existing Epic structure

Core Pattern: Decompose-First

Key principle: Build IDEAL Story plan FIRST, THEN check existing Stories to determine mode:

  • No existing Stories → CREATE MODE (delegate to ln-221-story-creator)

  • Has existing Stories → REPLAN MODE (delegate to ln-222-story-replanner)

Rationale: Ensures consistent Story decomposition based on current Epic requirements, independent of existing Story structure (may be outdated).

Story Numbering Convention

Rule: Stories start from Story 1 (US001), NO Story 0 reserved.

Rationale:

  • Epic 0 = Infrastructure Epic (group of 5-10 Stories like any other Epic)

  • Stories within Epic 0 numbered normally: US001, US002, ... US010

  • No reserved Story 0 (unlike Epics, Stories don't need infrastructure placeholder)

Numbering within Epic:

  • Epic 0: Infrastructure → US001-US010 (logging, monitoring, CI/CD Stories)

  • Epic 1: User Management → US011-US020 (registration, login, profile Stories)

  • Epic 2: Product Catalog → US021-US030 (product list, search, details Stories)

Next Story Number: Incremented sequentially across ALL Epics (read from kanban_board.md Epic Story Counters table)

How It Works

Phase 1: Context Assembly

Objective: Gather context for Story planning (Epic details, planning questions, frontend context, fallback docs, user input)

Step 1: Discovery (Automated)

Auto-discovers from docs/tasks/kanban_board.md:

  • Team ID: Reads Linear Configuration table

  • Epic: Parses Epic number from request → Validates in Linear → Loads Epic description

User format: "Epic N" (Linear Project number, e.g., "Epic 7: OAuth Authentication")

  • Query: get_project(query="Epic N") → Fetch full Epic document

  • Extract: Goal, Scope In/Out, Success Criteria, Technical Notes (Standards Research if Epic created by ln-210 v7.0.0+)

  • Note: Epic N = Linear Project number (global), NOT initiative-internal index (Epic 0-N)

  • Next Story Number: Reads Epic Story Counters table → Gets next sequential number

Step 2: Extract Planning Information (Automated)

Parses Epic structure for Story planning questions:

| Q1 - User/Persona | Epic Goal ("Enable [persona]...") + Scope In (user roles)

| Q2 - What they want | Epic Scope In (capabilities) + functional requirements

| Q3 - Why it matters | Epic Success Criteria (metrics) + Goal (business value)

| Q4 - Which Epic | Already from Step 1

| Q5 - Main AC | Derive from Epic Scope In features → testable scenarios

| Q6 - Application type | Epic Technical Notes (UI/API mentioned) → Default: API

Step 3: Frontend Research (Optional)

Trigger: If Q2 (capabilities) OR Q5 (AC) missing after Step 2

Process:

  • Scan HTML files: Glob **/*.html, src/**/*.html

  • Extract:

Forms → AC scenarios (e.g., <form id="login"> → "Given valid credentials, When submit, Then login success")

  • Buttons/Actions → capabilities (e.g., <button id="register"> → "User registration")

  • Validation rules → edge case AC (e.g., minlength="8" → "Given password <8 chars, Then error")

  • Combine with Epic context, deduplicate, prioritize Epic AC if conflict

Fallback: If no HTML → Skip to Step 4

Step 4: Fallback Search Chain

Objective: Fill missing Q1-Q6 BEFORE asking user.

For each question with no answer from Step 2-3:

| Q1 (User/Persona) | Search requirements.md for "User personas", "Actors" → Default "User" if not found

| Q3 (Why it matters) | Search requirements.md for "Business objectives", "Goals" → Infer from Epic Success Criteria

| Q6 (Application type) | Search tech_stack.md for "Frontend", "Backend", "API" → Default "API"

Skip: Q2, Q5 (Epic + HTML are sources of truth), Q4 (already known)

Step 5: User Input (Only if Missing)

If still missing after Step 2 + 3 + 4:

  • Show extracted: "From Epic: [Epic info]. From HTML: [HTML info]. From fallback: [fallback info]"

  • Ask user to confirm or provide remaining missing details

If all questions answered from Epic OR HTML OR fallback: Skip user prompts, proceed to Phase 2

Output: Complete context (Epic details, next Story number, Q1-Q6 answers)

Phase 2: Standards Research (Delegated)

Objective: Research industry standards/patterns BEFORE Story generation to ensure implementation follows best practices.

Why: Prevents outdated patterns or RFC violations (e.g., OAuth without PKCE).

Process:

  • Parse Epic for domain keywords: Extract domain from Epic goal/Scope In (authentication, rate limiting, payments)

  • Delegate to ln-001-standards-researcher:

Call Skill(skill: "ln-001-standards-researcher", epic_description="[Epic full description]", story_domain="[domain]")

  • Wait for Standards Research (Markdown string)

  • Store: Cache for Phase 5a/5b (workers insert in Story Technical Notes)

Output: Standards Research stored for ALL Stories in Epic

Skip conditions:

  • Epic has NO standards in Technical Notes

  • Story domain is trivial CRUD

  • Epic says "research not needed"

Time-box: 15-20 minutes (handled by ln-001)

Note: Research done ONCE per Epic, results reused for all Stories (5-10 Stories benefit from single research)

Phase 3: Planning

Objective: Build IDEAL Story plan, determine execution mode

Story Grouping Guidelines:

Each Story = ONE vertical slice of user capability (end-to-end: UI → API → Service → DB).

✅ GOOD Story Grouping (1 Story = 1 user journey):

  • ✅ "User registration" (form → validation → API → database → email)

  • ✅ "Password reset" (request link → verify token → set password → update DB)

  • ✅ "Product search" (input → filter/sort → API → DB query → display)

❌ BAD Story Grouping (horizontal slices):

  • ❌ "Create user table" (database only, no user value → Task, not Story)

  • ❌ "User registration API endpoint" (API layer only, not vertical)

  • ❌ "Registration UI form" (frontend only, not vertical)

Rule: 1 Story = 1 user capability = 3-5 AC = 6-20 hours = 10-28 tests

Build IDEAL Plan (Automated):

  • Analyze Epic Scope: Review features in Epic Scope In, identify user capabilities

  • Determine Story Count:

Simple Epic (1-3 features): 3-5 Stories

  • Medium Epic (4-7 features): 6-8 Stories

  • Complex Epic (8+ features): 8-10 Stories

  • Max 10 Stories per Epic

  • Story Size Guidelines:

| AC | 3 | 5 | >5 AC (split) | <3 AC (merge)

| Duration | 6h | 20h | >20h (split) | <6h (merge)

| Tests | 10 | 28 | >28 tests (split) | <10 tests (merge)

Over-decomposition indicators:

  • ❌ <3 AC, <6 hours, <10 tests

  • ❌ Purely technical (no user value)

  • ❌ Title starts with "Add", "Create", "Update" (likely Task)

  • ❌ Crosses only 1-2 layers (not vertical)

  • Build IDEAL Plan "in mind":

Each Story: persona + capability + business value

  • Each Story: 3-5 testable AC (Given-When-Then)

  • Stories ordered by dependency

  • Each Story: Test Strategy section exists but is empty (tests planned later by ln-510-test-planner)

  • Each Story: Technical Notes (architecture, integrations, Standards Research from Phase 2, guide links)

INVEST Checklist:

| Independent | Can develop/deploy without blocking others | "Request OAuth token" (independent) | "Validate token" depends on "Request token" (merge or ensure API contract)

| Negotiable | AC focus on WHAT, not HOW | "User gets valid token" (what) | "Use authlib 1.3.0, store in Redis" (how)

| Valuable | Clear business value | "User refreshes expired token to maintain session" | "Add token_refresh table" (no user value)

| Estimable | Can estimate 6-20h | Clear scope, known patterns, researched standards | "Implement authentication" (too vague)

| Small | Fits 1-2 sprints | 3-5 AC, 6-20h | "Full OAuth flow" (>5 AC, >20h)

| Testable | AC measurable | "Given valid refresh token, Then receive token <200ms" | "Token refresh should be fast" (not measurable)

Output: IDEAL Story plan (5-10 Stories) with titles, statements, core AC, ordering

Phase 4: Check Existing & Detect Mode

Objective: Determine execution mode based on existing Stories AND user intent

Process:

Query Linear for existing Stories in Epic:

list_issues(project=Epic.id, label="user-story")

Mode Detection:

  • Analyze user request for keywords:

ADD keywords: "add story", "one more story", "additional story", "append"

  • REPLAN keywords: "update plan", "revise", "requirements changed", "replan stories"

  • Decision matrix:

| Count = 0 | CREATE | Phase 5a: ln-221-story-creator

| Count ≥ 1 AND ADD keywords | ADD | Phase 5c: ln-221-story-creator (appendMode)

| Count ≥ 1 AND REPLAN keywords | REPLAN | Phase 5b: ln-222-story-replanner

| Count ≥ 1 AND ambiguous | ASK USER | "Add new Story or revise the plan?"

Important: Orchestrator loads metadata ONLY (ID, title, status). Workers load FULL descriptions (token efficiency).

Output: Execution mode determined + existingCount for workers

Phase 5a: Delegate CREATE (No Existing Stories)

Trigger: Epic has no Stories yet (first decomposition)

Delegation:

Call ln-221-story-creator via Skill tool:

Skill(
  skill: "ln-221-story-creator",
  epicData: {id, title, description},
  idealPlan: [ /* 5-10 Stories from Phase 3 */ ],
  standardsResearch: "Standards Research from Phase 2",
  teamId: "team-id",
  autoApprove: false  // or true for automation
)

Worker handles:

  • Generate Story documents (8 sections, insert Standards Research)

  • Validate INVEST criteria

  • Show preview

  • User confirmation (if autoApprove=false)

  • Create in Linear (project=Epic, labels=user-story, state=Backlog)

  • Update kanban_board.md (Epic Grouping Algorithm)

Output: Created Story URLs + summary from worker

Phase 5b: Delegate REPLAN (Existing Stories Found)

Trigger: Epic already has Stories (requirements changed)

Delegation:

Call ln-222-story-replanner via Skill tool:

Skill(
  skill: "ln-222-story-replanner",
  epicData: {id, title, description},
  idealPlan: [ /* 5-10 Stories from Phase 3 */ ],
  standardsResearch: "Standards Research from Phase 2",
  existingCount: N,
  teamId: "team-id",
  autoApprove: false  // or true for automation
)

Worker handles:

  • Load existing Stories (Progressive Loading: ONE BY ONE for token efficiency)

  • Compare IDEAL vs existing (KEEP/UPDATE/OBSOLETE/CREATE operations)

  • Show replan summary with diffs (AC, Standards Research, Technical Notes)

  • User confirmation (if autoApprove=false)

  • Execute operations (respecting status constraints: Backlog/Todo only, warnings for In Progress/Review/Done)

  • Update kanban_board.md (add NEW Stories only via Epic Grouping Algorithm)

Output: Operation results + warnings + affected Story URLs from worker

Phase 5c: Delegate ADD (Append to Existing Stories)

Trigger: Epic has Stories, user wants to ADD more (not replan existing)

Delegation:

Call ln-221-story-creator via Skill tool with appendMode:

Skill(
  skill: "ln-221-story-creator",
  appendMode: true,  // ADD to existing, don't replace
  epicData: {id, title, description},
  newStoryDescription: userRequestedStory,  // Single Story from user request
  standardsResearch: "Standards Research from Phase 2",
  teamId: "team-id",
  autoApprove: false
)

Key differences from CREATE MODE:

  • appendMode: true → Skip full IDEAL plan, create only requested Story

  • newStoryDescription → User's specific request (e.g., "add authorization Story")

  • Does NOT require Phase 3 IDEAL plan for all Stories

  • Preserves existing Stories without comparison

Worker handles:

  • Research standards for NEW Story only

  • Generate Story document (8 sections)

  • Validate INVEST criteria

  • Create in Linear (append to existing)

  • Update kanban_board.md

Output: Created Story URL + summary from worker

TodoWrite format (mandatory): Add phases to todos before starting:

- Phase 1: Context Assembly (in_progress)
- Phase 2: Standards Research via ln-221 (pending)
- Phase 3: Build IDEAL Story Plan (pending)
- Phase 4: Check Existing Stories (pending)
- Phase 5: Delegate to ln-222/ln-223 (pending)
- Wait for worker result (pending)

Mark each as in_progress when starting, completed when done.

Integration with Ecosystem

Calls:

  • ln-001-standards-researcher (Phase 2) - research standards/patterns for Epic

  • ln-221-story-creator (Phase 5a, 5c) - CREATE and ADD worker

  • ln-222-story-replanner (Phase 5b) - REPLAN worker

Called by:

  • ln-200-scope-decomposer (Phase 3) - automated full decomposition (scope → Epics → Stories)

  • Manual - user invokes for Epic Story creation/replanning

Upstream:

  • ln-210-epic-coordinator - creates Epics (prerequisite for Story creation)

Downstream:

  • ln-300-task-coordinator - creates implementation tasks for each Story

  • ln-310-story-validator - validates Story structure/content

  • ln-400-story-executor - orchestrates task execution for Story

Definition of Done

✅ Phase 1: Context Assembly Complete:

Team ID, Epic number, Next Story Number loaded from kanban_board.md Q1-Q6 extracted from Epic (Step 2) Frontend Research attempted if Q2/Q5 missing (Step 3) Fallback Search attempted for missing info (Step 4) User input requested if still missing (Step 5) Complete Story planning context assembled

✅ Phase 2: Standards Research Complete:

Epic parsed for domain keywords ln-001-standards-researcher invoked with Epic description + Story domain Standards Research cached for workers OR Phase 2 skipped (trivial CRUD, no standards, explicit skip)

✅ Phase 3: Planning Complete:

Epic Scope analyzed Optimal Story count determined (5-10 Stories) IDEAL Story plan created (titles, statements, core AC, ordering) Story Grouping Guidelines validated (vertical slicing) INVEST checklist validated for all Stories

✅ Phase 4: Check Existing Complete:

Queried Linear for existing Stories (count only) Execution mode determined (CREATE or REPLAN)

✅ Phase 5: Delegation Complete:

Called ln-221-story-creator (Phase 5a) OR ln-222-story-replanner (Phase 5b) via Skill tool Passed epicData, idealPlan, standardsResearch, teamId, autoApprove Received output from worker (Story URLs + summary + next steps)

Example Usage

CREATE MODE (First Time):

"Create stories for Epic 7: OAuth Authentication"

Process:

  • Phase 1: Context Assembly → Discovery (Team "API", Epic 7, US004), Extract (Persona: API client, Value: secure API access), Frontend Research (HTML login/register forms → AC), Fallback Search (requirements.md for personas)

  • Phase 2: Standards Research → Epic mentions "OAuth 2.0", delegate ln-001 → Standards Research with RFC 6749, patterns

  • Phase 3: Planning → Build IDEAL (5 Stories: "Register client", "Request token", "Validate token", "Refresh token", "Revoke token")

  • Phase 4: Check Existing → Count = 0 → CREATE MODE

  • Phase 5a: Delegate CREATE → Call ln-221-story-creator → US004-US008 created with Standards Research

REPLAN MODE (Requirements Changed):

"Replan stories for Epic 7 - removed custom token formats, added scope management"

Process:

  • Phase 1: Context Assembly → Discovery (Team "API", Epic 7, has US004-US008), Extract (Removed custom formats, added scopes)

  • Phase 2: Standards Research → Epic mentions "OAuth 2.0 scopes", delegate ln-001 → Updated Standards Research with RFC 6749 Section 3.3

  • Phase 3: Planning → Build IDEAL (5 Stories: "Register client", "Request token", "Validate token", "Refresh token", "Manage scopes")

  • Phase 4: Check Existing → Count = 5 → REPLAN MODE

  • Phase 5b: Delegate REPLAN → Call ln-222-story-replanner → KEEP 4, UPDATE Technical Notes (scope research), OBSOLETE US008, CREATE US009

Best Practices

Story Content:

  • Research-First: Always perform Phase 2 research (standards/patterns) before Story generation

Story level: STANDARDS/PATTERNS (OAuth RFC 6749, middleware pattern)

  • Task level: LIBRARIES (authlib vs oauthlib) - delegated by ln-300

  • Business-oriented Stories: Each Story = USER JOURNEY (what user does, what they get), NOT technical tasks

✅ GOOD: "As API client, I want to refresh expired token, so that I maintain session without re-authentication"

  • ❌ BAD: "Create token refresh endpoint in API" (Task, not Story)

  • Vertical Slicing: Each Story delivers end-to-end functionality (UI → API → Service → DB)

  • One capability per Story: Clear, focused persona + capability + value

  • Testable AC: Given-When-Then, 3-5 AC, specific criteria ("<200ms" not "fast")

  • Test Strategy: Section exists but is empty at Story creation (tests planned later by ln-510-test-planner)

  • Standards Research: Include Phase 2 research in ALL Story Technical Notes

Story Decomposition:

  • Decompose-First: Build IDEAL plan before checking existing - prevents anchoring to suboptimal structure

  • INVEST validation: Validate every Story against INVEST criteria

  • Size enforcement: 3-5 AC, 6-20 hours

  • Avoid over-decomposition: <3 AC, <6 hours → Merge Stories

User Interaction:

  • Epic extraction: Try to extract all planning info from Epic in Phase 1 Step 2 before asking user

  • Frontend Research: HTML forms/validation → AC scenarios (Phase 1 Step 3)

  • Fallback search: requirements.md, tech_stack.md if Epic incomplete (Phase 1 Step 4)

  • Only ask user for missing info after Epic extraction AND frontend AND fallback search fail

Delegation:

  • Orchestrator loads metadata only: ID, title, status (~50 tokens per Story)

  • Workers load full descriptions: 8 sections (~5,000 tokens per Story)

  • Token efficiency: 10 Stories × 50 tokens = 500 tokens (orchestrator) vs 10 Stories × 5,000 tokens = 50,000 tokens (workers load when needed)

Version: 4.0.0 (BREAKING: Decomposed to Orchestrator-Worker pattern. Phase 4a/4b removed, replaced with Phase 5a/5b delegation to ln-221-story-creator/ln-222-story-replanner. Orchestrator loads metadata only, workers load full descriptions for token efficiency. Progressive Loading now handled by ln-222-story-replanner, not orchestrator. Story execution logic moved to workers, orchestrator focuses on context assembly, standards research, planning, mode determination, delegation.) Last Updated: 2025-11-20

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