Ensure accessibility in UI components including semantic HTML, ARIA attributes, keyboard navigation, and WCAG 2.2 AA compliance.
日本語の概要は準備中です。原文の説明を表示しています。
Creates structured plans from requirements. Generates comprehensive plans with steps, dependencies, risks, and success criteria. Coordinates with specialist agents for planning input and validates plan completeness. Uses template-renderer for formatted output.
インストールする前に、エージェントに与えられる指示の中身を確認できます。
Before creating a new plan, gather context from recent work to avoid duplication and build on prior decisions:
git log --oneline -5 to see what was recently shippedTaskList() to check for completed tasks with relevant metadata.claude/context/memory/decisions.md for architectural choices that constrain this plan.claude/context/memory/issues.md for known blockers or workaroundsUse this context to:
Parse user requirements:
Request planning input from relevant agents:
Create plan following this EXECUTABLE structure:
# Plan: [Title]
## Executive Summary
[2-3 sentence overview]
## Objectives
- [Objective 1]
- [Objective 2]
## Phases
### Phase N: [Phase Title]
**Dependencies**: [Phase numbers or 'None']
**Parallel OK**: [Yes/No - can tasks run concurrently?]
#### Tasks
- [ ] **N.1** [Task description] (~X min)
- **Command**: `actual shell command here`
- **Verify**: `command to verify success`
- **Rollback**: `command to undo if needed`
- [ ] **N.2** [Task description] (~X min) [⚡ parallel OK]
- **Command**: `...`
- **Verify**: `...`
#### Phase N Error Handling
If any task fails:
1. Run rollback commands for completed tasks (reverse order)
2. Document error: `echo "Phase N failed: [error]" >> .claude/context/memory/issues.md`
3. Do NOT proceed to Phase N+1
#### Phase N Verification Gate
```bash
# All must pass before proceeding
[verification commands]
```
| Risk | Impact | Mitigation | Rollback |
|---|---|---|---|
| [Risk] | [H/M/L] | [Strategy] | [Command] |
| Phase | Tasks | Est. Time | Parallel? |
|---|---|---|---|
| 1 | 5 | 30 min | Partial |
| 2 | 3 | 20 min | No |
### The Executable Task Format (MANDATORY)
Every task MUST include:
1. **Checkbox** - `- [ ]` for progress tracking
2. **ID** - `N.M` format for reference
3. **Time estimate** - `(~X min)`
4. **Command** - Actual executable command
5. **Verify** - Command to confirm success
6. **Rollback** - Command to undo (if applicable)
7. **Parallel marker** - `[⚡ parallel OK]` if can run concurrently
**Enhanced task format with structured completion fields** (verify/done/files are OPTIONAL — omit for backward compatibility):
```markdown
- [ ] **N.1** [Task description] (~X min)
- **Command**: `actual shell command here`
- **Verify**: `pnpm test -- --grep "pattern"` (command proving task is done)
- **Done**: [measurable criteria for "done" — e.g. "All tests pass, lint clean, file exists"]
- **Files**: [`path/to/file1`, `path/to/file2`] (files this task creates or modifies)
- **Rollback**: `command to undo if needed`
```
> **Schema**: Full task structure is documented in `.claude/schemas/plan-format.schema.json`.
> The `verify`, `done`, and `files` fields are optional — existing plans without them remain valid.
### Guidelines
- Define clear objectives
- Break down into phases (<=7 phases total)
- Each phase has <=7 tasks
- Every task has executable commands
- Include verification gates between phases
- For **HIGH** or **EPIC** complexity tasks, invoke `discuss-phase` skill BEFORE generating the plan to surface ambiguities and resolve scope, architecture, and acceptance criteria questions with the user
### Step 4: Assess Risks
Identify risks and mitigation:
- Technical risks
- Resource risks
- Timeline risks
- Dependency risks
- Mitigation strategies
### Step 5: Validate Plan
Validate plan completeness:
- All requirements addressed
- Dependencies mapped
- Success criteria defined
- Risks identified
- Plan is feasible
### Step 6: Generate Artifacts
Create plan artifacts using the template-renderer skill:
**Using Template-Renderer**:
After creating plan data structure, invoke template-renderer to generate formatted output:
```javascript
// Map plan data to template tokens
const planTokens = {
PLAN_TITLE: plan.title,
DATE: new Date().toISOString().split('T')[0],
FRAMEWORK_VERSION: 'Agent-Studio v3.1.0',
STATUS: plan.status || 'Phase 0 - Research',
EXECUTIVE_SUMMARY: plan.executiveSummary,
TOTAL_TASKS: `${plan.totalTasks} atomic tasks`,
FEATURES_COUNT: plan.features.length,
ESTIMATED_TIME: plan.estimatedTime,
STRATEGY: plan.strategy,
KEY_DELIVERABLES_LIST: plan.keyDeliverables.map(d => `- ${d}`).join('\n'),
// Phase-specific tokens
PHASE_0_PURPOSE: plan.phases[0].purpose,
PHASE_0_DURATION: plan.phases[0].duration,
PHASE_1_NAME: plan.phases[1].name,
PHASE_1_PURPOSE: plan.phases[1].purpose,
PHASE_1_DURATION: plan.phases[1].duration,
DEPENDENCIES: plan.phases[1].dependencies,
PARALLEL_OK: plan.phases[1].parallelOk ? 'Yes' : 'No',
VERIFICATION_COMMANDS: plan.phases[1].verificationCommands,
// Add more phase tokens as needed
};
// Invoke template-renderer skill
Skill({
skill: 'template-renderer',
args: {
templateName: 'plan-template',
outputPath: `.claude/context/plans/${planId}.md`,
tokens: planTokens
}
});
```
**Output Locations**:
- Plan markdown (from template): `.claude/context/plans/<plan-id>.md`
- Plan JSON (structured data): `.claude/context/plans/<plan-id>.json`
- Plan summary (for quick reference)
</execution_process>
<plan_types>
**Feature Development Plan**:
- Objectives: Feature goals
- Steps: Analysis -> Design -> Implementation -> Testing
- Agents: Analyst -> PM -> Architect -> Developer -> QA
**Refactoring Plan**:
- Objectives: Code quality goals
- Steps: Analysis -> Planning -> Implementation -> Validation
- Agents: Code Reviewer -> Refactoring Specialist -> Developer -> QA
**Migration Plan**:
- Objectives: Migration goals
- Steps: Analysis -> Planning -> Execution -> Validation
- Agents: Architect -> Legacy Modernizer -> Developer -> QA
**Architecture Plan**:
- Objectives: Architecture goals
- Steps: Analysis -> Design -> Validation -> Documentation
- Agents: Architect -> Database Architect -> Security Architect -> Technical Writer
</plan_types>
<integration>
**Integration with Planner Agent**:
Planner agent uses this skill to:
- Generate plans from requirements
- Coordinate specialist input
- Validate plan completeness
- Track plan execution
</integration>
<best_practices>
1. **Coordinate Early**: Get specialist input before finalizing plan
2. **Keep Steps Focused**: <=7 steps per plan section
3. **Map Dependencies**: Clearly identify prerequisites
4. **Assess Risks**: Identify and mitigate risks proactively
5. **Validate Thoroughly**: Ensure plan is complete and feasible
</best_practices>
</instructions>
<examples>
<formatting_example>
**Example Plan Output**
**Command**: "Generate plan for user authentication feature"
**Generated Plan**:
```markdown
# Plan: User Authentication Feature
## Executive Summary
Add JWT-based authentication with login/logout endpoints. Includes password hashing, session management, and security testing.
## Objectives
- Implement JWT-based authentication
- Support login, logout, and session management
- Provide secure password handling
## Phases
### Phase 1: Setup & Design
**Dependencies**: None
**Parallel OK**: Partial
#### Tasks
- [ ] **1.1** Create feature branch (~2 min)
- **Command**: `git checkout -b feature/auth`
- **Verify**: `git branch --show-current | grep feature/auth`
- [ ] **1.2** Create auth module directory (~1 min) [⚡ parallel OK]
- **Command**: `mkdir -p src/auth`
- **Verify**: `ls -d src/auth`
- [ ] **1.3** Design auth architecture (~15 min)
- **Command**: `Task({ task_id: 'task-1', agent: "architect", prompt: "Design JWT auth..." })`
- **Verify**: `ls .claude/context/artifacts/auth-design.md`
#### Phase 1 Verification Gate
```bash
git branch --show-current | grep feature/auth && ls src/auth && ls .claude/context/artifacts/auth-design.md
Dependencies: Phase 1 Parallel OK: No (sequential TDD)
2.1 Write auth endpoint tests (~10 min)
Task({ task_id: 'task-2', agent: "developer", prompt: "TDD: Write failing tests for /login endpoint" })npm test -- --grep "login" 2>&1 | grep -E "failing|FAIL"git checkout -- src/auth/__tests__/2.2 Implement login endpoint (~15 min)
Task({ task_id: 'task-3', agent: "developer", prompt: "Implement login to pass tests" })npm test -- --grep "login" 2>&1 | grep -E "passing|PASS"2.3 Implement logout endpoint (~10 min)
Task({ task_id: 'task-4', agent: "developer", prompt: "TDD: logout endpoint" })npm test -- --grep "logout" 2>&1 | grep -E "passing|PASS"If any task fails:
git stash && git checkout -- src/auth/echo "Phase 2 failed: $(date)" >> .claude/context/memory/issues.mdnpm test -- --grep "auth" && echo "All auth tests passing"
Dependencies: Phase 2 Parallel OK: Yes
3.1 Security audit (~20 min) [⚡ parallel OK]
Task({ task_id: 'task-5', agent: "security-architect", prompt: "Audit auth implementation" })ls .claude/context/reports/security/security-audit.md3.2 Run security tests (~5 min) [⚡ parallel OK]
npm run test:securityecho $? (exit code 0)| Risk | Impact | Mitigation | Rollback |
|---|---|---|---|
| JWT secret exposure | High | Use env vars | Rotate secret immediately |
| SQL injection | High | Parameterized queries | git revert HEAD |
| Phase | Tasks | Est. Time | Parallel? |
|---|---|---|---|
| 1 | 3 | 18 min | Partial |
| 2 | 3 | 35 min | No |
| 3 | 2 | 25 min | Yes |
| Total | 8 | ~78 min |
**After plan generation**, invoke template-renderer:
```javascript
// Map plan data to tokens
const tokens = {
PLAN_TITLE: 'User Authentication Feature',
DATE: '2026-01-28',
FRAMEWORK_VERSION: 'Agent-Studio v3.1.0',
STATUS: 'Phase 0 - Research',
EXECUTIVE_SUMMARY: 'Add JWT-based authentication with login/logout endpoints...',
TOTAL_TASKS: '8 atomic tasks',
FEATURES_COUNT: '1',
ESTIMATED_TIME: '~78 minutes',
STRATEGY: 'Foundation-first → Core features → Security review',
KEY_DELIVERABLES_LIST: '- Authentication module\n- Login/logout endpoints\n- Security audit',
PHASE_1_NAME: 'Setup & Design',
PHASE_1_PURPOSE: 'Create feature branch and design architecture',
PHASE_1_DURATION: '18 minutes',
DEPENDENCIES: 'None',
PARALLEL_OK: 'Partial',
VERIFICATION_COMMANDS: 'git branch --show-current | grep feature/auth && ls src/auth',
};
// Render plan using template
Skill({
skill: 'template-renderer',
args: {
templateName: 'plan-template',
outputPath: '.claude/context/plans/user-auth-plan.md',
tokens: tokens
}
});
</formatting_example> </examples>
Every plan emitted by plan-generator MUST contain exactly these 6 top-level sections in this exact order:
## Problem — why this work matters; the pain point or gap being addressed## Decision — what is being done; the chosen approach (not the steps, just the choice)## Scope — what is IN scope; explicitly list what is OUT of scope## Risks — what could go wrong; include mitigations and rollback commands## Steps — ordered implementation checklist using - [ ] task format## Done Criteria — acceptance criteria; objective conditions that prove the work is completeRules:
Why fixed order? AI-generated plans frequently reorder sections or omit scope/risks, causing incomplete execution. Fixed ordering enables automated validation and catches AI-slopped plans before they reach execution.
Every plan MUST include this as the LAST task, blocked by all other tasks:
Task: "Final: Self-review + token report"
Example TaskCreate for planners to emit:
TaskCreate({
subject: "Final: Self-review + token report",
description: "1. Run: npx ccusage@latest --model --today — display token costs\n2. Self-review all deliverables: Can I improve this?\n3. If improvements found, queue reflection-spawn-request\n4. NEVER dismiss failures as pre-existing\n5. TaskUpdate(completed, { metadata: { isFinalTask: true, pipelineComplete: true } })",
activeForm: "Running self-review and token report"
})
EVERY TASK MUST HAVE AN EXECUTABLE COMMAND
A task without a command is not a task - it's a wish.
| Anti-Pattern | Problem | Fix |
|---|---|---|
| "Install X" without command | Not executable | Add: cp -r source dest |
| "Verify Y works" | Vague | Add: npm test | grep PASS |
| "Update Z" | What file? What change? | Add exact Edit or sed command |
| No time estimates | Can't track progress | Add (~X min) to every task |
| No rollback | Can't recover from failure | Add rollback command |
Before finalizing any plan, verify:
verify command that proves completion objectively?done criteria that is measurable and unambiguous?This skill uses the template-renderer skill to generate formatted plans:
Integration Flow:
.claude/context/plans/Required Tokens (for plan-template):
PLAN_TITLE, DATE, FRAMEWORK_VERSION, STATUSEXECUTIVE_SUMMARY, TOTAL_TASKS, ESTIMATED_TIME, STRATEGYPHASE_N_NAME, PHASE_N_PURPOSE, DEPENDENCIES, PARALLEL_OKVERIFICATION_COMMANDSSee .claude/templates/plan-template.md for complete token list.
template-renderer - Renders plan-template with token replacementwriting-plans - Bite-sized task plans with complete code for implementationdiscuss-phase - Requirement disambiguation for HIGH/EPIC tasks before planningBefore starting:
cat .claude/context/memory/learnings.md
After completing:
.claude/context/memory/learnings.md.claude/context/memory/issues.md.claude/context/memory/decisions.mdASSUME INTERRUPTION: Your context may reset. If it's not in memory, it didn't happen.
まだレビューはありません。使ってみた感想をお寄せください。
概要と使いどころ
Ensure accessibility in UI components including semantic HTML, ARIA attributes, keyboard navigation, and WCAG 2.2 AA compliance.
日本語の概要は準備中です。原文の説明を表示しています。
Use when you want to improve response quality through meta-cognitive reasoning. Applies 15+ reasoning methods to reconsider and refine initial outputs.
日本語の概要は準備中です。原文の説明を表示しています。
N-round opposing-stance debates for trade-off analysis. Assigns pro/con roles to agents, runs structured debate rounds with quality scoring, and produces a moderator synthesis with confidence-rated recommendation. Generalizable to architecture, technology, security, and design decisions.
日本語の概要は準備中です。原文の説明を表示しています。
Force adversarial code review stance that eliminates confirmation bias — reviewer must find issues or re-analyze
日本語の概要は準備中です。原文の説明を表示しています。
Creates specialized AI agents on-demand when no existing agent matches a request. Use when the Router cannot find a suitable agent for a task. Enables self-evolution by generating persistent agents.
日本語の概要は準備中です。原文の説明を表示しています。
LLM-as-judge evaluation framework with 5-dimension rubric (accuracy, groundedness, coherence, completeness, helpfulness) for scoring AI-generated content quality with weighted composite scores and evidence citations
日本語の概要は準備中です。原文の説明を表示しています。