Claude-Code-Workflow/.claude/commands/issue/plan.md

---
name: plan
description: Batch plan issue resolution using issue-plan-agent (explore + plan closed-loop)
argument-hint: "--all-pending <issue-id>[,<issue-id>,...] [--batch-size 3] "
allowed-tools: TodoWrite(*), Task(*), SlashCommand(*), AskUserQuestion(*), Bash(*), Read(*), Write(*)
---

# Issue Plan Command (/issue:plan)

## Overview

Unified planning command using **issue-plan-agent** that combines exploration and planning into a single closed-loop workflow.

**Behavior:**
- Single solution per issue → auto-bind
- Multiple solutions → return for user selection
- Agent handles file generation

## Core Guidelines

**⚠️ Data Access Principle**: Issues and solutions files can grow very large. To avoid context overflow:

| Operation | Correct | Incorrect |
|-----------|---------|-----------|
| List issues (brief) | `ccw issue list --status pending --brief` | `Read('issues.jsonl')` |
| Read issue details | `ccw issue status <id> --json` | `Read('issues.jsonl')` |
| Update status | `ccw issue update <id> --status ...` | Direct file edit |
| Bind solution | `ccw issue bind <id> <sol-id>` | Direct file edit |

**Output Options**:
- `--brief`: JSON with minimal fields (id, title, status, priority, tags)
- `--json`: Full JSON (agent use only)

**Orchestration vs Execution**:
- **Command (orchestrator)**: Use `--brief` for minimal context
- **Agent (executor)**: Fetch full details → `ccw issue status <id> --json`

**ALWAYS** use CLI commands for CRUD operations. **NEVER** read entire `issues.jsonl` or `solutions/*.jsonl` directly. 

## Usage

```bash
/issue:plan [<issue-id>[,<issue-id>,...]] [FLAGS]

# Examples
/issue:plan                           # Default: --all-pending
/issue:plan GH-123                    # Single issue
/issue:plan GH-123,GH-124,GH-125      # Batch (up to 3)
/issue:plan --all-pending             # All pending issues (explicit)

# Flags
--batch-size <n>      Max issues per agent batch (default: 3)
```

## Execution Process

```
Phase 1: Issue Loading
   ├─ Parse input (single, comma-separated, or --all-pending)
   ├─ Fetch issue metadata (ID, title, tags)
   ├─ Validate issues exist (create if needed)
   └─ Group by similarity (shared tags or title keywords, max 3 per batch)

Phase 2: Unified Explore + Plan (issue-plan-agent)
   ├─ Launch issue-plan-agent per batch
   ├─ Agent performs:
   │   ├─ ACE semantic search for each issue
   │   ├─ Codebase exploration (files, patterns, dependencies)
   │   ├─ Solution generation with task breakdown
   │   └─ Conflict detection across issues
   └─ Output: solution JSON per issue

Phase 3: Solution Registration & Binding
   ├─ Append solutions to solutions/{issue-id}.jsonl
   ├─ Single solution per issue → auto-bind
   ├─ Multiple candidates → AskUserQuestion to select
   └─ Update issues.jsonl with bound_solution_id

Phase 4: Summary
   ├─ Display bound solutions
   ├─ Show task counts per issue
   └─ Display next steps (/issue:queue)
```

## Implementation

### Phase 1: Issue Loading (Brief Info Only)

```javascript
const batchSize = flags.batchSize || 3;
let issues = [];  // {id, title, tags} - brief info for grouping only

// Default to --all-pending if no input provided
const useAllPending = flags.allPending || !userInput || userInput.trim() === '';

if (useAllPending) {
  // Get pending issues with brief metadata via CLI
  const result = Bash(`ccw issue list --status pending,registered --json`).trim();
  const parsed = result ? JSON.parse(result) : [];
  issues = parsed.map(i => ({ id: i.id, title: i.title || '', tags: i.tags || [] }));

  if (issues.length === 0) {
    console.log('No pending issues found.');
    return;
  }
  console.log(`Found ${issues.length} pending issues`);
} else {
  // Parse comma-separated issue IDs, fetch brief metadata
  const ids = userInput.includes(',')
    ? userInput.split(',').map(s => s.trim())
    : [userInput.trim()];

  for (const id of ids) {
    Bash(`ccw issue init ${id} --title "Issue ${id}" 2>/dev/null || true`);
    const info = Bash(`ccw issue status ${id} --json`).trim();
    const parsed = info ? JSON.parse(info) : {};
    issues.push({ id, title: parsed.title || '', tags: parsed.tags || [] });
  }
}
// Note: Agent fetches full issue content via `ccw issue status <id> --json`

// Semantic grouping via Gemini CLI (max 4 issues per group)
async function groupBySimilarityGemini(issues) {
  const issueSummaries = issues.map(i => ({
    id: i.id, title: i.title, tags: i.tags
  }));

  const prompt = `
PURPOSE: Group similar issues by semantic similarity for batch processing; maximize within-group coherence; max 4 issues per group
TASK: • Analyze issue titles/tags semantically • Identify functional/architectural clusters • Assign each issue to one group
MODE: analysis
CONTEXT: Issue metadata only
EXPECTED: JSON with groups array, each containing max 4 issue_ids, theme, rationale
CONSTRAINTS: Each issue in exactly one group | Max 4 issues per group | Balance group sizes

INPUT:
${JSON.stringify(issueSummaries, null, 2)}

OUTPUT FORMAT:
{"groups":[{"group_id":1,"theme":"...","issue_ids":["..."],"rationale":"..."}],"ungrouped":[]}
`;

  const taskId = Bash({
    command: `ccw cli -p "${prompt}" --tool gemini --mode analysis`,
    run_in_background: true, timeout: 600000
  });
  const output = TaskOutput({ task_id: taskId, block: true });

  // Extract JSON from potential markdown code blocks
  function extractJsonFromMarkdown(text) {
    const jsonMatch = text.match(/```json\s*\n([\s\S]*?)\n```/) ||
                      text.match(/```\s*\n([\s\S]*?)\n```/);
    return jsonMatch ? jsonMatch[1] : text;
  }

  const result = JSON.parse(extractJsonFromMarkdown(output));
  return result.groups.map(g => g.issue_ids.map(id => issues.find(i => i.id === id)));
}

const batches = await groupBySimilarityGemini(issues);
console.log(`Processing ${issues.length} issues in ${batches.length} batch(es) (max 4 issues/agent)`);

TodoWrite({
  todos: batches.map((_, i) => ({
    content: `Plan batch ${i+1}`,
    status: 'pending',
    activeForm: `Planning batch ${i+1}`
  }))
});
```

### Phase 2: Unified Explore + Plan (issue-plan-agent) - PARALLEL

```javascript
Bash(`mkdir -p .workflow/issues/solutions`);
const pendingSelections = [];  // Collect multi-solution issues for user selection
const agentResults = [];       // Collect all agent results for conflict aggregation

// Build prompts for all batches
const agentTasks = batches.map((batch, batchIndex) => {
  const issueList = batch.map(i => `- ${i.id}: ${i.title}${i.tags.length ? ` [${i.tags.join(', ')}]` : ''}`).join('\n');
  const batchIds = batch.map(i => i.id);

  const issuePrompt = `
## Plan Issues

**Issues** (grouped by similarity):
${issueList}

**Project Root**: ${process.cwd()}

### Project Context (MANDATORY)
1. Read: .workflow/project-tech.json (technology stack, architecture)
2. Read: .workflow/project-guidelines.json (constraints and conventions)

### Workflow
1. Fetch issue details: ccw issue status <id> --json
2. Load project context files
3. Explore codebase (ACE semantic search)
4. Plan solution with tasks (schema: solution-schema.json)
5. **If github_url exists**: Add final task to comment on GitHub issue
6. Write solution to: .workflow/issues/solutions/{issue-id}.jsonl
7. Single solution → auto-bind; Multiple → return for selection

### Rules
- Solution ID format: SOL-{issue-id}-{uid} (uid: 4 random alphanumeric chars, e.g., a7x9)
- Single solution per issue → auto-bind via ccw issue bind
- Multiple solutions → register only, return pending_selection
- Tasks must have quantified acceptance.criteria

### Return Summary
{"bound":[{"issue_id":"...","solution_id":"...","task_count":N}],"pending_selection":[{"issue_id":"...","solutions":[{"id":"...","description":"...","task_count":N}]}]}
`;

  return { batchIndex, batchIds, issuePrompt, batch };
});

// Launch agents in parallel (max 10 concurrent)
const MAX_PARALLEL = 10;
for (let i = 0; i < agentTasks.length; i += MAX_PARALLEL) {
  const chunk = agentTasks.slice(i, i + MAX_PARALLEL);
  const taskIds = [];

  // Launch chunk in parallel
  for (const { batchIndex, batchIds, issuePrompt, batch } of chunk) {
    updateTodo(`Plan batch ${batchIndex + 1}`, 'in_progress');
    const taskId = Task(
      subagent_type="issue-plan-agent",
      run_in_background=true,
      description=`Explore & plan ${batch.length} issues: ${batchIds.join(', ')}`,
      prompt=issuePrompt
    );
    taskIds.push({ taskId, batchIndex });
  }

  console.log(`Launched ${taskIds.length} agents (batch ${i/MAX_PARALLEL + 1}/${Math.ceil(agentTasks.length/MAX_PARALLEL)})...`);

  // Collect results from this chunk
  for (const { taskId, batchIndex } of taskIds) {
    const result = TaskOutput(task_id=taskId, block=true);

    // Extract JSON from potential markdown code blocks (agent may wrap in ```json...```)
    const jsonText = extractJsonFromMarkdown(result);
    let summary;
    try {
      summary = JSON.parse(jsonText);
    } catch (e) {
      console.log(`⚠ Batch ${batchIndex + 1}: Failed to parse agent result, skipping`);
      updateTodo(`Plan batch ${batchIndex + 1}`, 'completed');
      continue;
    }
    agentResults.push(summary);  // Store for Phase 3 conflict aggregation

    for (const item of summary.bound || []) {
      console.log(`✓ ${item.issue_id}: ${item.solution_id} (${item.task_count} tasks)`);
    }
    // Collect and notify pending selections
    for (const pending of summary.pending_selection || []) {
      console.log(`⏳ ${pending.issue_id}: ${pending.solutions.length} solutions → awaiting selection`);
      pendingSelections.push(pending);
    }
    if (summary.conflicts?.length > 0) {
      console.log(`⚠ Conflicts: ${summary.conflicts.length} detected (will resolve in Phase 3)`);
    }
    updateTodo(`Plan batch ${batchIndex + 1}`, 'completed');
  }
}
```

### Phase 3: Conflict Resolution & Solution Selection

**Conflict Handling:**
- Collect `conflicts` from all agent results
- Low/Medium severity → auto-resolve with `recommended_resolution`
- High severity → use `AskUserQuestion` to let user choose resolution

**Multi-Solution Selection:**
- If `pending_selection` contains issues with multiple solutions:
  - Use `AskUserQuestion` to present options (solution ID + task count + description)
  - Extract selected solution ID from user response
  - Verify solution file exists, recover from payload if missing
  - Bind selected solution via `ccw issue bind <issue-id> <solution-id>`

### Phase 4: Summary

```javascript
// Count planned issues via CLI
const planned = JSON.parse(Bash(`ccw issue list --status planned --brief`) || '[]');
const plannedCount = planned.length;

console.log(`
## Done: ${issues.length} issues → ${plannedCount} planned

Next: \`/issue:queue\` → \`/issue:execute\`
`);
```

## Error Handling

| Error | Resolution |
|-------|------------|
| Issue not found | Auto-create in issues.jsonl |
| ACE search fails | Agent falls back to ripgrep |
| No solutions generated | Display error, suggest manual planning |
| User cancels selection | Skip issue, continue with others |
| File conflicts | Agent detects and suggests resolution order |

## Bash Compatibility

**Avoid**: `$(cmd)`, `$var`, `for` loops — will be escaped incorrectly

**Use**: Simple commands + `&&` chains, quote comma params `"pending,registered"`

## Quality Checklist

Before completing, verify:

- [ ] All input issues have solutions in `solutions/{issue-id}.jsonl`
- [ ] Single solution issues are auto-bound (`bound_solution_id` set)
- [ ] Multi-solution issues returned in `pending_selection` for user choice
- [ ] Each solution has executable tasks with `modification_points`
- [ ] Task acceptance criteria are quantified (not vague)
- [ ] Conflicts detected and reported (if multiple issues touch same files)
- [ ] Issue status updated to `planned` after binding

## Related Commands

- `/issue:queue` - Form execution queue from bound solutions
- `ccw issue list` - List all issues
- `ccw issue status` - View issue and solution details