", run_in_background: true, prompt: <prompt from Step 3> ) ``` **Wave strategy**: - Wave 1: Tasks with no dependencies (they inform downstream tasks) - Wave 2: Tasks depending on Wave 1 - Wave 3+: Continue until all tasks covered - Max 5 agents per wave to avoid overwhelming Perplexity proxy **Wait for each wave to complete before launching the next.** --- ### Step 5: Collect and Write Results As each agent completes, save its research output: 1. Write agent output to a temp file: ```bash echo "<agent output>" > /tmp/research-task-<ID>.md ``` 2. Write research back to tasks.json: ```bash python3 ~/.claude/skills/expand-tasks/script.py write-research --task-id <ID> --research /tmp/research-task-<ID>.md ``` 3. After all tasks are written, verify: ```bash python3 ~/.claude/skills/expand-tasks/script.py status ``` **AI judgment**: Review each research result for quality. If a result is too thin (< 5 lines of useful content) or clearly failed, re-run that specific task's research. --- ## Research Agent Prompt Pattern The `gen-prompt` command generates prompts that follow the research-before-coding pattern: 1. Agent receives task context (title, description, dependencies, subtasks) 2. Agent runs `perplexity_batch` or `mcp__perplexity-api-free__search` with 3-5 targeted queries 3. Agent distills results into structured summary 4. Summary returns to main context (~25-40 lines per task) **Critical**: Research agents must NEVER use WebSearch or WebFetch. Perplexity MCP only. --- ## Error Handling | Error | Action | |-------|--------| | Perplexity proxy down | Exit skill, tell user to start proxy | | Agent returns empty/failed | Re-run that specific task with different queries | | tasks.json not found | Exit skill, tell user to run /prd-taskmaster first | | Task already expanded | Skip silently unless user forces re-expansion | | Agent timeout | Mark task as failed, continue with others | --- ## Output After all tasks are expanded, the skill reports: - Total tasks expanded - Any failures that need retry - Next recommended action (usually: begin implementation) --- ## Integration with prd-taskmaster This skill fits between Step 8 (Parse & Expand Tasks) and Step 11 (Choose Next Action) of the prd-taskmaster workflow. After PRD is parsed into tasks but before execution begins. ``` /prd-taskmaster → generates PRD → parses into tasks ↓ /expand-tasks → researches each task → writes findings back ↓ Implementation begins (with research context in each task) ``` --- ## Tips - Run after PRD generation but before any implementation - Research results are stored in `research_notes` field of each task in tasks.json - Re-running on already-expanded tasks is safe (will skip unless forced) - For very large task lists (20+), consider expanding in dependency order to save context - Each research agent costs ~30s of Perplexity time; 15 tasks ≈ 3 waves ≈ 2-3 minutes total --- > Converted and distributed by [TomeVault](https://tomevault.io/claim/anombyte93) — claim your Tome and manage your conversions. <!-- tomevault:4.0:skill

# Anombyte93 Prd Taskmaster Expand Tasks > Expand Tasks with Research v1.0 - Skill: `tomevault-io/anombyte93-prd-taskmaster-expand-tasks` (Agent Skill, multi-file: 2 files) - Install (CLI): `npx skillmds@latest add tomevault-io/anombyte93-prd-taskmaster-expand-tasks` - Raw SKILL.md: https://api.skillmd.com/api/skills/tomevault-io/anombyte93-prd-taskmaster-expand-tasks/raw - Safety review: pending (external: skill-scanner PASS, skillspector PASS) - Works with: Claude Code, Claude.ai, OpenAI Codex - Category: Product & Planning - Author: tomevault-io (https://skillmd.com/u/tomevault-io) - Updated: 2026-09-17 - Page: https://skillmd.com/skills/tomevault-io/anombyte93-prd-taskmaster-expand-tasks --- # Expand Tasks with Research v1.0 Expands TaskMaster tasks with Perplexity research before coding begins. Deterministic operations handled by `script.py`; AI handles judgment. **Script location**: `~/.claude/skills/expand-tasks/script.py` **Part of**: prd-taskmaster toolkit **Depends on**: research-before-coding skill (pattern), Perplexity MCP proxy ## When to Use Activate when user says: expand tasks, research tasks, research before coding for all, expand subtasks. Do NOT activate for: single task research (use /research-before-coding), PRD generation (use /prd-taskmaster). ## Prerequisites - TaskMaster tasks.json must exist (run /prd-taskmaster first) - Perplexity proxy must be running at localhost:8765 - At least 1 task in tasks.json --- ## Workflow (5 Steps) ### Step 1: Preflight ```bash python3 ~/.claude/skills/expand-tasks/script.py read-tasks ``` Returns JSON: `total`, `expanded`, `pending_expansion`, `tasks[]`. **If `pending_expansion` is 0**: Report all tasks already expanded. Exit skill. **If Perplexity is down**: Check health first: ```bash curl -sf http://localhost:8765/health ``` If down, tell user to start it and exit. --- ### Step 2: Choose Scope Use AskUserQuestion: - **All tasks** (default): Expand every task that hasn't been researched yet - **Specific tasks**: User provides task IDs (comma-separated) - **By dependency level**: Expand tasks with no dependencies first, then next wave **AI judgment**: Recommend "All tasks" for initial expansion, "By dependency level" for incremental work. --- ### Step 3: Generate Research Prompts For each task to expand: ```bash python3 ~/.claude/skills/expand-tasks/script.py gen-prompt --task-id ``` Returns JSON with `prompt` field containing the full research agent prompt. **AI judgment**: Review the auto-generated prompt. Customize research questions if the task needs domain-specific queries. Add project context from the PRD or session-context files if relevant. --- ### Step 4: Launch Parallel Research Agents Launch research agents in parallel waves. Each wave = up to 5 concurrent agents. **For each task**, spawn a Task agent: ``` Task( subagent_type: "general-purpose", model: "sonnet", description: "Research Task : ", run_in_background: true, prompt: <prompt from Step 3> ) ``` **Wave strategy**: - Wave 1: Tasks with no dependencies (they inform downstream tasks) - Wave 2: Tasks depending on Wave 1 - Wave 3+: Continue until all tasks covered - Max 5 agents per wave to avoid overwhelming Perplexity proxy **Wait for each wave to complete before launching the next.** --- ### Step 5: Collect and Write Results As each agent completes, save its research output: 1. Write agent output to a temp file: ```bash echo "<agent output>" > /tmp/research-task-<ID>.md ``` 2. Write research back to tasks.json: ```bash python3 ~/.claude/skills/expand-tasks/script.py write-research --task-id <ID> --research /tmp/research-task-<ID>.md ``` 3. After all tasks are written, verify: ```bash python3 ~/.claude/skills/expand-tasks/script.py status ``` **AI judgment**: Review each research result for quality. If a result is too thin (< 5 lines of useful content) or clearly failed, re-run that specific task's research. --- ## Research Agent Prompt Pattern The `gen-prompt` command generates prompts that follow the research-before-coding pattern: 1. Agent receives task context (title, description, dependencies, subtasks) 2. Agent runs `perplexity_batch` or `mcp__perplexity-api-free__search` with 3-5 targeted queries 3. Agent distills results into structured summary 4. Summary returns to main context (~25-40 lines per task) **Critical**: Research agents must NEVER use WebSearch or WebFetch. Perplexity MCP only. --- ## Error Handling | Error | Action | |-------|--------| | Perplexity proxy down | Exit skill, tell user to start proxy | | Agent returns empty/failed | Re-run that specific task with different queries | | tasks.json not found | Exit skill, tell user to run /prd-taskmaster first | | Task already expanded | Skip silently unless user forces re-expansion | | Agent timeout | Mark task as failed, continue with others | --- ## Output After all tasks are expanded, the skill reports: - Total tasks expanded - Any failures that need retry - Next recommended action (usually: begin implementation) --- ## Integration with prd-taskmaster This skill fits between Step 8 (Parse & Expand Tasks) and Step 11 (Choose Next Action) of the prd-taskmaster workflow. After PRD is parsed into tasks but before execution begins. ``` /prd-taskmaster → generates PRD → parses into tasks ↓ /expand-tasks → researches each task → writes findings back ↓ Implementation begins (with research context in each task) ``` --- ## Tips - Run after PRD generation but before any implementation - Research results are stored in `research_notes` field of each task in tasks.json - Re-running on already-expanded tasks is safe (will skip unless forced) - For very large task lists (20+), consider expanding in dependency order to save context - Each research agent costs ~30s of Perplexity time; 15 tasks ≈ 3 waves ≈ 2-3 minutes total --- > Converted and distributed by [TomeVault](https://tomevault.io/claim/anombyte93) — claim your Tome and manage your conversions.