--- name: mastermind-research description: Mastermind research domain — market research, competitor analysis, user research, trend scanning. Spawns a Research Manager coordinating a mesh of researcher agents for comprehensive intelligence gathering. type: domain-skill default_mode: auto --- # Mastermind Research Domain This skill is invoked by `mastermind:master` or directly via `/mastermind:research`. --- ## Inputs - `brain_context`: BRAIN CONTEXT block (injected by master, or loaded standalone via mastermind-protocol/SKILL.md brain load) - `prompt`: the research question or intelligence goal - `project_name`: monotask space name - `board_id`: monotask board ID (set by master, or created standalone) - `mode`: auto | confirm --- ## Complexity Assessment Assess the prompt to determine execution mode: **Simple (direct execution):** Single-answer lookup or quick scan: - "What is the pricing model for Competitor X?" - "Find the current market size for SaaS tools in HR" → Use a single researcher agent. Skip manager delegation. **Complex (spawn Research Manager agent):** Any of these: - Full competitive landscape analysis - Market sizing with multiple data sources - User research synthesis across multiple interviews or signals - Trend analysis requiring cross-domain intelligence → Spawn Research Manager agent with full briefing. --- ## Standalone Execution (when called without master) If this skill is invoked directly (not by master): 1. Load brain context following mastermind-protocol/SKILL.md Brain Load Procedure (namespace: `research`) 2. Run intake from mastermind-intake/SKILL.md if prompt is vague 3. Follow mastermind-protocol/SKILL.md Monotask Space+Board Setup Procedure: ```bash project_name="${project_name:-$(basename "$PWD")}" space_id=$(monotask space list 2>/dev/null | awk -F' \| ' -v n="$project_name" '$2==n{print $1}' | head -1) [ -z "$space_id" ] && space_id=$(monotask space create "$project_name" 2>&1 | grep -oE '[0-9a-f]{8}-[0-9a-f]{4}-[0-9a-f]{4}-[0-9a-f]{4}-[0-9a-f]{12}') [ -z "$space_id" ] && { echo "ERROR: Could not find or create space '$project_name'"; exit 1; } board_id=$(monotask board create "research" --json | jq -r '.id // empty') [ -z "$board_id" ] && { echo "ERROR: Failed to create research board"; exit 1; } monotask space boards add "$space_id" "$board_id" >/dev/null 2>&1 || true todo_col=$(monotask column create "$board_id" "Todo" --json | jq -r '.id') doing_col=$(monotask column create "$board_id" "Doing" --json | jq -r '.id') done_col=$(monotask column create "$board_id" "Done" --json | jq -r '.id') ``` 4. Proceed with complexity assessment below 5. At end: follow mastermind-protocol/SKILL.md Brain Write Procedure (namespace: `research`) --- ## Complex Execution — Research Manager Agent Spawn a Research Manager agent via Task tool: ```javascript Task({ subagent_type: "researcher", description: `You are the Research Manager for project . CONTEXT: | Project: | Spawned by: mastermind:research BRAIN CONTEXT: YOUR BOARD: YOUR GOAL: STEP 1 — PLAN Decompose the research goal into parallel intelligence streams. For each stream, identify: - What specific question it answers - Which data sources to tap (web, docs, user signals, code, analytics) - Which specialist is best suited - How outputs from different streams combine into a final answer STEP 2 — CREATE TASKS For each research stream, create a monotask card on the project board. First look up column IDs and assign shell variables: ```bash columns=$(monotask column list "$BOARD_ID" --json) COL_TODO_ID=$(echo "$columns" | jq -r '.[] | select(.title == "Todo" or .title == "Backlog") | .id' | head -1) COL_DONE_ID=$(echo "$columns" | jq -r '.[] | select(.title == "Done") | .id' | head -1) ``` Then create the card: ```bash result=$(monotask card create "$BOARD_ID" "$COL_TODO_ID" "" --json) CARD_ID=$(echo "$result" | jq -r '.id // empty') monotask card set-description "$BOARD_ID" "$CARD_ID" "[specific research question this stream answers]" monotask card comment add "$BOARD_ID" "$CARD_ID" "CONTEXT: | Project: | Created by: Research Manager BRAIN MEMORY: [paste most relevant 3-5 brain context excerpts] SCOPE: [sources to consult, search queries to run, depth of analysis] CONSTRAINTS: [recency requirements, geographic scope, data reliability thresholds] SUCCESS CRITERIA: - [ ] [checkable item — e.g. \"top 5 competitors identified with pricing\"] AGENT: [researcher | Trend Researcher | UX Researcher | Analytics Reporter] SWARM: mesh 4 gossip DEPENDENCIES: [task IDs or \"none\"] OUTPUT FORMAT: unified output schema" ``` STEP 3 — EXECUTE Spawn one Task agent per research stream (mesh topology — findings cross-pollinate): - Web and market research: subagent_type "researcher" - Trend and signal analysis: subagent_type "Trend Researcher" - User behavior and UX signals: subagent_type "UX Researcher" - Data and metrics analysis: subagent_type "Analytics Reporter" Also run /mastermind:do --board to track execution. STEP 4 — COLLECT AND RETURN Synthesize all research streams into an intelligence report. Return to caller: domain: research status: complete | partial | blocked artifacts: - path: [research report if written to disk] type: report decisions: - what: [key findings and recommended actions] why: [evidence from research] confidence: [0.0-1.0] outcome: pending lessons: - what_worked: [which sources or methods yielded best signal] - what_didnt: [gaps or low-quality sources] next_actions: - [e.g. "run mastermind:idea to act on market insights"] - [e.g. "run mastermind:marketing with validated positioning"] board_url: monotask:///research run_id: `, run_in_background: true }) ``` --- ## Simple Execution For simple tasks (single researcher, single question): 1. Spawn one Task agent with the research question as a self-contained briefing 2. Collect output 3. Return unified output schema with `status: complete` --- ## Domain Swarm Defaults | Task Type | Agent | Swarm | |---|---|---| | Full competitive analysis | researcher + trend + UX | mesh 4 gossip balanced | | Market sizing | researcher | hierarchical 3 raft specialized | | Trend scan | Trend Researcher | single agent | | User research synthesis | UX Researcher | hierarchical 3 raft specialized | | Quick factual lookup | researcher | single agent |