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maestrobrainstorming
// Use before any creative work - creating features, building components, adding functionality, or modifying behavior. Explores user intent, requirements and design before implementation.
// Use before any creative work - creating features, building components, adding functionality, or modifying behavior. Explores user intent, requirements and design before implementation.
Use when bootstrapping, updating, or reviewing AGENTS.md — teaches what makes effective agent memory, how to structure sections, signal vs noise filtering, and when to prune stale entries
Use when encountering any bug, test failure, or unexpected behavior, before proposing fixes
Deep discovery and specification for ambitious features. Full BMAD-inspired interview with classification, vision, journeys, domain analysis, and FR synthesis. Same output contract (spec.md + plan.md) as a standard feature but far richer. Use for multi-component systems, regulated domains, or unclear requirements.
Use when facing 2+ independent tasks that can be worked on without shared state or sequential dependencies
Use when working with Docker containers — debugging container failures, writing Dockerfiles, docker-compose for integration tests, image optimization, or deploying containerized applications
Execute feature tasks following TDD workflow. Single-agent by default, --team for parallel Agent Teams, Sub Agent Parallels. Use when ready to implement a planned feature.
| name | maestro:brainstorming |
| description | Use before any creative work - creating features, building components, adding functionality, or modifying behavior. Explores user intent, requirements and design before implementation. |
| stage | ["discovery","research"] |
| audience | orchestrator |
Help turn ideas into fully formed designs and specs through natural collaborative dialogue.
Start by understanding the current project context, then run the structured interview in reference/interview-guide.md to refine the idea. Once you understand what you're building, present the design in small sections (200-300 words), checking after each section whether it looks right so far.
reference/interview-guide.md and follow its question sequenceBrainstorming insights are valuable but volatile -- they exist only in the conversation context. Persist them before moving on.
What to persist:
How to persist:
# Create the feature first (if it doesn't exist yet)
maestro_feature_create({ name: "<feature-name>", description: "<one-line>" })
# Save the brainstorming output as feature memory
maestro_memory_write({
key: "brainstorm-summary",
content: "<validated design summary>",
feature: "<feature-name>"
})
# Save key decisions separately for easy reference
maestro_memory_write({
key: "design-decisions",
content: "<decisions and rationale>",
feature: "<feature-name>"
})
When to persist: After the user validates the design in Phase 3, before chaining into planning. Do not wait until the end of the conversation -- persist as soon as the design stabilizes.
Brainstorming produces understanding, not documents. The validated design feeds directly into the maestro workflow -- never into standalone files under docs/.
When the design is validated, chain forward:
maestro_feature_create -- registers the feature in the maestro trackermaestro_memory_write with the brainstorming output -- persists where the planner can reference itmaestro_plan_write -- write the plan directly from the brainstorming outputmaestro:design or maestro:new-feature for deeper discovery and structured spec generationThe brainstorming output becomes the ## Discovery section that maestro_plan_write requires. Do not write design docs to docs/plans/ -- that bypasses the maestro workflow and leaves the design disconnected from execution.
Is the scope clear and small (1-3 tasks)?
--> YES: maestro_plan_write directly
--> NO:
Is a formal spec needed (multiple stakeholders, complex requirements)?
--> YES: maestro:design (full 16-step process)
--> NO: maestro:new-feature (interview + spec + plan)
A good brainstorming session produces:
Example summary:
## Design: Rate Limiting for REST API
**Problem**: No rate limiting means a single abusive client can degrade
service for all users. We had an incident on 2026-03-01 where one client
sent 10K req/sec and caused 503s for everyone.
**Approach**: Sliding window counter with Redis backend.
- Rejected token bucket (harder to implement distributed).
- Rejected fixed window (allows burst at window boundary).
**Scope**: Per-user limits on authenticated endpoints only.
**Non-goals**: IP-based limiting, per-endpoint limits, admin dashboard.
**Key decisions**:
- Fail open (allow request) if Redis is unavailable
- Return Retry-After header with 429 responses
- Default 100 req/min, configurable per user tier
maestro_feature_create -- Create a feature to work on (do this during brainstorming)maestro_memory_write -- Persist brainstorming discoveriesmaestro:brainstorming -- You are here. Explore ideas before planningmaestro:design -- Deep discovery for ambitious features (next step for complex work)maestro:new-feature -- Interview + spec + plan (next step for medium complexity)maestro_plan_write -- Write the plan directly (next step for simple work)maestro_plan_approve -- Approve the plan for executionmaestro:implement -- Execute the implementation