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Metis — Brainstorm Turn

brainstorm_turn

Run a brainstorm turn to surface relevant ideas, notes, and questions from your library. Use steering modes like expand, focus, or challenge to guide the session.

Instructions

Run one turn of a brainstorm session, returning relevant context.

Call this at the start of a brainstorm and after each steering action.
The tool fetches relevant ideas, notes, questions, and library notes so
you (the AI) can surface connections the user may not have considered.

Steering modes:
  expand    — broaden; surface tangential connections
  focus     — narrow; find the most relevant threads
  challenge — find counter-arguments and weaknesses
  synthesize — identify themes; propose a unifying framework
  connect   — explicit cross-domain connections to library/literature

Args:
    topic:        The brainstorm topic or question.
    steering:     One of expand|focus|challenge|synthesize|connect.
    session_uuid: Pass the UUID from the previous turn to continue a session.
                  Omit to start a new session.
    turn_notes:   Optional free-text notes from the previous turn to log.

Returns JSON with: session_uuid, turn_number, context (ideas/notes/
questions/library), steering_prompts, and instructions for the AI.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
topicYes
steeringNoexpand
turn_notesNo
session_uuidNo

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault
resultYes
Behavior4/5

Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?

No annotations are provided, so the description carries the full burden. It discloses that the tool fetches relevant ideas, notes, questions, and library notes, lists five steering modes with their meanings, explains session continuation via session_uuid, and describes the return format including session_uuid, turn_number, context, steering_prompts, and instructions. This is comprehensive.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Conciseness4/5

Is the description appropriately sized, front-loaded, and free of redundancy?

The description is well-structured with a summary sentence, usage instruction, enumerated steering modes, and a parameter list. Every sentence adds value, though the parameter list could be more concise. Overall, it's appropriately sized for a complex tool.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Completeness5/5

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

Given the tool complexity (iterative brainstorming with multiple steering modes) and the presence of an output schema (mentioned in description), the description is complete. It covers purpose, when to use, all parameters with semantics, steering modes, session management, and return value fields. No significant gaps.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Parameters5/5

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

Schema description coverage is 0%, but the description fully explains each parameter: topic (the brainstorm topic), steering (with explicit list of allowed modes), session_uuid (continuation vs new session), and turn_notes (optional notes). This adds complete semantic meaning beyond the schema's minimal type definitions.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Purpose5/5

Does the description clearly state what the tool does and how it differs from similar tools?

The description clearly states 'Run one turn of a brainstorm session, returning relevant context.' It specifies the verb and resource, and distinguishes from sibling tools like get_brainstorm_session and save_brainstorm_output by focusing on iterative turns with steering modes.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Usage Guidelines4/5

Does the description explain when to use this tool, when not to, or what alternatives exist?

Explicit guidance: 'Call this at the start of a brainstorm and after each steering action.' This clearly indicates when to use. While it doesn't explicitly list when not to use, the context makes it clear this is for iterative brainstorming, and siblings cover other phases.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.

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