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brainstorm

Generate novel ideas by applying creative frameworks (SCAMPER, Design Thinking) with domain context, idea clustering, feasibility analysis, and iterative refinement. Supports Gemini, Codex, and Claude.

Instructions

Generate novel ideas with dynamic context gathering. --> Creative frameworks (SCAMPER, Design Thinking, etc.), domain context integration, idea clustering, feasibility analysis, and iterative refinement. Supports Gemini, Codex, and Claude.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
promptYesPrimary brainstorming challenge or question to explore
providerNoProvider to use (e.g., 'gemini', 'codex', 'claude'). Defaults to server config ('gemini').gemini
modelNoOptional model to use (e.g., 'gemini-2.5-flash'). If not specified, uses the server default (provider default).
methodologyNoBrainstorming framework: 'divergent' (generate many ideas), 'convergent' (refine existing), 'scamper' (systematic triggers), 'design-thinking' (human-centered), 'lateral' (unexpected connections), 'auto' (AI selects best)auto
domainNoDomain context for specialized brainstorming (e.g., 'software', 'business', 'creative', 'research', 'product', 'marketing')
constraintsNoKnown limitations, requirements, or boundaries (budget, time, technical, legal, etc.)
existingContextNoBackground information, previous attempts, or current state to build upon
ideaCountNoTarget number of ideas to generate (default: 10-15)
includeAnalysisNoInclude feasibility, impact, and implementation analysis for generated ideas
Behavior2/5

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

No annotations are provided, so the description should carry the full burden. It mentions 'dynamic context gathering' and features like idea clustering and feasibility analysis, but lacks details on behavioral traits such as rate limits, authorization needs, or side effects.

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 concise, with one sentence and a bullet-like list of features. It is front-loaded with the purpose and uses an arrow to separate key highlights. No unnecessary words.

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

Completeness2/5

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

The tool has 9 parameters and no output schema. The description provides an overview of features but does not explain the return format, how results are structured, or how the 'dynamic context gathering' works in practice. More detail would be beneficial.

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

Parameters3/5

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

Schema coverage is 100%, so baseline is 3. The description does not add significant meaning beyond the parameter descriptions in the schema. For example, the 'methodology' parameter is already well-described in the schema with an enum.

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 the tool's purpose: 'Generate novel ideas with dynamic context gathering.' It lists creative frameworks and features, making it distinct from siblings like 'ask-ai' or 'deploy-agents'.

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

Usage Guidelines3/5

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

The description mentions supported providers and frameworks but does not provide explicit guidance on when to use this tool versus alternatives. No when-to-use or when-not-to-use context is given.

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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