idea_check

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

With no annotations provided, the description carries the full burden of behavioral disclosure. It effectively describes what the tool does (checks for existing ideas), mentions sources (GitHub + HN for 'quick', all sources for 'deep'), and outlines the return format (reality check report with specific components). It doesn't mention rate limits, authentication needs, or error handling, but covers the core behavior well for a tool without annotations.

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

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

The description is well-structured and front-loaded with the core purpose. Each sentence earns its place: the first states what it does, the second provides usage guidelines, the third lists trigger phrases, and the last sections explain parameters and returns. There's no wasted text, and it's appropriately sized for the tool's complexity.

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

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

Given the tool has 2 parameters (1 required), 0% schema description coverage, no annotations, but has an output schema, the description provides excellent contextual completeness. It explains the tool's purpose, when to use it, parameters, and return format. The output schema existence means the description doesn't need to detail return values, and it appropriately focuses on semantics and usage.

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

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

The schema description coverage is 0%, so the description must compensate fully. It provides clear semantic explanations for both parameters: 'idea_text' is described as 'Natural-language description of the idea' and 'depth' is explained with its two enum values ('quick' uses GitHub+HN, fast; 'deep' uses all sources in parallel). This adds significant value beyond the bare schema.

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

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

The description clearly states the tool's purpose with specific verbs ('Check if a product idea already exists') and resource ('product idea'). It distinguishes the tool's function from potential alternatives by specifying it's for validation before building. The title is null, so the description carries the full burden and does so effectively.

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

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

The description provides explicit guidance on when to use the tool: 'when users discuss new project ideas, ask about competition, market saturation, or whether something has been built before.' It includes specific trigger phrases in multiple languages, making it very clear about the appropriate context for invocation. No sibling tools exist, so differentiation isn't needed.

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