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

Annotations already declare readOnlyHint and openWorldHint, covering safety. The description adds nothing about operational behavior like how sources are queried, how results are aggregated, or what the output looks like. It merely lists sources without explaining the process.

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 a single concise sentence that front-loads the tool's purpose. The list of sources is compact, though slightly dense with colon-separated items. It earns a high score for brevity without losing core information.

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?

The tool integrates six data sources and is designed for idea validation, but the description does not explain what the agent should do with the result, what format the response takes, or how to interpret the composite. With no output schema and no return-value guidance, the description is incomplete for such a complex tool.

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 input schema has full coverage of the single 'idea' parameter with a clear description ('Your idea, problem space, or keyword'). The tool description does not add additional semantics about how the parameter is interpreted, but since schema coverage is 100%, the baseline of 3 applies.

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 identifies the tool as an idea validation composite and enumerates the six data sources it integrates (e.g., HN pain signals, YC funded competitors, GitHub crowding). This distinguishes it from sibling tools like extract_company_landscape or extract_hackernews, though the phrasing 'Idea validation composite' is more of a noun phrase than an explicit verb+resource statement.

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 implies the tool is for idea validation but provides no explicit guidance on when to use it versus alternatives. It does not mention any exclusions, prerequisites, or compare itself to sibling tools such as extract_landscape or package_trends.

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