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

Beyond the annotations, it discloses a concrete side effect: 'Costs 1 credit.' It also reveals that the response is only a compact summary with verdict badge, score, findings, top bets, and ID/URL, and that the full report must be fetched separately. No contradiction with the 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?

Three dense sentences front-load the main purpose, then cover input constraints, cost, output shape, and follow-up retrieval. Every clause carries useful information with no padding.

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?

For a tool with an output schema, this description fully explains input, cost, and the summary-vs-full-report behavior, including the get_research follow-up. It is slightly incomplete only in not differentiating create_research from create_deep_dive within the sibling tool set.

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?

Schema coverage is 100% and the schema already describes the idea parameter as 'anything from a one-liner to full multiline notes.' The description repeats this and adds the 4,000-character limit already present in the schema's maxLength, so it contributes little beyond the 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 action and resource: 'Generate a comprehensive market research report based on a business idea.' It differentiates from get_research by noting that this call returns only a summary, but it does not explicitly distinguish create_research from the sibling create_deep_dive.

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?

It gives clear context for when to call: when a business idea needs market research, and it accepts anything from a one-liner to full notes. It also points the agent to get_research for fetching the full report later, but it does not explain when create_deep_dive or retry_research might be the better alternative.

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