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

Beyond the annotations (readOnlyHint, openWorldHint), the description discloses key behavioral traits: data is 'assembled live from keyless public sources' (Wikipedia, World Bank, REST Countries), fields that cannot be sourced are 'marked unavailable rather than estimated,' and the output is a 'machine-readable note with six sections.' This adds substantial transparency about data provenance, accuracy safeguards, and output structure, which the annotations do not cover.

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 moderately lengthy but every sentence contributes value: purpose, output structure, use cases, data sources, error handling, and inputs. It is well-organized and front-loaded with the primary action. Slightly verbose due to enumerating the six sections, but not wasteful.

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's complexity and the presence of an output schema, the description is remarkably complete. It explains what the tool does, what output format to expect, when to use it, how data is sourced, and how missing data is handled. It also covers all inputs succinctly. There are no obvious gaps for an agent to misuse the 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 already provides 100% coverage, describing each parameter clearly (topic, geo, sector, async). The description only adds 'Inputs: topic (required), geo and sector (optional refinements),' which merely restates the schema. It does not introduce new semantic insight beyond what the schema already offers, so the baseline score of 3 is appropriate.

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 starts with a specific verb and resource: 'Generate a structured, sourced market research brief on any market, sector or industry.' It also details six distinct sections and emphasizes 'no invented figures,' which clearly distinguishes it from generic 'market_sizing' or 'competitive_deep_dive' tools. The scope is explicit and unambiguous.

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 includes a dedicated 'When to use this tool' clause listing four concrete scenarios: assessing a new market, validating a business opportunity, preparing a pitch, or benchmarking before a strategic decision. While it clearly states when to use it, it does not explicitly mention when not to use it or name alternative tools, so it misses the full 'when-not/alternatives' criteria.

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