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

Annotations already mark the tool as read-only, idempotent, and non-destructive, so the description's burden is lower, but it adds critical behavioral context: snippets are 'KEYWORD WINDOWS, NOT FACTS' and figures must not be cited from snippets. It also clarifies the data scope by stating that MarketPing publishes no recommendations, price targets, or grey-market premiums.

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 compact and well-structured: it states the purpose first, then the output shape, then the critical snippet caveat, then the data scope. Every sentence earns its place, and the all-caps warning is an efficient way to emphasize a high-risk behavior.

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 two-parameter, read-only search tool with no output schema, the description is complete: it explains the search scope, return format, follow-up tool, snippet reliability limitation, and data boundaries. An agent has enough information to invoke it correctly and interpret results safely.

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 description coverage is 100%, so the baseline is 3; both query and company are already clearly described. The description adds useful context about the search corpus (annual reports, transcripts, presentations), but it does not need to explain parameter semantics further since the schema already does.

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 opens with a specific verb and resource: 'Full-text search across every page MarketPing holds', then enumerates document types (annual reports, earnings-call transcripts, investor presentations). It also names the exact return shape ({doc_id, page, snippet}) and points to read_pages as the intended follow-up, which clearly distinguishes it from generic sibling tools like search.

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 gives clear usage context: use it to search full text across MarketPing's document corpus, and follow up hits with read_pages. It does not explicitly state when not to use it or compare it against the sibling 'search' tool, but the follow-up routing provides enough practical guidance for an agent.

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