Search Intelligence

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

Annotations already declare the tool read-only, idempotent, and non-destructive, so safety is covered. The description adds useful context about returning 'cited records' but does not disclose other behaviors such as result ranking, pagination, or how 'relevance' is determined. No contradictions with 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 two sentences, front-loaded with the core action and scope, and contains no redundant text. Every phrase adds value, making it highly efficient.

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 this is a simple search tool with an output schema and strong annotations, the description covers the key aspects: input type (natural language), content domains, and result nature (cited records). It could mention result ordering or default behavior, but the schema covers parameters and output, so it is largely complete.

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%, with meaningful docstrings for all four parameters. The description adds no extra parameter meaning beyond the schema, so the baseline of 3 applies — it neither compensates for gaps nor detracts.

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 performs 'semantic search' over a specific resource ('DC Hub live intelligence corpus') and enumerates content types (news, M&A deals, facilities, market analysis narratives). This distinguishes it from more targeted siblings like get_news or search_facilities, though it does not differentiate from similarly named 'semantic_search' or '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 implies the tool is for natural-language, cross-corpus searches (e.g., 'natural-language query returns the most relevant cited records'), but it provides no explicit guidance on when to choose this over alternatives or when not to use it. Usage is inferred rather than directly stated.

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