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

Annotations already declare the tool read-only and idempotent, and the description adds substantial behavioral context beyond that: fan-out across sources, specific return fields (cik, filings with URIs, fundamentals sorted by period_end, patents with sunset warning, news fallback GDELT→GNews, LEI), and the 'up to 5' limit. It also discloses the inability to accept names, preventing misuse.

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?

Though long, the description is densely packed with useful information and never wastes a word. It opens with example queries, then the core purpose, then usage priority, then a structured list of return items, then input format. Each segment earns its place, and the semicolon-delimited return list is easy to scan.

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 is complex (fan-out over multiple APIs, multiple return fields, fallbacks, limits) and there is no output schema, but the description fully enumerates the return fields, data sources, sort order, limits, and fallback behavior. Nothing essential is missing.

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 both parameters thoroughly, including the ticker/CIK format and the name-not-supported caveat. The description echoes the schema without adding new parameter-level semantics, so 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 is extremely clear about what the tool does: it builds a full cross-source profile of a US public company in one parallel call. It provides multiple natural-language example queries and explicitly names the resources (SEC EDGAR, XBRL, USPTO, news, GLEIF). It also differentiates from siblings by stating 'ALWAYS PREFER over chaining single-pack SEC/XBRL/news lookups' and referencing resolve_entity for name-only inputs.

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 explicit when-to-use guidance ('when the user asks for a holistic view'), names the alternative (resolve_entity first if only a name), and notes the patents API soft-fail behavior. This is a model of clear usage instructions.

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