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

Even with annotations (readOnlyHint, openWorldHint, idempotentHint, destructiveHint), the description adds significant behavioral context: it fans out across multiple sources in parallel, mentions that the USPTO PatentsView API sunset May 2025 and soft-fails until reactivated, describes a GDELT→GNews fallback for news, and specifies the exact return fields. This goes well beyond what annotations provide.

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 dense and front-loaded with example queries, which helps the agent recognize invocation patterns. It packs in many important details (sources, return fields, fallbacks, limitations) without wasted sentences. The list of paraphrases is slightly redundant but not excessive, and the overall structure flows logically from usage to behavior to input constraints.

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?

With no output schema, the description fully responsible for describing return values, and it does: it lists cik + company_name, recent_filings with URIs, fundamentals (LATEST 10-K), patents, news mentions, and LEI. It also covers caveats like the patents sunset and name unsupported, as well as the parallel execution model. This is complete for a multi-source 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 covers both parameters thoroughly (type describes the enum, value explains ticker vs. CIK and the 'names not supported' note). The description repeats this information without adding new parameter-specific semantics beyond example queries. With schema coverage at 100%, the baseline 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 clearly states the tool's purpose: 'full cross-source profile of a US public company in ONE parallel call'. It uses a specific verb with a defined resource and scope. It also distinguishes itself from siblings by explicitly saying 'ALWAYS PREFER over chaining single-pack SEC/XBRL/news lookups' and by directing name-based lookups to resolve_entity.

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 explicitly tells when to use this tool ('when the user asks for a holistic view') and when not to ('names not supported — use resolve_entity first'). It also names the alternative approach (chaining single-pack lookups) and explains why this tool is preferred, providing clear context and exclusion criteria.

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