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

The description adds substantial behavioral context beyond the annotations: parallel fan-out across many sources, source fallback (GDELT→GNews), soft-failure of the USPTO API, and the meaning of empty sections via sources_used/sources_failed. It also explains resolved:false behavior for private companies. This goes well beyond the read-only/idempotent hints already provided.

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 purpose and routing guidance. It packs a lot of valuable detail into one continuous block, though a bit more paragraph structuring would improve scannability. Every sentence carries functional information, so there is little waste.

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 tool with no output schema, the description covers all essential runtime expectations: input formats, resolved-name behavior, per-source return categories, soft-fail semantics, sources_used/sources_failed, and the private-company no-match case. An agent has enough context to call this tool correctly and interpret the response.

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%: both parameters already have detailed descriptions in the input schema. The tool description largely restates the same value shapes (ticker, CIK, company name) rather than adding fundamentally new parameter-level semantics. Some output-context additions like resolved_from/resolved_to are useful but not parameter meaning.

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 uses a specific verb+resource pattern ('full cross-source profile of a US public company in ONE parallel call') and anchors it with concrete user phrasings. It also distinguishes itself from chaining single-pack lookups, making its purpose unmistakable even among many siblings.

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?

It explicitly states when to use the tool ('when the user asks for a holistic view') and gives a strong routing directive ('ALWAYS PREFER over chaining single-pack SEC/XBRL/news lookups'). It also covers the private-company edge case, telling the agent what result to expect instead of treating it as a generic failure.

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