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

Annotations already declare read-only, idempotent, open-world behavior, but the description adds substantial behavioral context: parallel fan-out across multiple external sources, fallback order (GDELT→GNews), the meaning of sources_used/sources_failed, empty sections as real 'no data' rather than bugs, and private-company resolution returning resolved:false with notes. It also explains that small-molecule-only companies showing no FDA biologics is expected. This far exceeds annotation coverage with no contradiction.

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 information-dense and front-loaded with intent, but it is quite long and contains some redundancy with the schema (e.g., type/value interchangeable behavior is restated) and an extended list of query examples. While every sentence carries data, the overall length may slow down an agent's parsing of key directives; a tighter structure would be more effective.

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 that there is no output schema, the description compensates admirably by enumerating the return fields (cik, company_name, recent_filings, fundamentals, patents, federal_contracts, fda_products, hiring, news, LEI), the source fan-out, failure semantics, and input-resolution edge cases. An agent has enough context to invoke the tool correctly and interpret results for this complex multi-source profile 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?

Schema coverage is 100% and both parameters already have descriptions, but the tool description adds important semantics: 'type' accepts company/ticker interchangeably, 'value' can be a ticker, zero-padded CIK, or company name, and name resolution goes through SEC EDGAR's company-name match. It also clarifies the private-company outcome for value, which the schema alone does not convey.

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?

Description states a specific verb and resource: 'full cross-source profile of a US public company in ONE parallel call.' It includes concrete query examples and explicitly frames itself as the holistic-view tool, which differentiates it from sibling tools like resolve_entity or compare_entities. The scope (US public company) and output highlights are unambiguous.

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 says 'ALWAYS PREFER over chaining single-pack SEC/XBRL/news lookups when the user asks for a holistic view,' giving clear when-to-use guidance and a when-not-to-use directive. However, it does not name specific alternative sibling tools (e.g., resolve_entity) or state conditions where a single-purpose lookup should win, so it stops just short of the 5-level explicitness.

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