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

Annotations already declare this as a safe, read-only, idempotent operation. The description adds valuable behavioral details beyond annotations: it fans out in parallel, lists specific return fields, and discloses that the USPTO patents source 'sunset May 2025 — soft-fails until reactivated' and that news uses a GDELT→GNews fallback. It doesn't mention rate limits or auth, but the added context is strong.

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 long but each sentence carries weight. It front-loads with example prompts, then states the core purpose, usage preference, return details, and parameter constraints. It's more verbose than ideal, but justified given the tool's complexity and multiple data sources.

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 compensates by enumerating the return structure: cik, company_name, recent_filings with URIs, fundamentals, patents, news mentions, and LEI. It also covers source behaviors (parallel fan-out, fallbacks, soft-fail) and input formatting, making it nearly complete for an agent to use effectively.

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 100% of parameters with descriptions for both 'type' and 'value'. The description reinforces with concrete examples ('AAPL', '0000320193') and reiterates the name limitation, but doesn't add significant new meaning beyond what the schema provides. Baseline 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 is exceptionally clear: it states the tool produces 'a full cross-source profile of a US public company in ONE parallel call' and provides concrete example queries. It also distinguishes itself from chained single-pack lookups and from sibling tools like resolve_entity, making its purpose 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?

It explicitly says 'ALWAYS PREFER over chaining single-pack SEC/XBRL/news lookups when the user asks for a holistic view,' and clearly notes that names are not supported, directing the agent to use resolve_entity first. This provides both when-to-use and when-not-to-use guidance.

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