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

Beyond the annotations (readOnlyHint, openWorldHint, idempotentHint, destructiveHint), the description discloses important behavioral details: it fans out across multiple sources in a single parallel call, returns specific data fields with sorting, includes fallback chains (GDELT→GNews), and notes the USPTO PatentsView API sunset with soft-fail behavior. This adds meaningful context about how the tool operates and its limitations, exceeding what annotations alone 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 long but densely packed with useful information. It is front-loaded with example queries and the core 'full cross-source profile' message. While it reads as a single verbose paragraph, each clause contributes to the tool's purpose, input requirements, output details, and fallback behavior. It is not wasteful, though restructuring into shorter sentences could improve scannability.

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 takes full responsibility for explaining return values, which it does thoroughly: lists cik, company_name, recent_filings (with URI format), fundamentals (specific fields and sorting), patents, news mentions, and LEI. It also covers input constraints, error conditions (names not supported), and fallbacks. For a complex multi-source tool, this description is remarkably complete and self-sufficient.

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 provides 100% parameter coverage with descriptions for type and value. The description adds valuable usage context beyond the schema: concrete examples ('AAPL', '0000320193'), the requirement for zero-padded CIK, and explicit note that names are unsupported. This reinforces and clarifies the schema rather than repeating it, adding practical semantic guidance.

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: building a 'full cross-source profile of a US public company in ONE parallel call.' It uses specific verbs like 'profile', 'research', 'brief me' and lists concrete output categories (SEC, XBRL, USPTO, news, LEI). It also distinguishes itself from sibling tools like resolve_entity and compare_entities by emphasizing the holistic, cross-source nature and the preference over chaining multiple lookups.

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.' It also provides clear exclusions: 'names not supported (use resolve_entity first if you only have a name)' and shows example queries to illustrate when to use the tool. This gives unambiguous guidance on when to select this tool over alternatives.

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