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

With annotations already declaring read-only, idempotent, and open-world, the description adds substantial behavioral context: fan-out across SEC EDGAR, GDELT→GNews fallback with rate-limit handling, USPTO soft-fail due to API sunset, and parallel execution. It also describes the return structure (changes[] grouped by source, total_changes count, citation URIs), going well beyond the annotations.

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 information-dense, with front-loaded examples that aid intent matching. While efficient, the initial example list is somewhat redundant and could be trimmed, but every subsequent sentence earns its place by covering sources, fallbacks, output, and alternatives.

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 fully documents return values (changes[], total_changes, citation URIs) and covers edge cases like GNews fallback and USPTO sunset soft-fail. It also provides a clear alternative tool, making the description complete for the tool's complexity.

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% with each parameter (type, since, value) having descriptive text. The description adds only a minor recommendation ('Use "30d" or "1m" for typical monitoring') and repeats the schema-provided formats. Given the high schema coverage, the description adds little new parameter-level meaning, hence a baseline 3.

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 provides a 'change feed for a company in the last N days/weeks/months' with specific verb ('change feed') and resource scope (company). It distinguishes from sibling by explicitly naming 'entity_profile' as the alternative for static profiles, and lists concrete example queries that map to user intents.

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 gives explicit when-to-use guidance through examples ('What's new with X') and states an alternative: 'Use entity_profile instead when you want the static profile...'. It also explains the time-window context and that this is for dynamic changes, not static data.

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