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

Annotations already mark the tool as read-only, idempotent, and non-destructive. The description adds valuable behavioral details: it fans out to multiple APIs with fallback logic (GDELT preferred, GNews on rate limit or 5xx), notes USPTO's PatentsView API sunset risk, and explains the return structure (changes[] grouped by source with citation URIs).

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 but well-structured, starting with example queries and then detailing sources and parameters. Every sentence adds useful information with no filler. Could be slightly more structured with bullet points, but it is efficient and clear.

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 the tool's complexity (multiple sources, fallback logic, parameter formats) and the absence of an output schema, the description fully covers: when to use, what it does, parameter details, output structure (changes[] grouped by source + total_changes + citation URIs), and known limitations (USPTO soft-fail). Nothing essential is missing.

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%, so baseline is 3. The description adds significant value by explaining the `since` parameter format with examples ('2026-04-01', '7d', '30d', '3m', '1y') and recommending '30d' or '1m' for typical monitoring. It also clarifies `value` accepts ticker or CIK.

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 as a 'change feed for a company in the last N days/weeks/months' and lists the sources (SEC EDGAR, GDELT→GNews fallback, USPTO). It explicitly distinguishes from the sibling tool 'entity_profile' by advising to use that instead for static profiles.

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 provides concrete usage examples ('What's new with X', 'latest on Y') and explicitly tells when not to use it ('Use entity_profile instead when you want the static profile'). This gives clear guidance on tool selection.

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