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

Despite annotations already marking readOnly/idempotent/destructive hints, the description adds rich behavioral detail: fan-out to multiple external APIs, GDELT→GNews fallback on rate-limit/5xx, PatentsView API sunset causing soft-fail, and return structure ('structured changes[] grouped by source + total_changes count + pipeworx:// citation URIs'). This goes well beyond what annotations 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 information-dense yet well-structured: examples, core purpose, sources, parameter format, return format, and alternative usage. Every sentence earns its place, front-loading natural-language triggers. Despite its length, it avoids redundancy and flows logically.

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 three parameters, no output schema, and a complex multi-source aggregation tool, the description covers all essential context: sources, fallback behavior, failure modes, return shape, and alternative tools. Even the `since` parameter's accepted formats are explained. This is a complete description for selecting and invoking the 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 description coverage is 100%, so baseline is 3. The description restates the `since` format (ISO date or relative) and `value` as ticker/CIK, but the schema already provides these details with examples. No new parameter semantics are added beyond the schema, so it neither improves nor degrades the baseline.

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 specific purpose: 'change feed for a company in the last N days/weeks/months'. It lists concrete sources (SEC EDGAR, GDELT→GNews, USPTO) and explicitly distinguishes itself from sibling tool entity_profile: 'Use entity_profile instead when you want the static profile'. This is a specific verb+resource with strong sibling differentiation.

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 opens with natural-language queries ('What's new with X', 'latest on Y') to signal when to use it. It explicitly provides an alternative: 'Use entity_profile instead when you want the static profile... regardless of window.' This satisfies the when/when-not/alternatives criterion with clear context.

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