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

While annotations declare readOnlyHint, openWorldHint, idempotentHint, and destructiveHint=false, the description adds runtime behaviors not captured in annotations: one parallel call fan-out, automatic GDELT→GNews fallback, PatentsView API sunset causing soft-fail, and the exact return shape (changes[] grouped by source, total_changes, pipeworx:// URIs). This is high-value behavioral transparency.

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 not bloated; it packs in query examples, source list, fallback logic, parameter formats, output shape, and an alternative tool. It could be improved with bullet points or clearer structural separation, but each sentence earns its place and the key purpose is front-loaded.

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 complex multi-source aggregator with no output schema, the description is remarkably complete. It covers the return structure, source-specific behavior, parameter semantics, fallback conditions, and a pointer to the alternative entity_profile tool. An agent could invoke this tool correctly with no additional context.

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% (all three parameters have descriptions), so baseline is 3. The description adds extra semantics: relative shorthand examples ('7d', '30d', '3m', '1y'), a recommendation for typical monitoring, and clarification that value can be ticker or zero-padded CIK. This slightly exceeds schema-level detail, meriting a 4.

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 opens with concrete query examples ('What's new with X') and clearly states it's a 'change feed for a company in the last N days/weeks/months'. It names the specific aggregated sources (SEC EDGAR, GDELT→GNews, USPTO) and explicitly contrasts with sibling entity_profile, so purpose is unambiguous and well-differentiated.

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 guidance on when to use this tool: 'Use entity_profile instead when you want the static profile... regardless of window.' It also explains source preference and fallback conditions (GDELT preferred, GNews when rate-limited/5xx), and even recommends typical 'since' values ('Use 30d or 1m for typical monitoring'). This goes far beyond a simple purpose statement.

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