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

Beyond the readOnly/idempotent annotations, the description richly details behavior: it fans out to multiple sources, describes GDELT→GNews fallback logic, notes the USPTO soft-fail due to API sunset, and discloses the output structure (changes[] grouped by source, total_changes, pipeworx:// citation URIs). This exceeds what annotations alone could convey.

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 every sentence adds value. It opens with user-facing query patterns, then moves to data sources, parameter behavior, return format, and an alternative tool. No fluff or redundant restatement of the tool name.

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 multi-source tool with fallbacks and no output schema, the description is remarkably complete. It covers all three parameters, source-specific behaviors, error/soft-fail conditions, return shape, and how to choose between this and sibling tools. Nothing critical appears 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% but the description adds meaningful guidance for the `since` parameter: it explains ISO vs relative shorthand with examples and recommends '30d' or '1m' for typical monitoring. It also clarifies the output structure, which indirectly helps parameter understanding. Minor deduction because type and value semantics are already fully in the schema.

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 with specific verbs and resources: it provides a change feed for a company over a time window, fanning out to SEC EDGAR, GDELT/GNews, and USPTO. It distinguishes itself from the sibling entity_profile by explicitly noting when to use that alternative 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?

Usage context is explicit: it shows example queries ('What's new with X'), explains the time-window parameter, and gives a clear alternative ('Use entity_profile instead when you want the static profile...'). This tells the agent both when to use this tool and when to choose a different one.

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