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

Beyond the annotations (readOnlyHint, idempotentHint, openWorldHint, destructiveHint=false), the description discloses substantial operational behavior: fan-out to SEC EDGAR, GDELT→GNews fallback, and USPTO patent search with known sunset that causes a soft-fail. It also notes parallel execution and structured returns, which are not inferable from annotations alone.

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?

Six sentences efficiently cover purpose, data sources, fallback behavior, parameter syntax, return shape, and sibling differentiation. Every sentence contributes new information with no redundancy or filler, making it easy for an agent to parse in one pass.

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?

Even though there is no output schema, the description specifies the return format (structured changes[], total_changes count, pipeworx:// citation URIs) and explains parameter syntax, source behavior, and failure modes. This is complete for a tool of this moderate 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?

The input schema already fully describes all three parameters (100% coverage), so the baseline is 3. The description adds meaningful semantics for `since` by enumerating accepted formats (ISO date vs relative shorthand like '7d', '30d', '3m', '1y') and recommending '30d' or '1m' for typical monitoring—value that goes beyond 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 explicitly states the tool is a 'change feed for a company in the last N days/weeks/months in ONE parallel call', with concrete example queries like 'What's new with X'. It also distinguishes itself from sibling `entity_profile` with a direct pointer to when the sibling should be used instead.

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 explicit usage context through example queries and clearly names an alternative: 'Use entity_profile instead when you want the static profile... regardless of window.' This gives the agent solid guidance on when to select this tool over a sibling.

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