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

Annotations declare readOnly, openWorld, idempotent, and non-destructive behavior, and the description adds valuable context beyond that: multi-source fan-out, source-specific fallbacks, rate-limit handling, sunset API soft-fail behavior, and the exact return structure. No contradiction with annotations.

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 carries necessary information—query patterns, source fan-out, date formats, return shape, and alternative tool. It is front-loaded with the most common use cases and avoids filler or repetition.

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 data sources, fallbacks, various date formats, citations), the description covers all essential aspects: what it returns, how sources behave, how to invoke it, and when to use a different tool. No output schema exists, but the description compensates by describing the return structure.

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?

Even though schema coverage is 100%, the description significantly enriches parameter understanding: it explains that 'since' accepts both ISO dates and relative shorthands with examples, and that 'value' can be a ticker or zero-padded CIK. It also notes the 'type' enum currently only supports 'company', adding clarity 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's function: a change feed for a company over a time window, with clear examples of user intents. It also distinguishes itself from the sibling entity_profile by contrasting dynamic changes vs static profile.

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?

Provides explicit 'when to use' guidance via natural language examples, and explicitly says to use entity_profile instead for static profiles. It also documents fallback behavior (GDELT vs GNews) and soft-fail for USPTO, so the agent knows what to expect.

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