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

The description discloses multi-source fan-out, GDELT→GNews fallback on rate limits/5xx, and the PatentsView API sunset causing soft-fail, which goes beyond the readOnly/idempotent annotations. It also describes the return structure (changes[], total_changes, citation URIs), providing a comprehensive behavioral model.

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?

While longer than two sentences, the description is well-organized and dense with useful information, avoiding repetition. The opening query examples are front-loaded for quick relevance matching, and the later sections on sources, parameters, and alternatives each add necessary context.

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?

The description covers trigger phrases, source behaviors, parameter options, output structure, and the key alternative tool, which is sufficient given the absence of an output schema. It even notes external API limitations, making it robust for an agent to set expectations.

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 covers all three parameters with detailed descriptions, including `since` format examples and the 30d/1m recommendation, so the description adds no new parameter meaning. Baseline 3 is appropriate given 100% schema coverage; any extra is redundant.

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 defines the tool as a change feed aggregating SEC/GDELT/GNews/USPTO data for a company over a time window, triggered by natural-language queries like 'What's new with X'. It differentiates from entity_profile by explicitly naming the alternative, making its scope unmistakable.

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?

It provides explicit when-to-use signals via example queries and states when to use entity_profile instead, giving a clear exclusion criterion. It also explains the parallel fan-out and fallback behavior, helping the agent decide based on user intent.

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