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

Annotations already declare read-only/idempotent/non-destructive, but the description adds substantial behavioral context: multi-source fan-out, fallback behavior, USPTO soft-fail due to API sunset, and parallel execution. This goes well beyond annotations, disclosing important runtime behaviors and edge cases.

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 and information-rich, front-loaded with user-facing examples. While every sentence provides useful info, the opening contains six synonymous phrasings of the same query pattern, which is slightly redundant. Overall, it is well-structured and each sentence contributes, but it could be tightened.

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 (three data sources, fallbacks, no output schema), the description fully explains return structure ('structured changes[] grouped by source + total_changes count + pipeworx:// citation URIs'), parameter behavior, source-specific quirks, and the alternative tool. This is complete for an agent to select and invoke correctly.

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% and the schema already contains the full parameter documentation including ISO/relative formats for 'since' and ticker/CIK for 'value'. The description repeats these details, adding only a minor recommendation ('Use 30d or 1m'). As per the baseline rule for high coverage, a 3 is appropriate.

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 immediately provides natural language queries and states the core function: 'change feed for a company in the last N days/weeks/months'. It clearly identifies the verb (get change feed) and resource (company), and differentiates from the sibling entity_profile by mentioning its alternative. This is as clear as the TDQS 4.3 example.

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 explicitly tells when to use this tool vs. alternatives: 'Use entity_profile instead when you want the static profile... regardless of window.' It also provides context on when the fallback sources activate (GDELT→GNews on rate-limit/5xx), which helps the agent decide. This meets the explicit-alternative and when-not-to-use criteria.

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