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

Annotations already indicate read-only, idempotent, open-world, and non-destructive behavior. The description goes well beyond by disclosing fan-out to multiple external APIs in parallel, the GDELT→GNews fallback, USPTO's soft-fail due to PatentsView sunset, and the return structure (changes[] grouped by source, total_changes, citation URIs). No contradictions 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 well-structured: it starts with recognition patterns, defines the core behavior, enumerates sources with fallback details, and ends with the alternative tool. Every sentence contributes useful context without redundancy or padding.

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 without an output schema, the description covers the return format (structured changes[], total_changes, pipeworx:// citation URIs), source-level behavior, fallbacks, and parameter handling. It also positions the tool against entity_profile, making its scope fully understandable for an agent.

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 description coverage is 100% — the schema already documents type, since, and value with format examples. The description repeats the `since` format and entity types but adds no new parameter-level meaning. Per the rubric, a high-coverage schema means a baseline of 3.

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 opens with natural-language queries and then explicitly states it's a 'change feed for a company in the last N days/weeks/months in ONE parallel call,' listing sources (SEC EDGAR, GDELT/GNews, USPTO). It clearly distinguishes itself from the sibling entity_profile by contrasting the dynamic feed with the 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?

It provides concrete example phrasings for when to use the tool ('What's new with X' / 'latest on Y'), and explicitly directs users to 'Use entity_profile instead when you want the static profile...' It also describes fallback behavior (GDELT preferred, GNews on rate-limit/5xx), which informs usage decisions.

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