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

Annotations already indicate read-only, idempotent, open-world, and non-destructive hints. The description adds substantial behavioral context: fan-out to multiple sources, fallback logic (GDELT preferred, GNews when rate-limited or 5xx), PatentsView API sunset causing soft-fail, and the return structure (changes[] grouped by source, total_changes count, pipeworx:// 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 every sentence serves a purpose: example queries, source list and fallbacks, parameter formats, return structure, and alternative tool. It front-loads the most actionable info (what the tool does, example queries) and keeps parenthetical details compact. Despite its length, it is efficiently structured for a complex tool.

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?

For a tool with three parameters, multiple data sources, and no output schema, the description is exceptionally complete. It covers return format, parameter semantics, fallback behavior, rate-limit handling, and a clear sibling distinction. The only minor gap is the exact shape of each change item, but the summary of the return structure suffices.

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%, so baseline is 3. The description adds value beyond schema by explaining `since` accepts ISO dates or relative shorthand ("7d", "30d", "3m", "1y") and recommending "30d" or "1m" for typical monitoring. It also clarifies `value` can be a ticker or zero-padded CIK. However, this enrichment is moderate, not exhaustive, so 4 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 clearly states it provides a change feed for a company over a time window, with specific verbs like "Fans out to SEC EDGAR, GDELT→GNews fallback, USPTO." It distinguishes itself from sibling tool entity_profile by explicitly redirecting users who need a static profile. The example queries further clarify the intended use case.

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 gives explicit usage context with example queries ("What's new with X"), parameter guidance (e.g., "Use '30d' or '1m' for typical monitoring"), and an explicit alternative: "Use entity_profile instead when you want the static profile... regardless of window." It also notes efficiency ("in ONE parallel call") and fallback behavior.

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