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

Discloses rich behavioral detail beyond the readOnly/idempotent annotations: fans out to SEC EDGAR, GDELT→GNews fallback behavior, USPTO soft-fail due to PatentsView API sunset, and the exact return structure (changes[] grouped by source, total_changes, pipeworx:// citation URIs). This is substantial added context.

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 front-loaded with user-intent phrases, then efficiently packs essential details—sources, fallbacks, date formats, return shape, and alternative tool—into a dense but well-organized paragraph. Every sentence earns its place; no filler or redundancy.

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 (multi-source, fallback logic, date parsing, output schema absent), the description covers all critical aspects: source APIs, fallback strategy, error/soft-fail behavior, return format, and an explicit alternative. An agent can confidently decide to invoke this tool and know what to expect.

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 by providing concrete date format examples ('7d', '30d', '3m', '1y') and a recommended default for typical monitoring, helping agents choose appropriate `since` values. It doesn't add much for `type`/`value` beyond the schema, but the extra usage guidance justifies a 4.

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 for a company over a time window, with explicit examples ('What's new with X') and a concrete verb phrase. It distinguishes itself from siblings by explicitly naming entity_profile as the alternative for static profiles, making the purpose 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?

Provides explicit when-to-use guidance via NLP-style examples, and directly states 'Use entity_profile instead when you want the static profile... regardless of window.' It also offers practical parameter advice ('Use "30d" or "1m" for typical monitoring'), going beyond a vague 'when needed'.

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