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

Annotations already declare readOnlyHint, openWorldHint, idempotentHint, and destructiveHint, so the description doesn't need to restate those. It adds substantial behavioral context: the cost of 1 unit, the distinction between evidence and last_event, within_lookback flag, the meaning of resolved:false, and the resolution_confidence threshold. This goes well beyond what annotations provide and covers edge cases clearly.

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 detailed but well-organized, starting with purpose, then usage, then parameter behavior, then edge cases. Each sentence serves a purpose, and the density is justified by the tool's complexity. It is not overly verbose, though it could be slightly more compact without losing key details.

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 there is no output schema, the description fully explains the expected output fields (evidence, last_event, within_lookback, resolved, resolution_confidence) and their interpretations. It covers the cost, the lookback window, and attribution confidence. It also handles the case where the company is not found. This is complete for an agent to invoke and interpret results 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 67% (domain and lookback_days have descriptions; org_id does not). The description significantly enriches lookback_days by explaining its effect on evidence and that it does not limit last_event. It also reiterates the domain flexibility. However, org_id remains unexplained both in schema and description, leaving a small gap. Overall, the description adds meaningful semantics for the key parameter.

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 a precise statement of what the tool does: 'Why to contact ONE company right now: dated funding and SEC 8-K evidence, each item linking to its source filing or announcement.' It uses a specific verb ('provide' or 'give'), names the resource (company), and clearly distinguishes itself from siblings by emphasizing 'ONE company' — implying the others handle multiple entities or different queries.

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 explicitly states when to use the tool: 'Use this when you have a company and need the reason and the proof.' It also explains different outcomes (empty evidence with last_event, resolved:false) and how to adjust lookback_days. However, it does not explicitly mention alternative sibling tools or conditions for not using this tool, though the 'ONE company' focus implicitly separates it from events_for_icp.

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