search_events

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

The description discloses that events are machine-merged and machine-reviewed, specifically noting that review_status is a batch machine approval, not per-item human review, and canonical_summary is an LLM-generated narrative. This is a valuable caveat beyond the basic operation, providing transparency about data reliability and provenance.

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 two dense sentences that convey the purpose, the merging behavior, provenance formats, and reliability caveats. No filler or redundant information; every phrase adds value.

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?

There is no output schema, so the description appropriately explains the key return fields (review_status, canonical_summary) and the per-source provenance structure. It also covers the source roles, making the tool's behavior sufficiently predictable for an agent to select and invoke it.

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?

With 100% schema coverage, the baseline is 3. The description adds no extra meaning about parameter usage—it focuses on the result structure rather than how to filter the parameters. Thus it neither improves nor worsens the schema's already clear documentation.

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 the tool's function: searching cross-book fused historical events with per-source provenance. It specifies the merging of records from multiple history books and the output structure, distinguishing it from sibling tools like get_person or query_by_place which target other entity types.

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 establishes a clear context for when to use this tool—when you need an event synthesized from multiple historical sources. It does not explicitly name alternatives or exclusions, but its scope is sufficiently distinct that an agent can infer when to apply it.

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