Search events

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

Annotations already declare readOnly=true, non-destructive, idempotent. The description adds that it performs case-insensitive substring search across specific fields and that LIKE wildcards are escaped, which are important behavioral details not in annotations. No contradictions.

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?

Two sentences: first defines core behavior, second provides concrete examples. No wasted words, and the structure is front-loaded with actionable information.

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?

The description covers the search scope and example uses. With an output schema present, the return value details are handled. Slight gap on result ordering or pagination, but acceptable for a search tool.

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 schema already documents both parameters. The description adds value by specifying which fields are searched (entity_path, diff, reasoning, agents), providing context beyond the schema description for the 'query' 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 clearly states the tool performs 'full-text search across entity paths, diffs, reasoning, and agents' and provides concrete example questions. This distinguishes it from sibling tools like blame (focused on authorship), diff (comparison), etc., by emphasizing its broad, cross-field search capability.

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 example queries ('what changes were made for the billing feature?') implying usage scenarios, but does not explicitly contrast with siblings. The context signals show sibling tools with focused purposes, making the search tool's broader applicability somewhat inferable.

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