search_records

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

With no annotations provided, the description carries the full burden of behavioral disclosure. It effectively describes key behaviors: it explains query syntax with examples, notes constraints (e.g., is empty/is not empty only works for specific field types), and mentions pagination and sorting options. However, it lacks details on error handling, rate limits, or authentication needs, which are common for such tools.

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 well-structured with clear sections: purpose, recommendation, query examples, and notes. It is appropriately sized for a complex tool, though some examples could be condensed. Every sentence adds value, such as clarifying field type constraints and referencing other tools for 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 the complexity (search tool with query language), no annotations, and no output schema, the description is quite complete. It covers purpose, usage guidelines, behavioral aspects (query syntax, constraints), and parameter context. However, it lacks details on output format (e.g., structure of returned records) and error cases, which would be helpful for full completeness.

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 description coverage is 100%, so the schema already documents all parameters (app_id, query, fields). The description adds value by providing extensive query examples and usage notes that clarify the semantics of the query parameter beyond the schema's basic examples, but it doesn't add significant meaning for app_id or fields parameters. Baseline 3 is appropriate as the schema does heavy lifting.

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 purpose: 'kintoneアプリのレコードを検索します' (searches records in a kintone app). It specifies the verb (search) and resource (records in a kintone app), and distinguishes itself from siblings like get_record (which retrieves a single record) or get_records (not listed, but implied as different).

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 provides explicit guidance on when to use this tool: it recommends using get_form_fields first to understand field codes and types before creating queries, and directs users to get_query_language_documentation for detailed syntax and specifications. It also distinguishes from siblings by not overlapping with tools like get_record or create_record.

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