data

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 and excels at this. It explicitly documents the output contract, side effects ('Modifies file on disk if operation is 'set' or 'delete''), and failure modes ('FileNotFoundError if file missing. ToolError if format disabled or invalid JSON'). It also details what each operation does, including that set/delete 'always writes to file,' which is crucial for understanding mutation behavior.

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 and appropriately sized, with a clear purpose statement, usage guideline, output contract, side effects, failure modes, and operation details. Every sentence earns its place, though it could be slightly more concise by integrating some details (e.g., combining operation descriptions with side effects).

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 (9 parameters, mutation operations) and the presence of an output schema (implied by context signals), the description is complete enough. It covers purpose, usage, behavior, output, side effects, and failures, compensating for the lack of annotations. The output schema handles return values, so the description doesn't need to explain them further.

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 9 parameters thoroughly. The description adds minimal parameter-specific information beyond the schema—it mentions 'dot-separated key path' and operations but doesn't provide additional syntax, format details, or usage examples. This meets the baseline of 3 when the schema does the 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 as 'Get, set, or delete data in JSON, YAML, or TOML files' with specific verbs (get/set/delete) and resources (structured data files). It distinguishes from sibling tools like data_convert, data_merge, data_query, and data_schema by focusing on basic CRUD operations rather than transformation, merging, querying, or schema operations.

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 clear context for when to use the tool: 'Use when you need to get, set, or delete specific values or entire sections in a structured data file.' However, it doesn't explicitly mention when NOT to use it or name specific alternatives among the sibling tools, such as using data_query for complex queries instead of get operations.

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