json_json_filter

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

With no annotations provided, the description must disclose behavioral traits. It only states the basic operation and return type. It does not specify error handling for missing keys, type mismatches, invalid JSON, or the behavior when no items match. The description fails to cover important edge cases.

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 extremely concise, using a single sentence with a clear structure: [context] + action + condition + return type. It front-loads the purpose. However, it sacrifices necessary details for brevity, making it borderline too minimal.

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 that there is an output schema, the return type is covered. However, the tool has 3 required string parameters with no format specifications or examples. The description does not address common pitfalls or provide enough context for an AI agent to reliably use the tool without errors.

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 0%, so the description must add meaning. It clarifies that 'data' is a JSON array (though in string format) and that 'key' and 'value' are used for filtering. However, it does not specify the expected format of the input string (e.g., must be valid JSON array) or provide examples. It adds marginal value beyond the parameter names.

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 filters a JSON array by key-value equality. It specifies an action (filter), resource (JSON array), and condition (key equals value). It is distinct from siblings like table_table_filter (which works on tabular data) and batch_batch_filter (which works on batch items), though it doesn't explicitly differentiate.

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?

No guidance is provided on when to use this tool vs. other filtering tools (e.g., batch_batch_filter, map_reduce_mr_filter). The description does not mention prerequisites, alternatives, or exclusions. An AI agent would have no context to decide between similar tools.

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