load_json_dataset

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

No annotations are provided, so the description must disclose behavioral traits. It does not mention error handling (e.g., file not found, invalid jq), side effects, or performance implications. The description is too brief for full transparency.

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 a single sentence with no wasted words. It is concise and front-loaded, but lacks any structural elements like sections, which could enhance readability for longer descriptions.

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 absence of an output schema, the description should explain what the tool returns. It does not describe the output format or behavior (e.g., whether it returns the array directly or a wrapper). This is a significant gap for a tool with no output schema.

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% for both parameters. The description adds value by clarifying the jq_expression parameter's expected output type ('returns an array of records'), which goes beyond the schema's generic description. This offsets the high coverage baseline.

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 it loads a JSON dataset using a jq expression returning an array of records. The verb 'Load' and resource 'JSON dataset' are specific, and the mention of jq distinguishes it from siblings like 'load_dataset'.

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 context for when to use (load JSON with jq) but does not explicitly state when not to use or recommend alternative tools. Implicit usage guidance is present but not exclusionary.

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