json_query

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

With no annotations, the description carries the transparency burden. It explains path syntax with examples, which is useful, but it doesn't disclose return format, error behavior for invalid JSON or missing paths, or whether wildcards are fully supported.

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 concise and front-loaded with the main verb, but the '[PRO — 3 trial uses left]' prefix adds unrelated operational information that muddies the core message. Still, it is short and informative.

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?

For a simple 2-parameter tool with no output schema, the description adequately covers purpose, syntax, and a use case. However, it could improve by stating the return type or what happens on failure, which is relevant for an agent.

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% and includes examples for the path parameter, so the schema already provides strong guidance. The description's examples are redundant with the schema, adding no additional meaning beyond what the schema already contains.

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 extracts values from a JSON object using dot-notation paths, with specific examples. This is a distinct action from sibling tools like json_format or json_diff, so it is well differentiated.

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?

It explicitly says 'Useful for quickly inspecting nested API responses,' providing clear context for when to use it. It doesn't mention alternatives or exclusions, but the use case is enough to guide the AI agent.

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