json_extract

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 describes the tool's capabilities (extraction methods) but lacks details on error handling, performance characteristics, or output format. The phrase 'Always use this tool when...' is somewhat prescriptive but doesn't contradict any annotations.

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 front-loaded with the core purpose. Both sentences earn their place by explaining capabilities and usage guidance. It could be slightly more concise by combining some concepts, but overall it's efficient and clear.

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 tool with 9 parameters, no annotations, and no output schema, the description provides adequate context about what the tool does and when to use it. However, it lacks details about return values, error conditions, or behavioral constraints that would be important for a complex extraction tool. The high schema coverage helps compensate somewhat.

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?

The schema description coverage is 100%, so the schema already documents all 9 parameters thoroughly. The description adds value by explaining the overall extraction approach and use cases, but doesn't provide additional parameter-specific semantics beyond what's in the schema. This meets the baseline for high schema coverage.

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 with specific verbs ('extract', 'retrieve', 'filter', 'search', 'slice') and resources ('JSON files', 'JSON elements'). It distinguishes from the sibling tool 'json_read' by emphasizing targeted extraction rather than general reading.

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 ('when you need to retrieve particular values, filter arrays/objects by conditions, search for patterns, or slice data') and ideal use cases ('targeted data extraction, data transformation, focused analysis'). It implicitly suggests alternatives by highlighting its specialized nature versus the likely more general 'json_read'.

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