extract_local

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

With no annotations provided, the description carries the full burden. It mentions using a 'local model' but does not disclose safety aspects (e.g., read-only nature), performance characteristics, or any side effects. The behavioral traits are minimal beyond the basic extraction operation.

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 (two short paragraphs plus an Args list) and avoids unnecessary information. It is front-loaded with the main purpose. The Args section adds structure, though the model parameter is missing from that list.

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 presence of an output schema (not shown but noted), the description does not need to detail return format. However, it is missing context about the model parameter and does not clarify how the extraction result is structured. Overall, it covers basics but leaves some gaps.

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 input schema has 3 parameters with 0% description coverage. The description adds meaning for 'text' and 'what_to_extract' with brief explanations and examples. However, the 'model' parameter is not described, leaving its purpose unclear (though default null suggests it's optional).

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 specifies exactly what the tool does: extract specific information from a text block using a local model. It gives concrete examples like function names, URLs, error messages, and TODO comments, making the purpose clear. This distinguishes it from siblings like ask_local or summarize_local, which are not focused on extraction.

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 states it is 'good for pulling structured data out of unstructured text', providing clear context for when to use. However, it does not specify when not to use it or mention alternative tools, such as using a different model or tool for broader summarization.

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