Extract data model

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

No annotations are provided, so the description carries the full burden of behavioral disclosure. It mentions that a cache can be used (via the refresh parameter), but does not explain the analysis process, potential side effects (e.g., reading many files), or what happens with unsupported ORMs. This is minimal behavioral context.

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, compact sentence listing the supported frameworks, which is efficient. It is front-loaded with the key resource, and every word adds value. It could be slightly more structured but is not verbose.

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 no annotations, no output schema, and a moderate complexity (4 params), the description is adequate but leaves gaps. It doesn't explain the output format or that the tool may perform a scan, which could surprise the agent. The parameter list is clear, but behavioral aspects like caching are only hinted at via the refresh parameter.

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 coverage is 100%, so each parameter is described in the schema. The description adds context by linking the tool to a broad set of ORMs, which clarifies the 'root' parameter's scope. However, the 'feature' parameter's meaning is not elaborated beyond the schema, but the schema is sufficient.

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 identifies a specific action ('extract') on a resource ('data model') and lists many supported ORMs and frameworks, which clearly communicates what the tool analyzes. However, it does not explicitly contrast with siblings like extract_endpoints or explain_feature, though the resource focus is fairly distinct.

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 implies usage for extracting data models from various ORMs, but does not state when to prefer this over alternatives like scan_project or explain_feature. There is no explicit when-not-to-use guidance, leaving some ambiguity for an agent choosing among siblings.

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