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okeefeco

PyEye Server

by okeefeco

find_models

Search for all Pydantic models in your Python project. Use scope options to filter by main project, all namespaces, or a specific namespace.

Instructions

Find all Pydantic models in the project.

Args: scope: Search scope (default "main"): - "main": Only the main project (default for plugins) - "all": Include configured namespaces - "namespace:name": Specific namespace

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
scopeNomain

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault
resultYes
Behavior2/5

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

No annotations are provided, so the description must carry the full burden. It only states it 'finds' models, providing no behavioral details like side effects, permissions, or whether it makes external calls.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Conciseness5/5

Is the description appropriately sized, front-loaded, and free of redundancy?

The description is front-loaded with the primary purpose, then concisely documents the parameter in a structured format (Args:) without any superfluous information.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Completeness4/5

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

The tool has only one optional parameter and an output schema exists, so the description adequately covers the parameter and context. It could mention the output type or that it searches the project, but it's sufficient.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Parameters5/5

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

Schema description coverage is 0%, but the description fully compensates by detailing the scope parameter with its valid values ('main', 'all', 'namespace:name') and defaults, which is critical for correct usage.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Purpose5/5

Does the description clearly state what the tool does and how it differs from similar tools?

The description states 'Find all Pydantic models in the project' which clearly identifies the tool's action and target resource. It distinguishes itself from sibling tools like find_blueprints or find_routes.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Usage Guidelines3/5

Does the description explain when to use this tool, when not to, or what alternatives exist?

The description explains the scope parameter options but lacks explicit guidance on when to use this tool versus alternatives or when not to use it.

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

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