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okeefeco

PyEye Server

by okeefeco

find_field_validators

Identify all field-specific validators in a Python project. Control the search scope to include main, configured namespaces, or a specific namespace.

Instructions

Find all field-specific validators.

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
Behavior3/5

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

With no annotations provided, the description carries the burden of behavioral disclosure. It explains the behavior of the 'scope' parameter, but does not mention any side effects, permissions, rate limits, or output structure beyond what is implied by the tool name. The presence of an output schema partially mitigates the need to describe return values.

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 extremely concise, consisting of three lines including the 'Args' header. It uses a bullet-point list for the parameter options, making it easy to scan. Every sentence serves a purpose with no superfluous text.

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?

For a tool with one well-documented parameter and an output schema (not shown), the description is largely complete. It could be improved by briefly noting what the output contains or mentioning any constraints, but the current level is adequate for the tool's simplicity.

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?

The schema coverage is 0%, so the description must compensate. It fully explains the single 'scope' parameter, including its default value and three possible values with clear meanings. This adds significant value beyond the schema, which only defines type and default.

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 starts with 'Find all field-specific validators,' which clearly states the tool's purpose. It distinguishes from sibling tools like 'find_validators' by specifying 'field-specific', making the tool's role unambiguous.

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

Usage Guidelines4/5

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

The description provides detailed guidance on the 'scope' parameter with three explicit options and their semantics. However, it does not explicitly compare this tool to alternatives like 'find_validators' or specify when to choose one over the other, which would strengthen this dimension.

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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