Lists PyProximal proximal operator names, optionally filtered by module and selected PyProximal version, to help agents find available operators.
List PyProximal proximal operator names, optionally filtered by module.
pyproximal_version selects the PyProximal version (e.g. "0.10"); default is the latest.
| Name | Required | Description | Default |
|---|---|---|---|
| module | No | ||
| pyproximal_version | No |
| Name | Required | Description | Default |
|---|---|---|---|
No arguments | |||
Changes observed during successful MCP inspections.
v0.1.0Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are provided, so the description must carry behavioral disclosure. 'List' implies a safe read operation and the version/default behavior is disclosed, but there is no explicit statement about side effects, remote access, pagination, or failure behavior; the output schema covers return structure.
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?
Two short sentences, front-loaded with the main action and resource, followed by the version parameter detail. There is essentially no wasted text.
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?
The tool is simple, the two parameters are explained, and an output schema exists so return values need not be described. Given no annotations, it could be slightly more explicit about read-only behavior, but it is complete enough to call correctly.
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 description coverage is 0%, but the description compensates well: it explains that module optionally filters results and that pyproximal_version selects the version with an example format and latest default. It does not give examples or allowed values for module, so it is not perfect.
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 states a specific verb and resource: list PyProximal proximal operator names, with an optional module filter. It is clear enough to distinguish from solver/workflow listing siblings, though it does not explicitly name the nearest alternative such as list_operators.
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?
It explains the two practical usage knobs: filtering by module and selecting a PyProximal version, with latest as the default. However, it does not state when to use this tool instead of siblings like list_operators or list_proxsolvers, leaving that to inference.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.