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pfc_query_python_api

Search PFC Python SDK documentation by keywords to find matching API paths and signatures. Use when you have keywords but do not know the exact API path.

Instructions

Search PFC Python SDK documentation by keywords (like grep).

Returns matching API paths with signatures. Use pfc_browse_python_api for full documentation.

When to use:

  • You have keywords but don't know exact API path

  • Example: "ball velocity", "create", "contact force"

Related tools:

  • pfc_browse_python_api: Get full documentation for a known API path

  • pfc_query_command: Search PFC commands by keywords

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
queryYesSearch keywords for PFC Python SDK API. Examples: 'ball pos', 'contact force', 'model solve'. Case-insensitive.
limitNoMaximum number of results (1-20).

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault

No arguments

Behavior4/5

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

Description discloses that the tool returns matching API paths with signatures, and notes case-insensitive search. With no annotations provided, the description adequately covers safe read behavior, though it could mention absence of side effects or error handling.

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?

Description is concise yet structured with clear sections: purpose, when to use, examples, and related tools. No redundant sentences, front-loaded with key information.

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

Completeness5/5

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

Given presence of output schema, description needn't detail return format. It sufficiently covers purpose, usage, parameters, and tool relationships. Complete for a straightforward search tool with good schema coverage.

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

Parameters4/5

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

Schema coverage is 100% with good documentation. Description adds value by explaining search style ('like grep'), case-insensitivity, and providing example keywords, which enhances understanding beyond schema alone.

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?

Description clearly states verb 'Search' and resource 'PFC Python SDK documentation'. It distinguishes from sibling tool pfc_browse_python_api by noting this tool is for keyword search while the other provides full documentation for known paths.

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

Usage Guidelines5/5

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

Explicitly states when to use ('when you have keywords but don't know exact API path') and provides examples. Also lists related tools with brief descriptions, aiding selection.

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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