StatsPAI

describe_function

Read-only

Retrieves machine-readable metadata for a registered StatsPAI function, including parameters, assumptions, failure modes, and alternatives, so you can validate and call unlisted functions correctly.

Instructions

Full machine-readable metadata for one registered StatsPAI function: JSON-Schema parameters (types, defaults, enums), assumptions, pre-conditions, failure modes, alternatives, validation tier and evidence notes, plus the accepted keyword aliases. Read this before calling a function that is not in the listed tools.

Tool call template

Replace each placeholder with a value matching the input schema. Only required parameters are included; add optional parameters as needed.

{
  "id": 1,
  "jsonrpc": "2.0",
  "method": "tools/call",
  "params": {
    "arguments": {
      "name": "<name>"
    },
    "name": "describe_function"
  }
}

Input Schema

Name	Required	Description	Default
`name`	Yes	Registered function name (sp.<name>).
`detail`	No	Payload depth; agent is the fullest.	agent
`data_id`	No	Data handle (d_...) from load_data; replaces data_path.
`data_csv`	No	Small inline table as CSV text.
`as_handle`	No	Cache the fit and return its result_id.
`data_path`	No	Absolute path of a data file on the server.
`result_id`	No	Handle of an earlier fit made with as_handle=true.
`data_records`	No	Small inline table as row objects.
`max_output_bytes`	No	Result byte budget (default 262144; 0 = none).

Output Schema

Name	Required	Description	Default
No arguments

Schema Changelog

Changes observed during successful MCP inspections.

First observedv0.1.0Nov 12, 2026

TDQS

A4.5/5.0

Behavior5/5

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

Annotations only declare read-only and closed-world behavior, while the description adds substantive context about the metadata payload: assumptions, pre-conditions, failure modes, alternatives, validation tier, evidence notes, and aliases. This tells the agent what the tool inspects and why it matters before invocation.

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?

Two sentences, front-loaded with purpose and then the usage rule. The long enumeration is purposeful because it specifies the metadata returned, and there is no unnecessary wording.

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?

For a metadata-description tool with an output schema and fully documented parameters, the description covers purpose, usage, and payload content. The output schema carries return shape, so nothing critical is missing.

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

Parameters3/5

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

Schema description coverage is 100%, and the schema documents all nine parameters including the detail enum and data handles. The description mentions JSON-Schema parameters and aliases as output content but does not add per-parameter meaning beyond the schema, so the baseline of 3 is appropriate.

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 a specific verb and resource: full machine-readable metadata for one registered StatsPAI function. It scopes the tool to a single function and distinguishes it from data-description siblings by focusing on function metadata.

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?

It gives an explicit condition: read this before calling a function that is not in the listed tools. It does not name call_function as the follow-up or state broader exclusions, so the guidance is clear but not a full when/when-not/alternatives guide.

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