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QuanterLab

by com.quanterlab
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describe_capability

Read-only

Match a natural-language intent string to one or more QuanterLab workflows.

    Returns a list of matching workflows with their name, description, required and optional parameters,
    estimated runtime, and what a request may leave open with the default each one takes (`defaults`). Use this to
    pick the right `start_*` tool when the user describes what they want in their own words. The run starts with
    those defaults, named in one short line with its result; the person's own changes come after it, as next
    steps.

    Args:
        intent: What the person wants, in their own words, e.g. "I want to find mean-reverting
            stocks", "backtest an RSI strategy on Apple", "is my SPY
            strategy overfit?".

Input Schema

NameRequiredDescriptionDefault
intentYes

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observed

TDQS

A4.6/5.0
Behavior4/5

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

Annotations already declare read-only, non-destructive, closed-world behavior. The description adds useful behavioral detail by listing the returned workflow fields and the `defaults` concept, though one sentence about how the run starts is somewhat ambiguous for a discovery tool.

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

Conciseness4/5

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

The description is front-loaded with purpose and return details, then usage guidance and parameter examples. It is mostly efficient, but the sentence beginning 'The run starts...' is somewhat ambiguous in the context of a describe-only tool.

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?

There is no output schema, so the description compensates by explaining what the returned list contains, including workflow metadata and defaults. It does not document edge cases such as no-match behavior, but it is complete enough for an agent to invoke the tool correctly.

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 has 0% description coverage for the only parameter, so the description has to carry the full burden. It does so by explaining that `intent` is free-form user wording and by providing concrete examples such as finding mean-reverting stocks and backtesting an RSI strategy.

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 gives a specific verb and resource: match a natural-language intent string to QuanterLab workflows. It also states the return contents and explicitly distinguishes the tool from the execution tools by saying it is used to pick the right `start_*` tool.

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?

It states the condition directly: use this when the user describes what they want in their own words, and use it to pick the correct `start_*` tool. This gives both the when-to-use and the alternative execution path without requiring inference.

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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