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okareo-ai

Okareo MCP Server

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by okareo-ai

Query Okareo Documentation

get_docs
Read-onlyIdempotent

Query Okareo documentation to understand concepts like Scenarios, Checks, Targets, Drivers, Evaluations, and Simulations. Choose conceptual mode for technical detail or user_legible for plain-language explanations.

Instructions

Query the Okareo documentation system for information about Okareo primitives and workflows.

    Use this tool when the agent or user needs to understand how Okareo
    concepts work — Scenarios, Checks, Targets, Drivers, Evaluations,
    and Simulations.

    Two modes are available:
    - 'conceptual': Detailed technical documentation for agent reasoning.
      Default top_k=5 (returns up to 5 documentation entries).
    - 'user_legible': Plain-language explanations for human users.
      Default top_k=3 (returns up to 3 documentation entries).

    If the Okareo documentation service is unavailable (e.g. air-gapped
    environment), the tool returns a helpful error suggesting get_templates
    as a fallback.

    Args:
        query: The question to ask the Okareo documentation system. Be
            specific — e.g., 'How do Checks and Evaluations work together?'
            or 'What is a Driver persona?'
        mode: Documentation mode — 'conceptual' or 'user_legible'.
        top_k: Number of documentation entries to return. Defaults to 5
            for conceptual mode, 3 for user_legible mode. Maximum 10.
    

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
modeYes
queryYes
top_kNo

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault
resultYes
Behavior5/5

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

The description goes well beyond the annotations (readOnlyHint, openWorldHint, idempotentHint, destructiveHint) by disclosing mode-specific behaviors: 'conceptual' default top_k=5, 'user_legible' default top_k=3, maximum top_k=10, and a helpful error message suggesting get_templates as a fallback. These details describe the tool's dynamic behavior and error handling, which are not inferable from annotations alone.

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 well-structured and front-loaded: first sentence states purpose, followed by usage guidance, mode details, error behavior, and parameter explanations. While longer than average, every sentence adds value—no redundancy. The use of bullet points and an Args section makes it scannable and easy to parse.

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?

Despite having multiple parameters and no schema descriptions, the description is complete for a read-only documentation query tool. It covers all parameter semantics, mode behavior, defaults, and fallback scenarios. The presence of an output schema means return-value details are not required, so the description is sufficient for an agent to correctly select and invoke the tool.

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 input schema provides only parameter names and types (query, mode, top_k, with top_k nullable and default null). The description compensates fully by explaining each parameter: query with concrete examples ('How do Checks and Evaluations work together?'), mode with its two possible values ('conceptual' or 'user_legible'), and top_k with its mode-specific defaults and maximum value (10). This is essential since the schema has no descriptions (0% coverage).

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 clearly states the tool's purpose: 'Query the Okareo documentation system for information about Okareo primitives and workflows.' It uses a specific verb (query) and resource (documentation system), and explicitly lists the concepts covered (Scenarios, Checks, Targets, Drivers, Evaluations, Simulations). This also distinguishes it from sibling tools like get_templates, which is mentioned as a fallback.

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?

Explicit guidance is provided: 'Use this tool when the agent or user needs to understand how Okareo concepts work.' It also suggests a specific alternative (get_templates) in the event the documentation service is unavailable. The description clearly indicates when to use this tool and provides a fallback option, making it easy to choose among siblings.

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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