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list_analyses

Retrieve recent prediction market analyses with summaries to support trading decisions on platforms like Kalshi and Polymarket.

Instructions

List recent analyses with summary information.

Args: limit: Maximum number of analyses to return.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
limitNo

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault
resultYes

Implementation Reference

  • The implementation of the `list_analyses` MCP tool, which calls the `/v1/analyses` endpoint.
    @mcp.tool()
    async def list_analyses(limit: int = 20) -> str:
        """List recent analyses with summary information.
    
        Args:
            limit: Maximum number of analyses to return.
        """
        return await _request("GET", "/v1/analyses", params={"limit": limit})
Behavior2/5

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

No annotations are provided, so the description must carry full behavioral disclosure. It mentions 'recent' and 'summary information' but fails to define the time window for 'recent', the sorting order, or what fields are excluded in the summary. No mention of pagination behavior beyond the limit parameter.

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 appropriately brief with no wasted words. The Args section is structured clearly, though the docstring format is slightly informal compared to natural prose. Information is front-loaded effectively.

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

Completeness3/5

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

For a single-parameter list tool with an output schema, the description is minimally adequate. However, given the presence of sibling tools like get_analysis and analyze_market, it lacks crucial context about the return format (summary vs. full details) and the temporal scope of 'recent' that would help an agent select the correct tool.

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?

With 0% schema description coverage, the description compensates by documenting the limit parameter as 'Maximum number of analyses to return.' However, it omits that the parameter is optional and has a default value of 20, which the schema shows but the description does not explain.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Purpose4/5

Does the description clearly state what the tool does and how it differs from similar tools?

The description clearly states the verb (List) and resource (analyses), and specifies the scope (recent with summary information). It implicitly distinguishes from analyze_market (creation) but does not explicitly differentiate from get_analysis (retrieval of specific record).

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

Usage Guidelines2/5

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

No guidance provided on when to use this tool versus alternatives like get_analysis (which presumably retrieves a specific analysis by ID). No mention of prerequisites, permissions, or typical workflows.

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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