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check_analysis_status

Monitor the progress of market analysis tasks to track completion status and retrieve results for informed trading decisions.

Instructions

Check the current status of a running or completed analysis.

Args: analysis_id: Analysis identifier returned by analyze_market.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
analysis_idYes

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault
resultYes

Implementation Reference

  • The tool `check_analysis_status` is implemented and registered as an MCP tool in `src/rekko_mcp/server.py`. It calls `_request` to query the analysis status from the backend.
    @mcp.tool()
    async def check_analysis_status(analysis_id: str) -> str:
        """Check the current status of a running or completed analysis.
    
        Args:
            analysis_id: Analysis identifier returned by analyze_market.
        """
        return await _request("GET", f"/v1/insights/{analysis_id}/status")
Behavior3/5

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

No annotations provided, so description carries full burden. Mentions applicability to both 'running or completed' states, implying it's safe to call repeatedly. However, lacks disclosure of polling patterns, typical latency, rate limits, or cache behavior expected for status-checking tools.

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?

Front-loaded purpose statement followed by Args documentation. Efficient with no wasted words, though the Args format is slightly redundant with the schema structure (necessary given 0% schema coverage).

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?

Adequate for a single-parameter status tool with output schema. Covers core workflow relationship to analyze_market. Gap: should mention typical async polling pattern since it explicitly handles 'running' analyses, and possible status values returned.

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 0% (no property descriptions), but the description compensates effectively by documenting the parameter inline: 'Analysis identifier returned by analyze_market.' This provides both semantic meaning (ID type) and provenance (source tool), though format constraints could be added.

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?

Clear verb ('Check') + specific resource ('status of a running or completed analysis'). The focus on 'status' effectively distinguishes this from sibling 'analyze_market' (which initiates) and 'get_analysis' (which likely retrieves results data).

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?

Establishes clear workflow context by stating the analysis_id is 'returned by analyze_market', indicating when to use the tool. However, lacks explicit guidance on when to prefer this over 'get_analysis' or polling best practices for long-running analyses.

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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