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AlgoChains MCP Server

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by AlgoChains
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Python
Hybrid

get_prediction_market_bot_metrics

Read-onlyIdempotent

Retrieve recent JSONL metric entries for a specified prediction-market bot from the local audit log to analyze performance and detect issues.

Instructions

Read recent JSONL metric entries for a prediction-market bot_id from the local audit log.

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": {
      "bot_id": "<bot_id>"
    },
    "name": "get_prediction_market_bot_metrics"
  }
}

Input Schema

NameRequiredDescriptionDefault
bot_idYes
max_linesNo

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observedv22.7.1

TDQS

A3.5/5.0
Behavior3/5

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

Annotations already indicate read-only, idempotent, and non-destructive behavior. The description adds context about the data format (JSONL) and source (local audit log), but does not explain what 'recent' means or any output details.

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 a single, concise sentence with no filler. Every word adds value, clearly conveying the tool's purpose and scope.

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?

For a simple read-only tool with two parameters and no output schema, the description is mostly complete. It identifies the resource and source, but lacks definition of 'recent' and details about the returned data format.

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

Parameters2/5

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

Schema description coverage is 0%, so the description bears the burden. It only implies the 'bot_id' parameter but does not explain 'max_lines' or its default value. No parameter details are provided beyond the schema itself.

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 action ('Read'), the specific resource ('JSONL metric entries'), the scope ('recent'), and the source ('local audit log'). It distinguishes this tool from siblings like 'get_all_bot_metrics' (all bots) or 'get_live_bot_metrics' (live data).

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?

The description provides no guidance on when to use this tool versus its siblings (e.g., 'get_all_bot_metrics', 'get_live_bot_metrics'). It lacks explicit when-not-to-use or alternative recommendations.

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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