timps-swarm

timps_rag_evaluator

Evaluate RAG pipelines using RAGAS-style metrics for context precision, recall, faithfulness, answer relevance, MRR, and NDCG. Outputs a runnable evaluation harness and an improvement plan.

Instructions

Run a RAGAS-style evaluation of a RAG pipeline: context precision/recall, faithfulness, answer relevance, MRR/NDCG, with a runnable eval harness and an improvement plan.

Tool call template

This tool declares no required parameters. Add optional parameters from the input schema as needed.

{
  "id": 1,
  "jsonrpc": "2.0",
  "method": "tools/call",
  "params": {
    "arguments": {},
    "name": "timps_rag_evaluator"
  }
}

Input Schema

Name	Required	Description	Default
`request`	No	Plain-English task or context for the agent.
`language`	No	Primary programming language (default: python).	python

Schema Changelog

Changes observed during successful MCP inspections.

First observedv2.2.1Aug 20, 2026

TDQS

A4/5.0

Behavior3/5

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

No annotations are provided, so the description carries the burden. It mentions creating a runnable eval harness and improvement plan, implying file/system changes, but does not disclose potential side effects (e.g., modifying files, installing dependencies) or any required permissions. This is a moderate gap.

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, dense sentence that front-loads the primary purpose (RAG evaluation) and then lists key metrics and deliverables. It is concise without unnecessary words, making it easy to parse.

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?

The description mentions the evaluation aspects and outputs (harness, improvement plan), but does not elaborate on how the harness is delivered or any prerequisites. While not exhaustive, it gives enough context for typical usage, and there is no output schema to detail further.

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

Parameters3/5

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

The input schema already provides coverage for both parameters (request and language) with descriptions. The tool description does not add extra semantics beyond the schema, so the baseline of 3 applies given high schema 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: running a RAGAS-style evaluation of a RAG pipeline, specifying key metrics (context precision/recall, faithfulness, answer relevance, MRR/NDCG). It distinguishes from siblings by focusing on evaluation rather than design or other tasks.

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?

The description implies usage for evaluating RAG pipelines and mentions delivering an improvement plan, but does not explicitly state when to use it versus alternatives (e.g., when to pick this over other RAG tools). It is clear but could be more direct about the situation.

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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