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timps-swarm

timps-swarm

by Sandeeprdy1729
OverviewSchemaSourceRelated ServersDiscussionsAdmin
Python
Hybrid

timps_prompt_engineer

Improve LLM responses by rewriting prompts with Chain-of-Thought reasoning, XML tags, and few-shot examples. Provide a plain-English task and get an optimized prompt.

Instructions

Rewrite prompts with Chain-of-Thought, XML tags, and few-shot examples for better LLM output.

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_prompt_engineer"
  }
}

Input Schema

NameRequiredDescriptionDefault
requestNoPlain-English task or context for the agent.
languageNoPrimary programming language (default: python).python

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observedv2.2.1

TDQS

B3.4/5.0
Behavior3/5

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

There are no annotations, so the description carries the burden. It states the tool rewrites prompts, which implies a non-destructive operation (though rewrite could be destructive to the original if not careful). It doesn't disclose side effects, output format, or whether it modifies the input or creates a new version. Sufficient for a text-processing tool but lacks depth.

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 a single concatenated sentence that is concise (14 words) and front-loaded with the verb 'Rewrite'. It conveys the purpose and methods efficiently without padding.

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?

The tool is relatively simple (2 optional params, no output schema, no annotations). The description covers the core function but lacks guidance on expected output, reversibility, or quality guarantees. It doesn't say what the rewritten prompt looks like or how to assess the improvement. Given the simplicity, it's adequate but could mention typical use cases or limitations.

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?

Schema coverage is 100%, so the schema already documents both parameters. The description adds context about what the tool does but doesn't add meaning about the 'request' or 'language' parameters beyond their schema descriptions. 'language' default is python, but the description doesn't explain why language matters for prompt rewriting, or if it affects the rewrite style.

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 tool rewrites prompts to improve LLM output using specific techniques (Chain-of-Thought, XML tags, few-shot examples). It has a specific verb (rewrite) and resource (prompts), and the mention of techniques distinguishes it from generic prompt-related tools, though no sibling tool specifically does the same.

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

Usage Guidelines3/5

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

The description implies usage when you have a prompt that needs improvement, but it doesn't explicitly state when to use this tool versus alternatives like timps_self_critic_agent or timps_prompt_injection_scanner. No exclusions are mentioned.

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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