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SymKit

by LBurny
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Python
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tool_recommend

Recommends a suitable tool for a given task by evaluating the task description and optional domain, then returns a recommended tool with rationale and an example.

Instructions

    💡 Recommend the best tool(s) for a given task.

    Args:
        task: Brief description of what you want to do
        domain: Optional domain context

    Returns:
        Recommended tool with rationale and example

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": {
      "task": "<task>"
    },
    "name": "tool_recommend"
  }
}

Input Schema

NameRequiredDescriptionDefault
taskYes
domainNogeneral

Output Schema

NameRequiredDescriptionDefault

No arguments

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observedv1.0.0

TDQS

A4.1/5.0
Behavior4/5

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

With no annotations provided, the description carries the full burden of behavioral disclosure. It explains that the tool returns a recommended tool with rationale and example, which covers its main behavior. No contradictions or hidden side effects are indicated.

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 extremely concise: one sentence plus structured Args/Returns. It is front-loaded with an emoji and every sentence adds value. No wasted words.

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

Completeness5/5

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

Given the tool's simplicity (two parameters, no nested objects) and the presence of an output schema, the description adequately covers what the tool does and returns. It is complete for its purpose.

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 description coverage is 0%, so the description must compensate. The Args section adds meaning beyond the schema: 'Brief description of what you want to do' for task and 'Optional domain context' for domain. This is helpful but still brief, without examples or constraints.

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 'Recommend the best tool(s) for a given task,' which is a specific verb+resource. The tool's meta-purpose distinguishes it from sibling tools that perform specific actions like assume, derive, or session management.

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 usage context is implied: it is meant for tasks where tool selection is needed. However, there is no explicit guidance on when to use this tool versus alternatives, nor are any exclusions or prerequisites 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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