Agent Feedback Loop

get_best_tools

Find top-rated MCP tools for specific tasks using community feedback data to select reliable options based on performance metrics.

Instructions

Get the highest-rated MCP tools, optionally filtered by task type.

Shows the best tools based on community feedback data.

Args: task: Filter by task description keyword (optional) limit: Max results (default: 10)

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": "get_best_tools"
  }
}

Input Schema

Name	Required	Description	Default
`task`	No
`limit`	No

Schema Changelog

Changes observed during successful MCP inspections.

First observedv0.1.0Apr 2, 2026

TDQS

B3.3/5.0

Behavior3/5

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

With no annotations provided, the description carries the full burden. It adds valuable context by specifying the data source ('community feedback data'), but omits other behavioral details such as read-only guarantees, pagination behavior, or rate limiting constraints.

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 appropriately front-loaded with the core purpose in the first sentence, followed by behavioral context, then parameter details. The structure is efficient with no wasted words, though the Args section formatting is slightly informal.

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?

Given the tool's simplicity (2 flat parameters) and lack of output schema, the description provides adequate coverage of inputs and data source. However, it lacks description of return format or pagination, which would be expected for a list-returning tool.

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?

With 0% schema description coverage (properties lack 'description' fields), the description compensates effectively by documenting both parameters: 'task' is explained as a 'Filter by task description keyword' and 'limit' as 'Max results (default: 10)', clarifying semantics and defaults beyond the schema titles.

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 specific action ('Get') and resource ('highest-rated MCP tools') with scope ('optionally filtered by task type'). While it uses distinct terminology ('highest-rated') that implicitly differentiates from siblings like 'get_trending_tools', it does not explicitly contrast usage against them.

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 explains how to filter results ('optionally filtered by task type') but provides no explicit guidance on when to select this tool versus 'get_tool_quality' or 'get_trending_tools'. There are no stated prerequisites or exclusion criteria.

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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