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all-agents-mcp

all-agents-mcp

by Dokkabei97
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TypeScript
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debug_with

Debug an error by choosing an AI agent and supplying the error message, code, and context to identify the root cause.

Instructions

Debug an error using a specific agent. Provide the error and optional code context.

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": {
      "agent": "<agent>",
      "error": "<error>"
    },
    "name": "debug_with"
  }
}

Input Schema

NameRequiredDescriptionDefault
codeNoRelevant code context
agentYesAgent to debug with
errorYesError message or description
contextNoAdditional context (stack trace, logs, etc.)
timeoutNoTimeout in ms

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observedv1.2.2

TDQS

B3.4/5.0
Behavior2/5

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

With no annotations, the description must carry the burden of behavioral disclosure. It merely states the action and gives no detail about side effects (e.g., external agent invocation), output format, or potential long-running behavior. This is insufficient for a tool that likely calls another agent.

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 two short sentences, front-loaded with the core purpose, and contains no empty filler. Every word contributes to understanding the tool's purpose.

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

Completeness2/5

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

Given the absence of an output schema and annotations, the description leaves critical questions unanswered: what does the tool return, how does the agent receive input, what does the timeout control, and what counts as 'code context'? For a 5-parameter tool, this is an under-specified description.

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 explains each parameter. The description's mention of 'error and optional code context' adds no extra meaning beyond the schema, aligning with the baseline of 3.

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 states a specific verb ('debug') and resource ('an error'), clearly distinguishing this from siblings like ask_agent or explain_with. The phrase 'using a specific agent' further clarifies the mechanism without being a tautology.

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 a use case—when you have an error to debug with a specific agent—but does not explicitly state when to prefer this tool over alternatives such as ask_all or delegate_task. No exclusions or comparisons are provided.

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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