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pipeline-doctor

pipeline-doctor

by SaadInamdar7
OverviewSchemaSourceRelated ServersDiscussionsAdmin
Python
Remote

diagnose_mwaa_environment

Fetches read-only MWAA worker and network settings to diagnose a supplied error or symptom and identify likely causes with fixes.

Instructions

Fetch MWAA worker and network settings (read-only) and diagnose the given error or symptom.

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": {
      "name": "<name>",
      "error": "<error>"
    },
    "name": "diagnose_mwaa_environment"
  }
}

Input Schema

NameRequiredDescriptionDefault
nameYes
errorYes
use_llmNo

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observedv0.1.0

TDQS

B3.1/5.0
Behavior3/5

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

With no annotations, the description at least discloses that the fetch is read-only. It does not state required permissions, whether diagnosis invokes an LLM, rate limits, or what output the agent should expect.

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?

One front-loaded sentence with no filler. It is structurally efficient, though its brevity contributes to the semantic gaps noted elsewhere.

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?

For a 3-parameter diagnostic tool with no annotations and no output schema, the description is thin. It omits the meaning of use_llm and does not describe the diagnosis result, leaving the agent without enough context to invoke it confidently.

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

Parameters2/5

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

Schema coverage is 0% and the description only loosely maps inputs: 'given error or symptom' explains the error parameter and 'MWAA environment' implies name. The use_llm parameter is never mentioned, so a significant input remains undocumented.

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?

Names a specific verb (diagnose) and resource (MWAA environment), and adds that it fetches worker and network settings. The MWAA specificity distinguishes it from the other diagnose_* siblings, though it does not explicitly route among them.

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 phrase 'diagnose the given error or symptom' implies use for MWAA failures, but gives no explicit when-not conditions and does not name any alternative tool such as diagnose_incident or list_failure_patterns.

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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