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observe-instrument-mcp

observe-instrument-mcp

by alanzha2
OverviewSchemaSourceRelated ServersDiscussionsAdmin
Python
Local

check_instrumentation

Read-onlyIdempotent

Audit a Python AI agent file to identify missing ioa-observe-sdk instrumentation and receive specific recommendations.

Instructions

Audit a Python AI agent file for missing ioa-observe-sdk instrumentation.

Read-only — does not modify the file. Use instrument_agent to apply changes.

Args: file_path: Path to the Python file to audit.

Returns: Audit report: what is present, what is missing, and specific recommendations.

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": {
      "file_path": "<file_path>"
    },
    "name": "check_instrumentation"
  }
}

Input Schema

NameRequiredDescriptionDefault
file_pathYes

Output Schema

NameRequiredDescriptionDefault
resultYes

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observedv0.1.2

TDQS

A4.7/5.0
Behavior4/5

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

Annotations already declare readOnlyHint=true, destructiveHint=false, idempotentHint=true. The description adds context about the audit scope (missing instrumentation) and the return content (audit report with specifics), which goes beyond the annotations.

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?

Three sentences: purpose, read-only note with sibling link, and args/returns. Front-loaded main purpose, 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 one parameter, implied output schema, and sibling tool, the description covers purpose, behavior, parameters, and return value. No missing context for proper use.

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?

Schema description coverage is 0%, but the description's 'Args' section explains that 'file_path' is 'Path to the Python file to audit', adding meaning beyond the schema's type and title.

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 uses a specific verb 'Audit' and resource 'Python AI agent file', specifying the scope 'for missing ioa-observe-sdk instrumentation'. It clearly distinguishes from the sibling tool 'instrument_agent' by stating 'Read-only — does not modify the file'.

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

Usage Guidelines5/5

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

Explicitly states 'Read-only — does not modify the file' and 'Use instrument_agent to apply changes', providing clear when-to-use and when-not-to-use guidance with an explicit alternative.

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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