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lmcp_doctor

Diagnose and resolve issues with AI app connections, macOS permissions, and integrations so AI agents can use your Mac as expected.

Instructions

Checks everything LMCP depends on on this Mac — the AI apps connected to it, macOS permissions, each integr...

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault

No arguments

Schema Changelog

Changes observed during successful MCP inspections.

  1. Addedv3.0.410

TDQS

C2.8/5.0
Behavior2/5

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. The verb 'Checks' suggests a read-only inspection, but the description does not explicitly state that it makes no modifications, whether it requires elevated permissions, or what side effects might occur. The truncated 'each integr...' also leaves the behavioral scope incomplete.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Conciseness2/5

Is the description appropriately sized, front-loaded, and free of redundancy?

The description is front-loaded with the main verb and subject, but it is visibly truncated mid-sentence ('each integr...'), making it grammatically incomplete. While brevity is good, an unfinished thought reduces clarity and looks like a drafting error rather than intentional conciseness.

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 tool with no output schema and no annotations, the description should explain what the check produces or how results are presented. It does not mention return format, severity of findings, or next steps. It also fails to clarify scope boundaries that would differentiate it from the many diagnostic-related siblings in the tool list.

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?

The tool has zero parameters and an empty schema, so there is nothing for the description to explain. Per the baseline for parameterless tools, a score of 4 is appropriate since no semantic overhead exists.

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 gives a specific verb ('Checks') and a defined resource ('everything LMCP depends on on this Mac'), followed by concrete examples (AI apps, macOS permissions, integrations). It clearly indicates this is a comprehensive dependency check. However, it does not explicitly distinguish itself from similar diagnostic siblings like run_diagnostics, permissions_status, or lmcp_upgrade_diagnostics, and the term 'everything' is broad.

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?

No when-to-use or when-not-to-use guidance is provided. The description implies a comprehensive health-check use case but never mentions alternatives such as permissions_status, list_missing_permissions, or run_diagnostics, nor the conditions that would make one more appropriate than the others.

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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