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MagicTurtle-s

o365-Admin MCP

list_skills

Discover available skills and resource references for Microsoft 365 administration, providing API patterns, best practices, and endpoint-specific documentation.

Instructions

Returns available skills and resource references. Skills contain API patterns and best practices. Resources contain endpoint-specific documentation for different Microsoft 365 services.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault

No arguments

Schema Changelog

Changes observed during successful MCP inspections. Dates show when Glama detected each change.

  1. First observedv1.0.0

TDQS

A3.7/5.0
Behavior3/5

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

With no annotations, the description carries the full burden. It accurately conveys that the tool returns available skills and resource references, and it clarifies what those items contain. It does not mention side effects, ordering, caching, or whether the list is exhaustive, but for a simple zero-parameter list operation this is acceptable but not deeply transparent.

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?

Two short sentences, front-loaded with the primary behavior, and each sentence adds useful information: what is returned and what those returned items mean. No filler or redundancy.

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

Completeness4/5

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

For a parameterless list tool, the description gives enough context to understand the output domain: skills are API patterns/best practices and resources are endpoint-specific docs. The absence of an output schema is partially mitigated by this description, though it does not describe response format or pagination.

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 schema coverage is 100%, so there are no parameter semantics to document. The description earns its points by explaining what the returned data represents, which is the main semantic value an agent needs.

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 uses a clear verb ('Returns') and names the resources ('skills and resource references'), with additional explanation of what skills and resources are. It is distinguishable from read_skill by being a list operation, though it does not explicitly contrast itself with siblings.

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 'Returns available skills and resource references' implies a discovery/list use, which an agent can infer as a precursor to read_skill, graph_api_call, or powerplatform_api_call. However, the description does not explicitly state when to use this tool versus alternatives or give any exclusions.

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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