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Copilot Studio MCP

Copilot Studio MCP

by jgt87
OverviewSchemaSourceRelated ServersDiscussionsAdmin
TypeScript
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List AI Builder prompts / models

cs_list_prompts

List AI Builder models and custom prompts in a Copilot Studio environment and return IDs for cs_add_tool type 'prompt'.

Instructions

pac copilot model list: AI Builder models (including custom prompts) in the environment, with ids for cs_add_tool type 'prompt'.

Tool call template

This tool declares no required parameters. Add optional parameters from the input schema as needed.

{
  "id": 1,
  "jsonrpc": "2.0",
  "method": "tools/call",
  "params": {
    "arguments": {},
    "name": "cs_list_prompts"
  }
}

Input Schema

NameRequiredDescriptionDefault
searchNo
activeOnlyNo
environmentNoEnvironment id or URL; default active pac profile

Schema Changelog

Changes observed during successful MCP inspections.

  1. Changed1 schema field changedv0.1.8
    • removedInput schema / additionalProperties
      Removed value: -false
  2. First observedv0.1.5

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 carries the full burden. It does disclose what the listing contains (AI Builder models plus custom prompts, with ids) and the downstream consumer (cs_add_tool). It says nothing about permissions, scope of the environment, pagination, or how search/activeOnly alter results.

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?

A single front-loaded sentence with no filler; the resource being listed comes first and the downstream use follows. Slightly compressed/telegraphic style but nothing wasted.

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 list tool with three parameters, no output schema, and no annotations, the description leaves filtering semantics, scope, and result shape unexplained. An agent cannot tell what search or activeOnly do or what the returned entries look like.

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 only 33% – just 'environment' is documented. The description adds no meaning for 'search' or 'activeOnly', leaving two of three parameters unexplained in both schema and description. It does not compensate for the coverage gap.

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?

States a specific verb+resource: listing AI Builder models (including custom prompts) in the environment. It also distinguishes itself by tying the output to cs_add_tool type 'prompt', which no sibling list tool does. The 'pac copilot model list' prefix is jargon but doesn't obscure the purpose.

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?

Implies usage by saying the listing yields ids for cs_add_tool type 'prompt', so an agent can infer this is the lookup step before adding a prompt tool. However there is no explicit when-to-use/when-not guidance and no stated alternative for enumerating prompts.

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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