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ap_list_ai_models

ap_list_ai_models
Read-onlyIdempotent

List configured AI providers and their available models. Use this to discover valid provider and model values for configuring Run Agent steps. The output shows provider names and model IDs needed for the aiProviderModel input.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
providerNoFilter by provider name. Omit to list all configured providers and their models.

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observed

TDQS

A4/5.0
Behavior3/5

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

Annotations already declare readOnlyHint=true, idempotentHint=true, destructiveHint=false and openWorldHint=false, so the safety profile is fully covered. The description adds that the output enumerates provider names and model IDs, which is modest but real added context for a read tool. It does not mention auth/permission needs or whether unconfigured providers appear.

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?

Three short sentences, front-loaded with the purpose and followed by use case and output shape. All three earn their place, though the first and third sentences partially overlap in describing what is returned.

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?

For a no-required-param, read-only listing tool with full schema coverage and no output schema, the description supplies the missing piece — what the response contains (provider names and model IDs). An agent has everything needed to select and call it correctly.

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

Parameters3/5

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

Schema description coverage is 100%: the single `provider` enum parameter is fully documented, including the default behavior when omitted. The description adds nothing about the filter beyond what the schema already says, so the baseline 3 applies.

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?

States a precise verb and resource ('List configured AI providers and their available models') and goes further to name the downstream purpose (discovering valid values for Run Agent steps). No sibling tool in the set covers AI provider/model discovery, so the tool is unambiguously distinguishable.

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

Usage Guidelines4/5

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

'Use this to discover valid provider and model values for configuring Run Agent steps' gives clear, actionable context for when to reach for this tool. There is no when-not guidance or named alternative, but none is needed since no sibling overlaps this capability.

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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