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Validate a custom model endpoint

validate_custom_model
Read-only

Validate the HTTPS URL and adapter configuration for an external custom model. For OpenAI-compatible mode provide baseUrl; for custom REST use endpoint. Set probe=true only when an actual minimal request to the external provider is intended. Returns validation or probe status; credentials are transient and never stored or echoed. Requires active trial or Pro; does not perform a user prompt Send.

Input Schema

NameRequiredDescriptionDefault
modelNoOptional external model identifier for a test probe.
probeNoTrue sends a minimal external request to test the model; false only checks URL safety.
apiKeyNoOptional transient API credential, never stored or echoed.
baseUrlNoPublic HTTPS base URL for openai-compatible mode.
authModeNoCustom REST authentication method: bearer, API-key header, or none.bearer
endpointNoFull public HTTPS URL for custom-rest mode.
adapterModeYesAdapter: openai-compatible or custom-rest.
promptFieldNoJSON request field for test prompt content on custom REST endpoints.prompt
systemFieldNoJSON request field for system instructions on custom REST endpoints.system
apiKeyHeaderNoHeader name when using api-key-header authentication.x-api-key
responseTextPathNoJSON response field or path holding the generated text.

Schema Changelog

Changes observed during successful MCP inspections.

  1. Changed11 schema fields changed
    • addedInput schema / properties / adapterMode / description
      Added value: +"Adapter: openai-compatible or custom-rest."
    • addedInput schema / properties / apiKey / description
      Added value: +"Optional transient API credential, never stored or echoed."
    • addedInput schema / properties / apiKeyHeader / description
      Added value: +"Header name when using api-key-header authentication."
    • addedInput schema / properties / authMode / description
      Added value: +"Custom REST authentication method: bearer, API-key header, or none."
    • addedInput schema / properties / baseUrl / description
      Added value: +"Public HTTPS base URL for openai-compatible mode."
    • addedInput schema / properties / endpoint / description
      Added value: +"Full public HTTPS URL for custom-rest mode."
    • addedInput schema / properties / model / description
      Added value: +"Optional external model identifier for a test probe."
    • addedInput schema / properties / probe / description
      Added value: +"True sends a minimal external request to test the model; false only checks URL safety."
    • addedInput schema / properties / promptField / description
      Added value: +"JSON request field for test prompt content on custom REST endpoints."
    • addedInput schema / properties / responseTextPath / description
      Added value: +"JSON response field or path holding the generated text."
    • addedInput schema / properties / systemField / description
      Added value: +"JSON request field for system instructions on custom REST endpoints."
  2. First observed

TDQS

A4.1/5.0
Behavior4/5

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

Annotations already cover the safety profile (readOnlyHint=true, openWorldHint=true, destructiveHint=false), but the description adds real value beyond them: the probe flag triggers an actual outbound request to a third-party provider, credentials are transient and never stored or echoed, and the tool is gated behind trial/Pro. No contradiction with openWorldHint.

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?

Four dense, front-loaded sentences with no filler; the core action and mode-conditional parameters come first, followed by probe semantics, return/credential notes, and the entitlement constraint. Slightly compressed but every sentence carries information.

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?

With 11 parameters and no output schema, the description compensates by naming the return ('validation or probe status'), the credential lifecycle, and the tier requirement, while the schema covers per-field detail. It omits behavior for the custom-REST field-mapping params (promptField, systemField, responseTextPath), but those are adequately documented in the schema.

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%, so all 11 parameters are already documented. The description reiterates the baseUrl-vs-endpoint split by adapterMode and the probe semantics, which the schema itself states, and adds little syntax or format detail beyond that. Baseline 3 is appropriate when the schema carries the load.

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 specific verb and resource: 'Validate the HTTPS URL and adapter configuration for an external custom model.' It also delimits scope against the sibling run_custom_model by declaring 'does not perform a user prompt Send,' so an agent can separate validation from execution without opening either schema.

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?

Gives explicit conditional guidance: use baseUrl for OpenAI-compatible mode and endpoint for custom REST, and set probe=true only when an actual external request is intended. It also states the trial/Pro prerequisite. It stops short of naming the alternative tool (run_custom_model) or stating when NOT to validate, which keeps it below a 5.

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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