ModelsLab v8

Endpoint Details (V8)

endpoint-details

Read-only

Search V8 endpoint configurations and retrieve their full parameter schemas plus all
connected models that can be used with them.

Use this tool before calling a generation tool so you know:
- Exactly what `params` the endpoint expects (types, enums, defaults, required fields)
- Which `model_id` values are valid for the endpoint

Search modes:
- Provide `category` + `endpoint` slug to look up a specific endpoint.
- Provide `search` to find endpoints by name or description across all categories.
- Combine both to narrow results to a category with a keyword search.

Workflow:
1. Call this tool to get the parameter schema and available model IDs.
2. Pick a `model_id` from the `models` list in the response.
3. Call the appropriate generation tool (`image-generation`, `video-generation`,
   `audio-generation`, `3d-generation`) with `model_id`, `endpoint`, and `params`.

Input Schema

TableJSON Schema

Name	Required	Description
`limit`	No	Maximum number of endpoint configurations to return (1–20). Defaults to 10.
`search`	No	Keyword to search endpoint names and descriptions (e.g. "speech", "image turbo").
`category`	No	Narrow results to a V8 category: "images", "videos", "audios", or "3ds". Optional — omit to search all categories.
`endpoint`	No	The endpoint slug to look up (e.g. "text-to-image", "text-to-speech"). Optional — omit to return all endpoints in the category.
`model_limit`	No	Maximum number of connected models to return per endpoint, sorted by popularity (1–20). Defaults to 5.

Schema Changelog

Changes observed during successful MCP inspections.

First observedOct 2, 2026

TDQS

A4.6/5.0

Behavior4/5

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

readOnlyHint=true already establishes the safety profile, and the description usefully adds what the call returns (parameter schemas with types/enums/defaults/required fields, plus a ranked models list). It does not mention pagination behavior or describe the search matching semantics beyond keyword-vs-category, which keeps it short of a 5.

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?

Front-loaded with the core verb and the search-mode and workflow blocks are cleanly separated, so an agent can scan to the relevant part quickly. It is slightly longer than strictly necessary (the workflow restates the first line's intent), but every block carries usable information.

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?

No output schema exists, and the description compensates by enumerating what the response contains (param schema, models list). Combined with full parameter coverage and the readOnly annotation, an agent has everything needed to discover and chain into a generation call.

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?

With 100% schema coverage the baseline is 3, but the description adds real semantics the schema does not: how `category` and `endpoint` combine for a specific lookup, how standalone `search` spans all categories, and how combining both narrows results. It adds meaning beyond the field descriptions rather than restating them.

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?

The description states a specific verb and resource ('Search V8 endpoint configurations and retrieve their full parameter schemas plus all connected models'), and explicitly positions itself as a discovery prerequisite relative to the generation siblings. An agent can distinguish it from list-models/list-providers and from the generation tools without opening any schema.

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

Usage Guidelines5/5

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

It gives explicit when-to-use ('Use this tool before calling a generation tool'), a numbered workflow, and names the concrete alternatives (image/video/audio/3d-generation) with the parameters they expect. Nothing about sequencing is left to inference.

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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