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configure_asset_vision

Define an optional OpenAI-compatible vision endpoint for analyzing assets, storing credentials in the OS store.

Instructions

Configure an optional OpenAI-compatible vision endpoint. Credentials stay in the OS store.

Input Schema

NameRequiredDescriptionDefault
modelNo
api_keyNo
endpointNo

Schema Changelog

Changes observed during successful MCP inspections.

  1. Addedv0.9.1

TDQS

C2.8/5.0
Behavior2/5

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

No annotations are provided, so the description carries the full behavioral burden. It does add one genuinely useful fact beyond structure — credentials are stored in the OS store, not returned or persisted inline — but omits whether an existing endpoint is overwritten, whether null values clear or preserve current settings, and whether the endpoint is validated on save.

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, zero filler, with the core purpose front-loaded and the storage guarantee as the follow-up. Every clause earns its place.

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 configuration-writing tool with three undocumented parameters, no annotations, and no output schema, the description is thin: it does not explain the effect of omitting each parameter, whether configuration is additive or replacing, or how success/failure is surfaced.

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 description coverage is 0% across three parameters (model, api_key, endpoint). The description only obliquely maps to two of them — 'vision endpoint' gestures at endpoint and 'credentials' at api_key — and says nothing about model choice, accepted formats, or the meaning of the null defaults.

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 (Configure) and resource (an optional OpenAI-compatible vision endpoint), so an agent knows exactly what this tool changes. No sibling performs vision-endpoint configuration, so differentiation is implicit rather than stated.

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

Usage Guidelines2/5

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

The word 'optional' hints that a vision endpoint is not mandatory, but there is no explicit when-to-use guidance, no prerequisite conditions, and no mention of alternatives or what happens if it is never configured. The agent must infer the entire trigger context.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.