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set_config

Adjust model, size, output directory, or timeout settings and save them permanently. New settings take effect on the next call without a restart.

Instructions

Change settings and persist them to the config file. Call this when the user asks to switch a model, change a default size, output directory or timeout, or change provider. Only the fields passed are changed and everything else is preserved. Changes take effect on the next call with no restart.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
apiKeyNoAPI key to store. Write-only: no tool ever returns it. Omit to keep the current key.
baseUrlNoAPI base URL override. Omit to use the provider default.
providerNoProvider id. Known: ark.
imageSizeNoDefault image size as WxH, for example 1024x1024.
outputDirNoDefault output directory. Set to an empty string to fall back to <workspace>/image_output.
imageModelNoDefault image model id.
videoModelNoDefault video model id. Video is generated only by an explicit generate_video call.
imageTimeoutMsNoDefault budget for one image call, in milliseconds. Raise it for a slow provider.
videoTimeoutMsNoDefault budget for the whole video flow, in milliseconds. A five second clip measured about four minutes.

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observedv0.2.0

TDQS

A4.2/5.0
Behavior4/5

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

No annotations are provided, so the description carries the full disclosure burden, and it does substantial work: it discloses persistence ('persist them to the config file'), partial-update semantics ('Only the fields passed are changed and everything else is preserved'), and effect timing ('Changes take effect on the next call with no restart'). It does not cover behavior on invalid values or error responses, which keeps it at a 4.

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?

Three sentences, each earning its place: the first states the core action, the second gives when-to-use triggers, the third clarifies semantics and effect timing. Information is front-loaded and there is zero filler or redundancy.

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?

For a 9-parameter, all-optional config tool with no annotations and no output schema, the description covers purpose, invocation triggers, persistence, partial-update behavior, and effect timing, while the schema fully documents every parameter. The main gap is the absence of any statement about return values or failure/validation behavior, but nothing critical for correct invocation is missing.

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 every parameter already carries a meaningful description in the schema itself, setting the baseline at 3. The description adds a small but useful cross-parameter semantic — 'Only the fields passed are changed' — clarifying that omitted parameters are preserved, but it does not need to and does not duplicate param-level detail.

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 ('Change settings and persist them to the config file') and elaborates with concrete use cases: 'switch a model, change a default size, output directory or timeout, or change provider.' This clearly differentiates it from siblings generate_image and generate_video (generation tools) and get_config (read-only access), so an agent can distinguish them without opening schemas.

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?

The description gives explicit trigger conditions ('Call this when the user asks to switch a model, change a default size, output directory or timeout, or change provider'), which is clear, actionable guidance. It does not explicitly name get_config as the alternative for reading config or state when not to call the tool, so it stops short of the full 5, but the context is unambiguous.

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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