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tt-P607

novelai

by tt-P607
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Python
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novelai_encode_vibe

Encode an image into a reusable vibe binary via the official encode-vibe API, with optional masks, focus/noise seeds, and information extraction, returning a local .bin file for vibe transfer.

Instructions

Encode an image into a reusable vibe binary with the official encode-vibe API. Supports masks, extraction, focus/noise seeds. Returns a local .bin for mode=vibe. Sends selected assets to NovelAI and may spend credits. Verified free operations need no extra approval; paid/unknown prices return an approval plan. No automatic retry.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
filesNoBind local files to official JSON fields without pasting base64 into chat.
requestYes
cost_approvedNoTrue only after the user explicitly approves this operation's credit spend or unknown price, dimensions and sample count. Verified free requests do not need this flag. Read-only subscription/quote checks may run before approval.
high_resolution_approvedNoTrue only with explicit user consent for more than 1,048,576 output pixels per image, or an upscale whose final dimensions are not known in advance.

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observedv0.2.0

TDQS

A3.7/5.0
Behavior5/5

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

Discloses network send to NovelAI, potential credit spend, approval-plan behavior for paid/unknown prices, and no automatic retry. Complements annotations by adding cost and approval context beyond the readOnly and openWorld hints.

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-loads the purpose, then lists capabilities, output, and cost/retry details. Slightly listy and has minor overlap between the credit-spend and approval-plan sentences.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Completeness3/5

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

Covers the return format (local .bin) and side effects, but omits explanation of high_resolution_approved and the files binding. For a complex, multi-parameter tool with no output schema, notable gaps remain.

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?

Mentions masks, extraction, focus/noise seeds and mode=vibe, clarifying several request fields. With schema coverage at 75%, the description adds useful meaning but does not cover every parameter.

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 (encode) and resource (image into reusable vibe binary) and names the official API. Does not explicitly contrast with sibling generation tools, but the purpose is unambiguous.

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?

Provides operational rules for cost approval and retries but no guidance on when to choose this tool over alternatives like novelai_generate or novelai_revise. No when-to-use, when-not-to-use, or alternative selection criteria.

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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