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Quinn's Conveyance — Paid ComfyUI Knowledge MCP

by io.github.jkomalleyjr
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get_chaining_rule

Get the verified rules for chaining AI video clips into a continuous sequence (MiniMax H3 / Wan). Covers true-last-frame chaining, crossfade vs hard cut decisions, and prompting for pace continuity. Use when assembling multi-clip sequences. Do NOT use for single-clip generation. Costs $0.005 per call, paid in USDC on Base via x402.

Tool call template

Replace each placeholder with a value matching the input schema. Only required parameters are included; add optional parameters as needed.

{
  "id": 1,
  "jsonrpc": "2.0",
  "method": "tools/call",
  "params": {
    "arguments": {
      "query": "<query>"
    },
    "name": "get_chaining_rule"
  }
}

Input Schema

NameRequiredDescriptionDefault
queryYesYour error message, question, or topic.

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observed

TDQS

A4.3/5.0
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 burden. It discloses a meaningful behavioral trait beyond the schema: the $0.005 per-call cost and the USDC-on-Base/x402 payment path, which an agent must know before invoking repeatedly. It does not describe the shape of the returned rule text, leaving that gap open.

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?

Four short sentences, front-loaded with the capability and its covered topics before usage guidance and the cost note. Every sentence carries distinct information with no filler.

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?

For a one-parameter lookup tool with no output schema, the description states what it retrieves, the domains it covers, when to use it, when not to, and the invocation cost. There is no output schema, so return-value explanation is not required; nothing critical 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% and there is a single 'query' parameter, so the schema already documents it ('Your error message, question, or topic'). The description adds no syntax, format, or constraint detail for that parameter, so the baseline 3 applies.

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 ('Get the verified rules for chaining AI video clips') and enumerates the covered sub-topics (true-last-frame chaining, crossfade vs hard cut, pace continuity). An agent can immediately distinguish it from the diagnostic/recipe siblings.

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 an explicit positive trigger ('Use when assembling multi-clip sequences') and an explicit exclusion ('Do NOT use for single-clip generation'), which is a strong when/when-not pair. It does not name a concrete alternative sibling for the single-clip case, so it falls just short of 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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