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vizcom_generate_board

Generate 1–4 images from an existing prompt node directly onto its board, consuming credits; poll output IDs with vizcom_read_board to retrieve results.

Instructions

Generate 1–4 images from an existing prompt node directly onto its board. Consumes credits. Submission is never retried. Default 2k avoids Match source unexpectedly selecting 4k. Poll output IDs using vizcom_read_board.

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": {
      "workbenchId": "<workbenchId>",
      "nodeId": "<nodeId>",
      "x": "<x>",
      "y": "<y>"
    },
    "name": "vizcom_generate_board"
  }
}

Input Schema

NameRequiredDescriptionDefault
xYes
yYes
countNo
widthNo
heightNo
nodeIdYes
resolutionNo2k
workbenchIdYes

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observedv0.1.0

TDQS

A3.8/5.0
Behavior4/5

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

Adds real behavior beyond the annotations: it consumes credits, submission is never retried, and the 2k default guards against 'Match source' unexpectedly resolving to 4k. These are non-obvious operational facts an agent needs. It stops short of describing failure modes or what the returned IDs look like.

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?

Four tight sentences, front-loaded with the action and scope, then cost/retry/resolution caveats, then the polling pointer. Dense and mostly waste-free, though 'Match source' is terse enough to be ambiguous on first read.

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 credit-consuming, non-idempotent generation call with no output schema, the description covers cost, retry semantics, resolution default, and how to retrieve results. The main gap is the unexplained geometry parameters (x, y, width, height).

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 8 parameters, so the description must compensate. It only clarifies count (1–4), resolution (default 2k, source caveat) and implicitly nodeId; x, y, width, height, and workbenchId remain unexplained in both schema and description.

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 (Generate) and resource (images onto a board) plus the source constraint 'from an existing prompt node', which separates it from sibling render tools like vizcom_render_sketch and vizcom_render_pipeline.

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

Usage Guidelines3/5

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

Gives a clear follow-up path ('Poll output IDs using vizcom_read_board') and a resolution caveat, but never says when to choose this over vizcom_render_sketch, vizcom_render_pipeline, or vizcom_create_prompt_node. Usage is implied rather than contrasted with alternatives.

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