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logisim

logisim

by n0n3o
OverviewSchemaSourceRelated ServersDiscussionsAdmin
Python
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logisim_render

Render a Logisim-evolution .circ circuit as a PNG image, optionally setting inputs or running clock cycles first, so you can visually verify wire values and circuit behavior.

Instructions

Render a circuit as a PNG picture (wire colours show values), optionally after setting inputs or running steps; optionally save the picture to a file.

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": {
      "path": "<path>"
    },
    "name": "logisim_render"
  }
}

Input Schema

NameRequiredDescriptionDefault
pathYesPath to the .circ file (absolute, or relative to the working folder)
scaleNoImage scale (default 1.5, reduced automatically for large circuits)
stepsNoSimulation steps, in order
inputsNoInput name -> value (integer; multi-bit pins take the whole number, e.g. 5 or "0x1F")
circuitNoCircuit inside the file (default: the main circuit)
save_toNoAlso write the PNG here

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observedv2.0.0

TDQS

A3.5/5.0
Behavior3/5

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 useful behavior (wire colours depict values, scale auto-reduced for large circuits is in the schema not description, optional file save). However, it does not state whether rendering requires the simulator to be loaded, whether state changes from inputs/steps persist, or what the response looks like. Adequate but incomplete.

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?

A single well-structured sentence that front-loads the core action and appends optional behaviors. No wasted words; every clause adds meaning.

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?

For a 6-parameter visualization tool with nested objects and no output schema, the description covers purpose and options but leaves behavioral gaps (persistence of input/step state, failure modes, return format). No annotations to fall back on. Adequate but not complete.

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 each parameter is fully documented in the schema. The description adds only framing (optional input setting/steps/save) without parameter-level detail, which is the baseline when the schema does the heavy lifting.

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+resource (render a circuit as PNG) and adds meaningful detail (wire colours show values, optional input setting/stepping/saving). It is distinguishable from siblings like logisim_inspect or logisim_verify, though it doesn't explicitly name them for contrast.

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?

Usage is implied by the description (render for visualization, optionally set inputs or run steps), but there is no explicit when-to-use or when-not-to-use guidance versus alternatives like logisim_inspect or logisim_simulate.

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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