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logisim

logisim

by n0n3o
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Python
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logisim_truth_table

Simulate all input-pin combinations for a Logisim circuit (up to 16 bits) to generate a truth table for outputs, LEDs, and probes plus minimal DNF/CNF formulas for 1-bit outputs.

Instructions

Simulate every combination of the input pins (max 16 bits; multi-bit pins count all their bits) and return the truth table of all outputs, LEDs and probes, plus the minimal DNF/CNF formula of each 1-bit output.

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_truth_table"
  }
}

Input Schema

NameRequiredDescriptionDefault
pathYesPath to the .circ file (absolute, or relative to the working folder)
circuitNoCircuit inside the file (default: the main circuit)
formulasNoDerive minimal formulas (default true)
max_rowsNoRows to print (default 64)

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observedv2.0.0

TDQS

A3.9/5.0
Behavior3/5

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

With no annotations, the description carries the full burden. It does disclose a real behavioral trait — the 16-bit cap and that multi-bit pins count all their bits — which signals the exponential blowup boundary. However, it does not say what happens when the cap is exceeded (error vs. truncation), nor mention cost/runtime for large circuits.

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?

A single sentence, front-loaded with the core action and following with limits, outputs and formula derivation. Dense but every clause adds information; the parentheticals earn their place, though the line is slightly over-packed.

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 tool with no output schema, the description does state what is returned (full truth table plus per-output formulas) and the key input constraint. Missing only edge-case behavior (over-16-bit handling) and any note on runtime, which prevents a 5.

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?

Schema coverage is 100%, so the baseline is 3. The description adds value beyond the schema by clarifying that 'formulas' yields minimal DNF/CNF of each 1-bit output and that multi-bit pins count all bits toward the 16-bit budget, which contextualizes the numeric limit that the schema only states abstractly.

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 (simulate/return) and resource (truth table of all outputs, LEDs and probes, plus minimal DNF/CNF formulas). This is clearly differentiable from siblings like logisim_simulate, logisim_verify and logisim_check, which do not advertise exhaustive truth-table generation.

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?

The description implies the use case (exhaustive simulation of small combinational circuits, capped at 16 bits) but never states when to prefer this over logisim_simulate or logisim_verify, nor any exclusions or prerequisites. Usage must be inferred from the stated limits.

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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