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ossenna-hq

ltspice-mcp

by ossenna-hq

run_simulation

Run SPICE simulations on netlist files, automatically handling raw/log outputs and returning parsed results or a job ID for longer runs.

Instructions

Run a SPICE simulation on a netlist file. Sets the right batch flags, handles the ngspice headerless-raw dialect, routes the raw/log artifacts, and parses the results — so you never hand-parse a rawfile. Automatically runs synchronously for short simulations (<=30s timeout) or asynchronously for longer ones. Use wait=true to force synchronous execution. Returns raw/log file paths and simulation summary on completion, or a job ID for async tracking.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
waitNoForce synchronous execution. Blocks until completion or hard timeout.
formatNoResponse format: 'json' for structured data, 'text' for human-readable
netlistYesPath to the netlist file (.cir, .net, .asc)
timeoutNoTimeout in seconds (defaults to the server's configured default, 300s). Simulations exceeding 30s run asynchronously unless wait=true. With wait=true the effective limit is min(this timeout, 600s): 600s is a hard ceiling, not a floor — pass a larger timeout to use the full 600s.

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault
errorNo
rangeNo
errorsNo
job_idNo
statusNo
fourierNo
netlistNo
signalsNo
durationNo
log_fileNo
raw_fileNo
sim_typeNo
warningsNo
simulatorNo
step_countNo
meas_errorsNo
point_countNo
measurementsNo
observationsNo
failed_measurementsNo
Behavior4/5

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

Annotations indicate it's not read-only, not idempotent, and not destructive. The description adds context about setting batch flags, handling the ngspice headerless-raw dialect, routing artifacts, and sync/async execution. It does not contradict annotations and provides useful operational details, though error handling is not covered.

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?

The description is a single substantial paragraph, front-loaded with the core purpose. It's structured with clear sentences about execution modes and return values. It's slightly verbose but every sentence adds value; no filler. A more concise version could trim details, but it's not excessive.

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?

Given the tool's complexity and the presence of an output schema, the description covers essential context: sync/async behavior, timeout semantics, and return types. It explains why to use this tool (avoid parsing rawfiles) and how it handles long simulations. It's complete enough for an agent to effectively invoke and understand the outcome, though it doesn't mention error scenarios or partial failures.

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 baseline is 3. The description enriches semantics by clarifying timeout defaults, the 30s async threshold, and the 600s hard ceiling with wait=true. It also explains that wait=true forces sync execution, adding meaning beyond the schema descriptions.

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?

The description clearly states the tool runs a SPICE simulation on a netlist file, handles ngspice-specific details, and parses results. It distinguishes from siblings like run_sweep and run_montecarlo by explicitly focusing on a single simulation and automating rawfile parsing.

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?

It explains when to use synchronous vs asynchronous execution (short vs long simulations) and mentions wait=true to force sync. While it doesn't explicitly list alternatives, the context makes it evident this is for single simulations, with siblings for sweeps/montecarlo. It gives clear guidance on timeout behavior.

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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