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Svel26

Sigmatek LASAL MCP Server

by Svel26

run_class2_script

Destructive

Execute arbitrary Python 2.7 batch statements against the loaded LASAL project for batch API calls not covered by apply_project_changes; save changes explicitly.

Instructions

Escape hatch: run arbitrary Python 2.7 batch statements through Lasal2.exe (module batch, project prj in scope). Use for batch API calls not covered by apply_project_changes; the project is NOT saved automatically.

Input Schema

NameRequiredDescriptionDefault
argsNoOptional arguments exposed to the script as sys.argv[1:]. Default [].
lcp_pathNoAbsolute path to the .lcp file. Omit to use the currently selected project.
script_bodyYesPython 2.7 statements executed inside the CLASS 2 batch context. `batch` (sigmatek.lasal.batch) and the loaded project `prj` are in scope; the project is closed afterwards (call batch.Save(prj) yourself if the change must persist). Example: batch.Compile(prj, batch.CompileOptions.BuildChanges)

Schema Changelog

Changes observed during successful MCP inspections.

  1. Addedv0.3.2

TDQS

A4.4/5.0
Behavior4/5

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

Annotations only supply destructiveHint=true, so the description carries real weight here and delivers: it discloses the escape-hatch nature (arbitrary code), the project-closed-afterwards lifecycle, and that persistence requires an explicit batch.Save call. It stops short of describing error behavior or what the call returns, which is a minor remaining gap rather than a contradiction.

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?

Two sentences with zero padding, and the most decision-relevant fact ('Escape hatch') is front-loaded before the routing and persistence details. Every clause earns its place.

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 an arbitrary-code execution tool with no output schema, the description covers purpose, scope, alternative, and persistence semantics well. It could say a bit more about what the caller gets back (stdout, exceptions) or failure modes, but nothing essential for invoking it 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%, so `script_body`, `args`, and `lcp_path` are already documented in the schema, and the description's mention of `batch`/`prj` scope largely echoes that. Baseline 3 is appropriate when the schema does the heavy lifting and the prose adds only reinforcement.

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+resource: run arbitrary Python 2.7 batch statements through Lasal2.exe, naming the module (`batch`) and in-scope project (`prj`). It explicitly distinguishes itself from the sibling apply_project_changes, so an agent can route correctly without opening either schema.

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

Usage Guidelines5/5

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

Gives an explicit when-to-use condition ('batch API calls not covered by apply_project_changes') and names the alternative, which is exactly the routing information an agent needs. It also flags the persistence caveat ('the project is NOT saved automatically'), which is a usage-relevant warning rather than pure prose.

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