Skip to main content
Glama
richashworth

tlaplus-mcp

by richashworth

pcal_translate

Translates PlusCal algorithms embedded in TLA+ files into TLA+ by updating the file in-place between translation markers.

Instructions

Translate PlusCal algorithm embedded in a TLA+ file to TLA+. Modifies the .tla file in-place by inserting/updating the TLA+ translation between the * BEGIN TRANSLATION and * END TRANSLATION markers.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
tla_fileYesAbsolute path to the .tla file containing PlusCal code
fairnessNoFairness condition: wf (weak), sf (strong), wfNext (weak on Next), nof (none)nof
terminationNoAdd termination detection to the spec
no_cfgNoDo not generate a .cfg file
labelNoAdd missing labels automatically
line_widthNoLine width for the translation output
output_fileNoOptional. If provided, raw pcal.trans output is written to this file and the response contains output_file instead of raw_output. (Note: this is the raw TRANSLATOR output — the translated TLA+ spec is always written in-place to tla_file, reported as translated_file.)
Behavior3/5

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

No annotations provided, so the description carries full burden. It discloses that the file is modified in-place and that translation is placed between specific markers. However, it does not cover prerequisites, error conditions, or what happens if markers are missing, leaving some gaps.

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?

The description is two sentences: the first defines the main action, the second adds key details about in-place modification. No redundant or extraneous information.

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 complexity (7 parameters, no output schema), the description covers the essential purpose and main behavior. It could be improved by mentioning prerequisites or error handling, but it is largely complete for typical use.

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?

All 7 parameters have descriptions in the schema (100% coverage). The description adds no extra parameter information beyond the schema, so baseline score of 3 is appropriate.

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 explicitly states the verb 'Translate' and the resource 'PlusCal algorithm embedded in a TLA+ file'. It distinguishes this tool from siblings like tla_evaluate or tla_parse by specifying it handles PlusCal translation and modifies the file in-place.

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?

Indicates that the tool modifies the .tla file in-place, which implies when it should be used (translation step). It does not explicitly state when not to use or provide alternatives, but the context and sibling names suggest clear use cases.

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

Install Server

Other Tools

Latest Blog Posts

MCP directory API

We provide all the information about MCP servers via our MCP API.

curl -X GET 'https://glama.ai/api/mcp/v1/servers/richashworth/tlaplus-mcp'

If you have feedback or need assistance with the MCP directory API, please join our Discord server