DecisionLint: Jev/Luna Lint

Lint Jev and Luna decision-model questions, or ask the model to check them with your key.

Connector by nolindnaidoo · GitHub account verified by the MCP Registry

IndexedMITLocal (stdio)★ 1

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Works with Claude Code, Codex, VS Code, Cursor, Windsurf, Claude Desktop. Read the repository before you give any tool access to your data.

npx agentmarket install connector/nolindnaidoo-decisionlint

Asks which of your tools to add it to (Claude Code, Codex, Cursor, VS Code, Windsurf, Gemini CLI, Claude Desktop) and shows the change first. See https://agentmart.dev/cli.

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About

Lint Jev and Luna decision-model questions, or ask the model to check them with your key.

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Permissions

What this server can do and what it asks for, from its tool list, install config and code. Checked Oct 25, 2026.

Tools: 6 read · 2 write · 0 delete
Secrets: None asked for
Install scripts: None found
Runs as: Node.js package

Tools by what they do 8

Read from the source code; the running server may list different tools.

Read 6 · Look things up without changing anything.

ask_model
explain_rule
lint_paths
lint_text
list_rules
plan_ask

Write 2 · Create, change, send or run things.

fix_text
probe_question

Files it touches

/dev/stderr
Your home directory (~)

Tools (8)

Read from the source code; the running server may differ. Descriptions are the server’s own words; hidden characters are shown as [U+…].

ask_modelCheck with the model
Ask the model itself, TypeSafe's Jev or OpenAI's Luna, to check the questions in the given text or paths after linting them: overlapping options, a question that needs counting, a label that does not match its description, and the other checks list_rules marks runsHere: false. This sends the questions to the vendor with the user's own API key and costs money, so call it only when the user asks for a check with Jev or Luna, never on every edit, and use plan_ask first when the cost matters. The key is read from the platform's own variable, TYPESAFE_API_KEY, OPENAI_API_KEY, OPENROUTER_API_KEY, AI…
explain_ruleExplain a rule
A rule's own page, as Markdown: what it catches, an example that is flagged with the message the linter gives, one that is not, how to fix it and how to silence it. Use it before making a fix that fix_text leaves to you, or before silencing a finding.
fix_textFix text
Apply the safe fixes to a request body or source code passed as text, and return the mended text with how many findings were mended and the report of what is left. A safe fix only mends what the API would refuse: a criteria key written yes where it takes true, a mistyped question type, criteria in the wrong shape. A fix that changes what a working request does, such as adding a fallback option or pinning a model, is never applied here. It stays in the report with its edit marked safe: false, for you to make or to leave. Nothing is written to disk and nothing is sent over the network.
lint_pathsLint files
Lint the Jev and OpenAI Decisions questions in files or directories on disk. A directory is searched for the file types the linter reads. Returns the same report as lint_text, one entry per file. It sends nothing over the network.
lint_textLint text
Lint questions written for a decision model before they are sent: TypeSafe's Jev (System One, /v1/systemone) and OpenAI's Decisions API (gpt-6-luna, /v1/decisions), in either request shape, or the Vercel AI SDK's decide() for both. Pass a request body as JSON, or source code that builds one. Returns each finding with its rule, message, position and docs link, the edit that would mend it when there is one, plus how many questions were found and how many could not be read in full. Use it after writing or changing a question. It sends nothing over the network.
list_rulesList rules
List every rule with its code, name, what it catches, default level, its own page with an example, the vendor page behind it, and whether it runs offline here or only when ask_model asks the model.
plan_askPlan a check with the model
Say what ask_model would send for the given text or paths, and send nothing: how many requests, to which model, about how many input tokens, how many questions are held back for having a part built at runtime, and how many fall past maxCalls. Needs no key. Call it first when the user wants to know the cost of a check before paying for it.
probe_questionProbe a question
Send one question to Jev several times, as written and with its layout changed, options reversed, labels hidden, levels reversed, criteria removed, to see whether the answer holds. Returns a report as Markdown with a verdict and which variants moved the decision. The text must carry the state the question is asked against, and when it has more than one question, questionId names the one. Asks Jev only, about a dozen requests, with the user's TypeSafe key found the way ask_model finds it. It costs money, so call it only when the user asks to probe a question.