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NSTOK AI Software Factory MCP Server

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by nstok-id

run_lint

Run linting and static analysis on an NSTOK repository to detect code issues and enforce standards. Specify the repository to validate.

Instructions

Run linting and static analysis on an NSTOK repository.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
repositoryYesRepository name to run static analysis and linting for

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observedv1.0.0

TDQS

C2.9/5.0
Behavior2/5

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

No annotations are provided, so the description carries the full behavioral burden, and it discloses almost nothing. It does not say whether linting is read-only or can auto-fix/rewrite files, whether it blocks or reports, what happens on failure, or whether the repository must exist locally. Only 'static analysis' hints at a non-mutating read, which is a thin signal.

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 front-loaded sentence with no filler or redundancy. It is efficient, though so terse that conciseness edges toward under-specification rather than crisp completeness.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Completeness3/5

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

For a one-parameter tool with full schema coverage and no output schema, the definition is minimally sufficient to invoke correctly. It is missing outcome context — what the tool produces, how diagnostics are surfaced, and whether failure is expected behavior — that an agent would want before committing to a lint run.

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?

With one parameter and 100% schema description coverage, the schema already documents 'repository' fully. The description adds only indirect value by naming the target ecosystem ('NSTOK repository'), which lightly clarifies what a valid repository value looks like, but adds no format or naming specifics.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Purpose4/5

Does the description clearly state what the tool does and how it differs from similar tools?

The description states a concrete verb and resource ('Run linting and static analysis') on a clearly scoped target ('an NSTOK repository'), so an agent can tell what the tool does. It does not, however, distinguish itself from close siblings such as run_tests, run_build, or validate_architecture, which all occupy the same 'check the code' space.

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

Usage Guidelines2/5

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

There is no when-to-use guidance, no preconditions (e.g. code must already be written or a branch checked out), and no mention of alternatives like run_tests or validate_architecture. The agent is left to infer that this tool is for pre-commit quality checks.

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