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SKILL.md Lint

by com.moltlinestudio

Cron Explain

cron_explain
Read-onlyIdempotent

Explain a 5-field cron expression in plain English and flag mistakes. FREE.

Typical input {"expression": "0 9 * * 1-5"} returns {"expression": "0 9 * * 1-5", "meaning": "at minute 0; at hour 9; every day of month; every month; day of week 1-5", "issues": ["none"]}; out-of-range fields are listed in "issues".

Use to read a schedule back in plain English before trusting it. Assumes 5-field cron; not for 6-field or seconds-precision variants. Errors: on invalid, missing, or malformed input this tool never raises a protocol error — it returns {"error": ""} (for example {"error": "expected 5 fields, got "}). Every call is read-only and idempotent, so after correcting the input it is always safe to retry.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
expressionYesA standard 5-field cron string (minute hour day-of-month month day-of-week), e.g. "0 9 * * 1-5"; must be non-empty.

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault

No arguments

TDQS

A4.9/5.0
Behavior5/5

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

The description adds significant behavioral context beyond annotations: it explains error handling ('never raises a protocol error — it returns an error object'), reaffirms idempotency and read-only nature, and provides example output. Annotations already indicate readOnlyHint, idempotentHint, and destructiveHint, but the description enriches understanding.

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 concise (approximately 150 words) and well-structured: purpose first, then example, usage guidance, and error behavior. Every sentence contributes meaning, with no redundancy. The 'FREE' is minor but not distracting.

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

Completeness5/5

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

Given the tool's simplicity (one parameter, clear annotations, output schema exists), the description is complete. It provides example output, error handling details, and usage context, leaving no gaps for an agent to determine how to invoke the tool correctly.

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?

The input schema covers the parameter with a detailed description (100% coverage). The description adds value with an example and clarifies the expected cron variant ('Assumes 5-field cron; not for 6-field or seconds-precision variants'), which informs valid parameter values. This goes beyond the schema baseline of 3.

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 explains a 5-field cron expression in plain English and flags mistakes. The verb 'explain' and resource 'cron expression' are specific, and the tool is distinct from unrelated siblings.

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?

The description provides explicit usage guidance: 'Use to read a schedule back in plain English before trusting it.' It also clearly states when not to use: 'not for 6-field or seconds-precision variants.' This is sufficient given no similar sibling tools exist.

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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TDQS

A4.7/5.0
Disambiguation5/5

Each tool has a clearly distinct purpose: cron explanation, text diffing, JSON validation, skill linting, packaging layout validation, and regex testing. There is no functional overlap, so an agent can easily select the correct tool.

Naming Consistency5/5

All tool names follow a consistent verb_noun pattern in snake_case (e.g., cron_explain, diff_texts, lint_skill). The naming convention is uniform and predictable across the entire set.

Tool Count5/5

With only 6 tools, the server is well-scoped for its linting and validation purpose. Each tool is justified and contributes to the overall functionality without redundancy or excessive bloat.

Completeness4/5

The tool set covers the primary validation needs for skills (linting, packaging, and auxiliary utilities like cron, diff, JSON, regex). Minor gaps could include a tool for validating skill dependencies or conformance to a specific schema, but the core workflows are well-supported.

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