Skip to main content
Glama

SKILL.md Lint

by com.moltlinestudio

Lint Skill

lint_skill
Read-onlyIdempotent

Lint one SKILL.md file the way marketplaces and agents parse it. FREE.

Checks YAML frontmatter presence and required fields (name, description), description quality, body structure (procedure steps, rules, degradation), secret/credential leakage, injection-style phrasing, and size budget. Typical input {"content": ""} returns {"verdict": "pass" | "pass-with-warnings" | "fail", "errors": ["..."], "warnings": ["..."], "stats": {"body_words": N, "has_frontmatter": bool}}.

Use on the full text of one SKILL.md. Not for the surrounding archive layout (packaging_check). Errors: on invalid, missing, or malformed input this tool never raises a protocol error — it returns {"error": ""} (for example {"error": "content is empty — pass the full SKILL.md text including frontmatter"}). Every call is read-only and idempotent, so after correcting the input it is always safe to retry.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
contentYesThe complete SKILL.md file text, frontmatter included; must be non-empty.

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault

No arguments

TDQS

A4.8/5.0
Behavior5/5

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

Annotations already declare readOnlyHint=true, idempotentHint=true, and destructiveHint=false. The description adds rich behavioral details: error handling (returns error object, never protocol error), idempotency (safe to retry), and input constraints, going well beyond annotations.

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?

The description is front-loaded with the core action and additional info, but slightly verbose with example output details that could be shifted to an external doc. Still, every sentence adds value and the structure is clear.

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 single parameter, rich annotations, and output schema, the description fully covers input, output, error handling, and idempotency. No gaps remain for an agent to misuse this tool.

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?

Schema coverage is 100% with a clear description for content. The description adds value by specifying the input format ('full SKILL.md text'), typical usage example, and what happens with invalid input, which is beyond the schema.

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 it lints one SKILL.md file, lists what it checks (YAML frontmatter, fields, etc.), and distinguishes it from the sibling packaging_check, which is about the archive layout.

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?

Explicitly says 'Use on the full text of one SKILL.md' and 'Not for the surrounding archive layout (packaging_check)', providing a direct alternative and clarifying scope.

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

All SKILL.md Lint toolsInspect
Try in Browser
RayrunBuild, deploy, and operate MCP servers without becoming an infrastructure team.ray.runAd

Glama MCP Gateway

Add one secure layer between your agents and this server.

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.

Resources