commands
The commands skill validates a Claude Code skill against DevKit standards by checking skill existence across multiple directories, verifying SKILL.md frontmatter compliance (name, description, allowed-tools, category, tags, version), and confirming proper file structure. Use this skill before publishing a new skill or after making modifications to ensure the skill meets all official DevKit requirements.
git clone --depth 1 https://github.com/giuseppe-trisciuoglio/developer-kit /tmp/commands && cp -r /tmp/commands/plugins/developer-kit-core/commands/devkit.verify- ~/.claude/skills/commandsdevkit.verify-skill.md
# Verify Skill: $1
## Overview
You are a skill validation specialist for the Claude Code Developer Kit. Your task is to perform a comprehensive
validation of the skill "$1" against all DevKit standards.
## Usage
```
/devkit.verify-skill $ARGUMENTS
```
## Arguments
| Argument | Description |
|--------------|------------------------------------------|
| `$ARGUMENTS` | Combined arguments passed to the command |
## Execution Instructions
**Agent Selection**: To execute this task, use the following approach:
- Primary: Use `general-purpose` agent with appropriate domain expertise
- Or use specialized agent if available for the specific task type
## Validation Process
Execute the following checks in sequence:
### 1. Skill Existence Check
- Search for the skill directory in the following locations (in this order):
- `.claude/skills/$1/` (project-level)
- `~/.claude/skills/$1/` (user-level)
- `./skills/**/$1/` (any category subfolder under the repo `skills/` directory — recursive search)
- Any other project-local plugin directories that the repository documents for skills (if present)
- Verify that a `SKILL.md` file exists inside the found skill directory
- Important: many development workflows (for example when authoring a Claude plugin or a shared skills repo) keep skills
under top-level `skills/` categories (e.g. `skills/langchain4j/<skill-name>`). This is an acceptable and supported
location for the purposes of validation and MUST NOT be treated as a false-positive or as a failure just because
`.claude/skills/` or `~/.claude/skills/` do not contain the skill.
- If the skill cannot be found in any of the locations above, report failure (Existence).
### 2. Requirements Conformance (@.docs/skills.md)
Check that the skill complies with all requirements from the official Skills documentation:
**SKILL.md Frontmatter:**
- `name` field: lowercase letters, numbers, hyphens only (max 64 characters)
- `description` field: present and descriptive (max 1024 characters). Description includes BOTH what the skill does AND
when to use it
- `allowed-tools` field: uses valid tool names only
- `category`: field, valid category
- `tags`: field, relevant, and descriptive (no generic tags like "skill" or "devkit")
- `version` field: uses semantic versioning (e.g., 1.0.0)
**Important:** Other frontmatter fields are not allowed.
**File Structure:**
- `SKILL.md` uses valid YAML frontmatter (opening and closing `---`)
- No YAML syntax errors (tabs, incorrect indentation)
- All referenced files in SKILL.md exist in the skill directory
- File paths use forward slashes (Unix style), not backslashes
**Content Quality:**
- Description is specific with trigger keywords (not vague/generic)
- Skill has a clear "When to Use" or "Instructions" section
- Examples are present and demonstrate the skill
- Examples (examples.md) file exists if multiple examples are provided
- Supporting files (if any) are properly referenced with Markdown links
- References (reference.md) file exists if the skill is complex
### 3. Template Adherence (@.docs/skill_template.md)
Verify the skill structure matches the template:
**Required Sections:**
- Skill name as H1 heading
- "When to Use This Skill" section with clear use cases
- "Core Concepts" or "Instructions" section
- "Examples" or practical demonstrations
- "Best Practices" or "Summary" section
**Metadata Alignment:**
- Frontmatter includes recommended fields (name, description, category, tags, version)
- Version number is present and follows semantic versioning (if included)
- Tags are relevant and descriptive (if included)
- Category is specified (if included)
**Content Organization:**
- Logical section hierarchy
- Progressive complexity in examples
- Clear cross-references to related content
- Proper code formatting and syntax highlighting
### 4. Dependency Validation (Context7 or u2m)
**IMPORTANT:** Only perform this check if the skill references specific libraries or frameworks.
For each library/framework mentioned in the skill:
- Identify the library name and version (if specified)
- Use mcp Context7 to check if the library is current
- Verify trust score is adequate (≥ 7.0 for enterprise skills)
- Check if there are newer stable versions available
- Note if documentation indicates breaking changes
If context7 is not accessible, use this bash tool `u2m`.
- Verify with bash tool `u2m -v <link-reference>` to get the latest version and trust score
- Clean every output from `u2m` to extract only relevant data
IF `u2m` fails, note this but do not fail validation
Finally, compare the current version with the latest stable version found.
**Skip this check if:**
- The skill is language-agnostic or doesn't reference specific libraries
- The skill only uses built-in language features
- No version numbers are specified
## Output Format
### Success Case
If ALL checks pass, output:
```
✅ Validation completed: The skill '$1' complies with all standards.
Details:
- ✅ SKILL.md file present and valid
- ✅ Frontmatter correct (name, description)
- ✅ Structure conforms to the template
- ✅ All referenced files exist
- ✅ [Dependencies validated / No dependencies to validate]
```
### Failure Case
If ANY check fails, output:
```
❌ Validation failed for the skill '$1'.
Required actions:
* **[Category]:** [Specific description of the issue]
* **[Category]:** [Specific description of the issue]
...
```
**Categories for errors:**
- **Existence:** Skill or SKILL.md not found
- **Requirements:** YAML frontmatter errors, invalid field values, missing required fields
- **Template:** Missing sections, incorrect structure, poor organization
- **File:** Referenced files not found, incorrect path format
- **Dependencies:** Outdated libraries, low trust scores, breaking changes
- **Content:** Vague descriptions, missing examples, poor documentation
## Examples of Specific Feedback
**Good specific feedback:**
-Provides chunking strategies for RAG systems. Generates chunk size recommendations (256-1024 tokens), overlap percentages (10-20%), and semantic boundary detection methods. Validates semantic coherence and evaluates retrieval precision/recall metrics. Use when building retrieval-augmented generation systems, vector databases, or processing large documents.
>
Implements document chunking, embedding generation, vector storage, and retrieval pipelines for Retrieval-Augmented Generation systems. Use when building RAG applications, creating document Q&A systems, or integrating AI with knowledge bases.
Provides AWS CloudFormation patterns for Auto Scaling including EC2, ECS, and Lambda. Use when creating Auto Scaling groups, launch configurations, launch templates, scaling policies, lifecycle hooks, and predictive scaling. Covers template structure with Parameters, Outputs, Mappings, Conditions, cross-stack references, and best practices for high availability and cost optimization.
Provides AWS CloudFormation patterns for Amazon Bedrock resources including agents, knowledge bases, data sources, guardrails, prompts, flows, and inference profiles. Use when creating Bedrock agents with action groups, implementing RAG with knowledge bases, configuring vector stores, setting up content moderation guardrails, managing prompts, orchestrating workflows with flows, and configuring inference profiles for model optimization.
Provides AWS CloudFormation patterns for CloudFront distributions, origins (ALB, S3, Lambda@Edge, VPC Origins), CacheBehaviors, Functions, SecurityHeaders, parameters, Outputs and cross-stack references. Use when creating CloudFront distributions with CloudFormation, configuring multiple origins, implementing caching strategies, managing custom domains with ACM, configuring WAF, and optimizing performance.
Provides AWS CloudFormation patterns for CloudWatch monitoring, metrics, alarms, dashboards, logs, and observability. Use when creating CloudWatch metrics, alarms, dashboards, log groups, log subscriptions, anomaly detection, synthesized canaries, Application Signals, and implementing template structure with Parameters, Outputs, Mappings, Conditions, cross-stack references, and CloudWatch best practices for monitoring production infrastructure.
Provides AWS CloudFormation patterns for DynamoDB tables, GSIs, LSIs, auto-scaling, and streams. Use when creating DynamoDB tables with CloudFormation, configuring primary keys, local/global secondary indexes, capacity modes (on-demand/provisioned), point-in-time recovery, encryption, TTL, and implementing template structure with Parameters, Outputs, Mappings, Conditions, cross-stack references.