skill-standardization

supercent-io/skills-template · updated Apr 8, 2026

MDX-style export adds YAML metadata + attribution linking explainx.ai and this canonical listing URL.

$npx skills add https://github.com/supercent-io/skills-template --skill skill-standardization
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summary

Validate and standardize SKILL.md files against the Agent Skills specification.

  • Validates frontmatter fields (name, description, allowed-tools, metadata) and enforces naming conventions, length constraints, and format rules
  • Converts legacy skill formats to standard structure, including section heading normalization and directory layout alignment
  • Provides templates and step-by-step guidance for creating new skills, improving descriptions for reliable triggering, and batch-validating s
skill.md

Skill Standardization

When to use this skill

  • Creating a new SKILL.md file from scratch
  • Auditing existing skills for Agent Skills specification compliance
  • Converting legacy skill formats (non-standard headings, frontmatter) to standard
  • Improving skill descriptions to trigger more reliably on relevant prompts
  • Adding evaluation test cases (evals/evals.json) to a skill
  • Batch-validating all skills in a directory for consistency

Agent Skills Specification Reference

Frontmatter fields

Field Required Constraints
name Yes 1–64 chars, lowercase alphanumeric + hyphens, no leading/trailing/consecutive hyphens, must match parent directory name
description Yes 1–1024 chars, must describe what skill does AND when to trigger
allowed-tools No Space-delimited list of pre-approved tools
compatibility No Max 500 chars, environment requirements
license No License name or reference to bundled file
metadata No Arbitrary key-value map for additional fields

Standard directory structure

skill-name/
├── SKILL.md          # Required
├── scripts/          # Optional: executable scripts
├── references/       # Optional: detailed documentation
├── assets/           # Optional: templates, images, data
└── evals/            # Optional: evaluation test cases
    └── evals.json

Progressive disclosure tiers

Tier What's loaded When Token budget
1. Catalog name + description Session start ~100 tokens per skill
2. Instructions Full SKILL.md body On activation < 5000 tokens (500 lines max)
3. Resources scripts/, references/ When needed Varies

Instructions

Step 1: Validate an existing skill

Run the validation script on a skill directory:

bash scripts/validate_skill.sh path/to/skill-directory

Validate all skills in a directory:

bash scripts/validate_skill.sh --all .agent-skills/

The script checks:

  • Required frontmatter fields (name, description)
  • name format: lowercase, no consecutive hyphens, matches directory name
  • description length: 1–1024 characters
  • allowed-tools format: space-delimited (not YAML list)
  • Recommended sections present
  • File length: warns if over 500 lines

Step 2: Write an effective description

The description field determines when a skill triggers. A weak description means the skill never activates; an over-broad one triggers at wrong times.

Template:

description: >
  [What the skill does — list specific operations.]
  Use when [trigger conditions]. Even if the user doesn't explicitly
  mention [domain keyword] — also triggers on: [synonym list].

Principles (from agentskills.io):

  1. Imperative phrasing — "Use this skill when..." not "This skill does..."
  2. User intent, not implementation — describe what the user wants to achieve
  3. Be explicit about edge cases — "even if they don't say X"
  4. List trigger keywords — synonyms, related terms the user might type
  5. Stay under 1024 characters — descriptions grow during editing; watch the limit

Before / After:

# Before (weak — never triggers)
description: Helps with PDFs.

# After (optimized — reliable triggering)
description: >
  Extract text and tables from PDF files, fill forms, merge and split documents.
  Use when the user needs to work with PDF files, even if they don't explicitly
  say 'PDF' — triggers on: fill form, extract text from document, merge files,
  read scanned pages.

Step 3: Create a new SKILL.md

Use this template as the starting point:

---
name: skill-name
description: >
  [What it does and specific operations it handles.]
  Use when [trigger conditions]. Triggers on: [keyword list].
allowed-tools: Bash Read Write Edit Glob Grep
metadata:
  tags: tag1, tag2, tag3
  version: "1.0"
---

# Skill Title

## When to use this skill
- Scenario 1
- Scenario 2

## Instructions

### Step 1: [Action]
Content...

### Step 2: [Action]
Content...

## Examples

### Example 1: [Scenario]
Input: ...
Output: ...

## Best practices
1. Practice 1
2. Practice 2

## References
- [Link](url)

Step 4: Convert legacy section headings

Legacy heading Standard heading
## Purpose ## When to use this skill
## When to Use ## When to use this skill
## Procedure ## Instructions
## Best Practices ## Best practices
## Reference ## References
## Output Format ## Output format

Step 5: Add evaluation test cases

Create evals/evals.json with 2–5 realistic test prompts:

{
  "skill_name": "your-skill-name",
  "evals": [
    {
      "id": 1,
      "prompt": "Realistic user message that should trigger this skill",
      "expected_output": "Description of what success looks like",
      "assertions": [
        "Specific verifiable claim (file exists, count is correct, format is valid)",
        "Another specific claim"
      ]
    }
  ]
}

Good assertions are verifiable: file exists, JSON is valid, chart has 3 bars. Avoid vague assertions like "output is good."

Available scripts

  • scripts/validate_skill.sh — Validates a SKILL.md against the Agent Skills spec

Examples

Example 1: Validate a skill directory

bash scripts/validate_skill.sh .agent-skills/my-skill/

Output:

Validating: .agent-skills/my-skill/SKILL.md
✓ Required field: name = 'my-skill'
✓ Required field: description present
✗ Description length: 1087 chars (max 1024)
✓ Name format: valid lowercase
✗ Name/directory mismatch: name='myskill' vs dir='my-skill'
✓ Recommended section: When to use this skill
✓ Recommended section: Instructions
⚠ Missing recommended section: Examples
✓ File length: 234 lines (OK)

Issues: 2 errors, 1 warning

Example 2: Batch validate all skills

bash scripts/validate_skill.sh --all .agent-skills/

Example 3: Fix common frontmatter issues

# WRONG — tags inside metadata is non-standard for some validators
metadata:
  tags: [tag1, tag2]   # list syntax
  platforms: Claude    # non-spec field

# CORRECT — per Agent Skills spec
metadata:
  tags: tag1, tag2     # string value
allowed-tools: Bash Read Write  # space-delimited, not a YAML list

Best practices

  1. Description quality first — weak descriptions mean the skill never activates; improve it before anything else
  2. Keep SKILL.md under 500 lines — move detailed reference docs to references/
  3. Pin script versions — use uvx [email protected] not just ruff to ensure reproducibility
  4. No interactive prompts in scripts — agents run in non-interactive shells; use --flag inputs, never TTY prompts
  5. Structured output from scripts — prefer JSON/CSV over free-form text; send data to stdout, diagnostics to stderr
  6. Add evals before publishing — at least 2–3 test cases covering core and edge cases

References

how to use skill-standardization

How to use skill-standardization on Cursor

AI-first code editor with Composer

1

Prerequisites

Before installing skills in Cursor, ensure your development environment meets these requirements:

  • Cursor installed and configured on your development machine
  • Node.js version 16.0+ with npm package manager (verify with node --version)
  • Active project directory or workspace where you want to add skill-standardization
2

Execute installation command

Execute the skills CLI command in your project's root directory to begin installation:

$npx skills add https://github.com/supercent-io/skills-template --skill skill-standardization

The skills CLI fetches skill-standardization from GitHub repository supercent-io/skills-template and configures it for Cursor.

3

Select Cursor when prompted

The CLI will show a list of available agents. Use arrow keys to navigate and space to select Cursor:

◆ Which agents do you want to install to?
│ ── Universal (.agents/skills) ── always included ────
│ • Amp
│ • Antigravity
│ • Cline
│ • Codex
│ ●Cursor(selected)
│ • Cursor
│ • Windsurf
4

Verify installation

Confirm successful installation by checking the skill directory location:

.cursor/skills/skill-standardization

Reload or restart Cursor to activate skill-standardization. Access the skill through slash commands (e.g., /skill-standardization) or your agent's skill management interface.

Security & Verification Notice

We perform automated surface-level scans (Gen AI Scanner, Socket, Snyk) during installation. These checks detect common vulnerabilities but do not guarantee complete security. Always review skill source code and verify the publisher's reputation before production use.

Skills execute code in your development environment. Always verify the publisher's identity, review recent commits, and test in isolated environments before production deployment.

List & Monetize Your Skill

Submit your Claude Code skill and start earning

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Use Cases

User Story & Requirements Generation

Create detailed user stories, acceptance criteria, and feature specs

Example

Generate user stories for 'password reset feature' with acceptance criteria, edge cases, and test scenarios

Reduce spec writing time by 50%, ensure comprehensive coverage

Competitive Analysis

Research competitors, compare features, identify gaps

Example

Analyze 5 competitor products, create feature comparison matrix, suggest differentiation opportunities

Complete competitive research in 2 hours instead of 2 days

Roadmap Prioritization

Evaluate features using frameworks (RICE, ICE, Kano) and create prioritized backlogs

Example

Score 20 feature ideas using RICE framework, generate prioritized roadmap with rationale

Make data-driven prioritization decisions faster

Stakeholder Communication

Draft PRDs, status updates, and stakeholder presentations

Example

Create executive summary of Q3 roadmap, monthly progress report, feature launch announcement

Save 3-5 hours/week on communication overhead

Implementation Guide

Prerequisites

  • Claude Desktop or compatible AI client
  • Access to product documentation and roadmap tools (Jira, Notion, etc.)
  • Understanding of product management frameworks (RICE, Jobs-to-be-Done, etc.)
  • Stakeholder contact information and communication channels

Time Estimate

30-60 minutes to see productivity improvements

Installation Steps

  1. 1.Install product management skill
  2. 2.Start with user story generation for known feature
  3. 3.Progress to competitive analysis: research 2-3 competitors
  4. 4.Use for roadmap prioritization: apply RICE/ICE scoring
  5. 5.Draft stakeholder communications and refine based on feedback
  6. 6.Build template library for recurring PM tasks
  7. 7.Share effective prompts with product team

Common Pitfalls

  • Not validating competitive research—verify facts before sharing
  • Accepting user stories without involving engineering team
  • Over-relying on frameworks without qualitative judgment
  • Not customizing outputs to company culture and communication style
  • Skipping stakeholder validation of generated requirements

Best Practices

✓ Do

  • +Validate research and competitive analysis with real data
  • +Collaborate with engineering when generating technical requirements
  • +Customize frameworks and templates to your company context
  • +Use skill for first drafts, refine with stakeholder input
  • +Document successful prompt patterns for PM tasks
  • +Combine AI efficiency with human judgment and intuition

✗ Don't

  • Don't publish competitive analysis without fact-checking
  • Don't finalize user stories without engineering review
  • Don't make prioritization decisions solely on AI scoring
  • Don't skip customer validation of generated requirements
  • Don't ignore company-specific context and culture

💡 Pro Tips

  • Provide context: company goals, constraints, customer feedback
  • Ask for alternatives: 'Show 3 ways to prioritize this roadmap'
  • Request stakeholder-specific formatting: 'Executive summary vs. engineering spec'
  • Use skill for 70% generation + 30% customization to company needs

When to Use This

✓ Use When

Use for user story writing, competitive research, roadmap prioritization, stakeholder communication, and PRD drafting. Best for reducing repetitive documentation and research work.

✗ Avoid When

Avoid for strategic product vision (requires deep customer empathy), pricing decisions (needs market and financial expertise), or when face-to-face customer discovery is more valuable than speed.

Learning Path

  1. 1Basic: user stories, feature specs, status updates
  2. 2Intermediate: competitive analysis, prioritization frameworks, PRDs
  3. 3Advanced: product strategy, go-to-market planning, OKR setting
  4. 4Expert: product vision, market positioning, business model innovation

Discussion

Product Hunt–style comments (not star reviews)
  • No comments yet — start the thread.
general reviews

Ratings

4.849 reviews
  • Ama Bhatia· Dec 24, 2024

    I recommend skill-standardization for anyone iterating fast on agent tooling; clear intent and a small, reviewable surface area.

  • Dhruvi Jain· Dec 16, 2024

    skill-standardization reduced setup friction for our internal harness; good balance of opinion and flexibility.

  • Chinedu Li· Dec 12, 2024

    Useful defaults in skill-standardization — fewer surprises than typical one-off scripts, and it plays nicely with `npx skills` flows.

  • Arya Diallo· Dec 4, 2024

    We added skill-standardization from the explainx registry; install was straightforward and the SKILL.md answered most questions upfront.

  • Chen Ramirez· Nov 27, 2024

    Registry listing for skill-standardization matched our evaluation — installs cleanly and behaves as described in the markdown.

  • Dev Bhatia· Nov 15, 2024

    skill-standardization reduced setup friction for our internal harness; good balance of opinion and flexibility.

  • Oshnikdeep· Nov 7, 2024

    I recommend skill-standardization for anyone iterating fast on agent tooling; clear intent and a small, reviewable surface area.

  • Ganesh Mohane· Oct 26, 2024

    Useful defaults in skill-standardization — fewer surprises than typical one-off scripts, and it plays nicely with `npx skills` flows.

  • Charlotte Chen· Oct 18, 2024

    skill-standardization reduced setup friction for our internal harness; good balance of opinion and flexibility.

  • Arya Zhang· Oct 6, 2024

    Registry listing for skill-standardization matched our evaluation — installs cleanly and behaves as described in the markdown.

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