skills.rest
iinoshirozheng
iinoshirozhengCOMMUNITY
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sensei

Automate frontmatter compliance improvements for Agent Skills using the Ralph loop.

Updated Aug 27, 2026
Search Tags:#automation#validation#frontmatter#tests#token-budget#ralph-loop#sensei
One-click install
npx skills add https://github.com/iinoshirozheng/SinoCloudChat --skill sensei-iinoshirozheng
Or copy as Structured Prompt for Agent▼
Please help me install this Agent Skill.
Skill: sensei
Source: https://github.com/iinoshirozheng/SinoCloudChat/tree/main/.agents/skills/sensei
Command: npx skills add https://github.com/iinoshirozheng/SinoCloudChat --skill sensei-iinoshirozheng

SYSTEM DOCUMENTATION & REQUIREMENTS

💡 This Skill includes references (resource) components.

What problem does it solve?

Frontmatter compliance for Agent Skills is often inconsistent, leading to unreliable discovery and activation across models. Sensei automates the Ralph loop to iteratively improve Skill frontmatter and keep tests, references, and token budgets aligned.

Core Features & Use Cases

  • Automated frontmatter auditing and scoring against the agentskills.io specification.
  • Iterative frontmatter improvement using the Ralph loop with scaffold, verify, and token checks.
  • Test scaffolding and verification for triggers/prompts, with batch processing support for multiple skills.
  • Token-budget checks and token-optimization suggestions to stay under recommended limits.
  • Reference validation to ensure linked docs remain within the skill directory.

Quick Start

Run sensei on <skill-name> to start the iterative frontmatter improvement loop.

Frequently Asked Questions about sensei

High-intent search queries and answers about installing and using this skill.

FAQPage Schema
How do I automate frontmatter compliance checks for Agent Skills?▼

Automate frontmatter compliance by running an iterative Ralph loop that validates triggers, anti-triggers, and token budgets against the agentskills spec. This standardizes discovery and activation across multi-skill repositories.

Why does my Agent Skill fail to activate reliably across different models?▼

Inconsistent frontmatter causes unreliable activation. Auditing and scoring your frontmatter against the agentskills.io specification standardizes triggers and anti-triggers to ensure consistent model discovery.

How do I optimize token budgets for multi-skill repositories?▼

Optimize token budgets by running automated checks that validate frontmatter limits and provide token-optimization suggestions. This ensures all skills stay under recommended token limits during batch processing.

What is the best way to standardize triggers and anti-triggers across multiple skills?▼

Standardize triggers and anti-triggers by applying an iterative improvement loop that scaffolds tests, verifies prompts, and validates frontmatter across multi-skill repositories to meet the agentskills spec.

Can I validate linked reference documents within a skill directory?▼

Reference validation checks linked documents to ensure they remain within the skill directory. This prevents broken paths and maintains structural integrity during frontmatter compliance improvements.

Does frontmatter auditing automatically prompt for repository commits?▼

Frontmatter auditing prompts for commit or issue creation after validating against the agentskills spec and enforcing token budgets, streamlining the integration of compliance fixes into your workflow.

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