
skill-editor
Creates, updates, and manages Agent Skills following the Claude Code style. Use this skill when the user wants to add a new capability, create a new skill, or modify an existing skill.
- Installs
- 110
- Last 24h
- —
- Trending rank
- —
- Security
- Not audited
Install
Works with every agent the skills CLI supports.
npx skills add https://github.com/davidkiss/smart-ai-skills --skill skill-editor- 01
Install
Run the command in your project. The CLI asks which agents to install for.
- 02
Describe the task
Ask your agent for something this skill covers. It loads skill-editor automatically when relevant.
- 03
Review the result
The agent follows the SKILL.md steps, scripts and references bundled with the skill.
SKILL.md
The instructions your agent reads when the skill is triggered.
Skills Editor Skill
Description
This skill enables the agent to create and maintain "Agent Skills" - modular capabilities that extend the agent's functionality. It ensures that all skills follow the standardized directory structure and file format required by the deepagents environment.
When to Use
- When the user asks to "create a skill" or "add a capability".
- When the user wants to package a specific workflow (e.g., "teach the agent how to handle PDF invoices").
- When modifying existing skills to add new resources or update instructions.
Skill Structure Rules
Every skill must reside in its own directory and contain a SKILL.md file.
1. Directory Structure
Create a new directory for the skill (e.g., pdf-processing/).
Inside, the SKILL.md is mandatory. Other files are optional but recommended for complex tasks to keep the context window light (Progressive Disclosure).
skill-name/
├── SKILL.md # (Required) Main instructions and metadata
├── REFERENCE.md # (Optional) Detailed API docs or reference material
├── FORMS.md # (Optional) Specialized guides
└── scripts/ # (Optional) Executable scripts
└── utility.py
2. SKILL.md Format
The SKILL.md file must start with YAML frontmatter, followed by markdown instructions.
Frontmatter Requirements:
name: Max 64 chars, lowercase letters, numbers, and hyphens only. No reserved words ("anthropic", "claude").description: Max 1024 chars. Must explain what the skill does and when to use it.
Content Sections:
# [Skill Name]## Instructions: Step-by-step guidance.## Examples: Concrete usage examples.
Instructions - How to Create a Skill
MUST use the todowrite and todoread tools to track progress of the execution of the below steps:
Step 1: Check for Similar Online Skills
Before creating or editing a skill, MUST run a quick web-search (use the webfetch tool) to find any existing, similar skills online (for example, Anthropic's official skills at https://github.com/anthropics/skills/tree/main/skills or community-maintained lists). If similar skills are found:
- If the license and terms allow reuse, prefer adapting them as a template and include a clear reference/link in the new skill's SKILL.md ("Based on: <url>").
- If the license requires attribution or imposes conditions, include the original LICENSE.txt (or a pointer) in the new skill directory and follow the license terms. If the license is incompatible with your intended use, notify the user and request guidance before importing.
Step 2: Check for Existing Skills
Before creating a new skill and not using an online skill as a template, search for existing or similar local skills and reuse their structure, examples, and patterns as a starting point.
Step 3: Create the Directory
Create a directory under .opencode/skills/ with a kebab-case name matching the skill's purpose.
Step 4: Create SKILL.md
Write the SKILL.md file with the required frontmatter and sections.
Template:
---
name: my-new-skill
description: Brief description of what this skill does and when to use it.
---
# My New Skill
## Instructions
[Clear, step-by-step guidance for the agent to follow]
## Examples
[Concrete examples of using this skill]
Step 5: Add Supporting Files (Optional)
If the skill requires large reference texts or scripts, create separate files (e.g., scripts/main.py, docs/api.md) and reference them in SKILL.md. The agent will read these only when needed.
Step 6: Update dependencies (Optional)
Add any required dependencies to the project's requirements.txt file using uv pip install <package> so the project's virtual environment is updated.
Step 7: Highlight necessary environment variables (Optional)
If a skill's scripts require environment variables (API keys, tokens, credentials), list them clearly in the SKILL.md Credentials section with the expected variable names (e.g., GITHUB_ACCESS_TOKEN, YOUTUBE_API_KEY). When creating a new skill, surface these required env vars to the user and advise adding them to the project's .env file or system environment before running the scripts.
Best Practices
- Progressive Disclosure: Don't put everything in
SKILL.md. Use it as an entry point that links to other files. - Deterministic Code: Prefer Python scripts for complex logic or data processing over natural language instructions.
- Concise Scripts: When creating script files, keep them concise—clear purpose, small functions, minimal external dependencies, and avoid unnecessary complexity.
- Clear Triggers: Ensure the
descriptionclearly states when the skill should be used so the router can pick it up correctly. - Confirm changes: Confirm changes with the user before executing any steps.
FAQ
What does the skill-editor skill do?
Creates, updates, and manages Agent Skills following the Claude Code style. Use this skill when the user wants to add a new capability, create a new skill, or modify an existing skill.
How do I install skill-editor?
Run npx skills add https://github.com/davidkiss/smart-ai-skills --skill skill-editor in your project. The skills CLI detects the agents you use and copies the skill into the right folder. For Claude Code you can also place the skill folder at ~/.claude/skills/skill-editor/ (personal) or .claude/skills/skill-editor/ (project).
Which AI agents can use skill-editor?
Any agent that supports the open Agent Skills format (a folder with a SKILL.md file), including Claude Code, Codex, Cursor, GitHub Copilot, Gemini CLI, Windsurf, Cline, OpenCode and more.
Is skill-editor safe to install?
No partner security audit is available yet. Skills can run commands and scripts, so read the SKILL.md and any bundled files before installing.
Who maintains skill-editor?
It is published by davidkiss in davidkiss/smart-ai-skills. It has 110 recorded installs.
More from davidkiss/smart-ai-skills
reflection
davidkiss/smart-ai-skills
MUST use this skill when user provides feedback / ask to do things in certain way, or when a tool call fails - for self-improvement - to learn user preferences and store them in AGENT.md / CLAUDE.md, and to propose improvements to skills.
task-breakdown
davidkiss/smart-ai-skills
Use when you have specs or requirements for a multi-step task to break it down into detailed tasks, before executing it
subagent-task-execution
davidkiss/smart-ai-skills
Open the skill to read its SKILL.md instructions.
Popular ai & agents skills
google-agents-cli-publish
google/agents-cli
This skill should be used when the user wants to "publish an agent", "publish my ADK agent", "register an agent with Gemini", "publish to Gemini" (formerly Gemini Enterprise), or needs guidance on the agents-cli publish gemini command. Also use when the user wants to "manage agents in Agent Registry", "list/update/delete registered agents", or "register an MCP server". Covers ADK vs A2A registration modes, programmatic and interactive usage, flag reference, auto-detection from deployment metadata, Agent Registry fleet management, and troubleshooting. Part of the agents-cli skills suite. Do NOT use for deployment (use google-agents-cli-deploy).
google-agents-cli-eval
google/agents-cli
This skill should be used when the user wants to "run an evaluation", "evaluate my agent", "evaluate my ADK agent", "write an eval dataset", "analyze eval failures", "compare eval results", "optimize agent", or needs guidance on the Gemini platform eval methodology and the Quality Flywheel. Covers eval metrics, dataset schema, LLM-as-judge scoring, and common failure causes. Applies to any agents-cli project, whatever framework the agent is written in. Do NOT use for agent API code patterns (ADK: use google-agents-cli-adk-code), deployment (use google-agents-cli-deploy), or project scaffolding (use google-agents-cli-scaffold).
skill-creator
anthropics/skills
Create new skills, modify and improve existing skills, and measure skill performance. Use when users want to create a skill from scratch, edit, or optimize an existing skill, run evals to test a skill, benchmark skill performance with variance analysis, or optimize a skill's description for better triggering accuracy.
codex-pet
prime-skills/runcomfy-agent-skills
Codex Pet generator on RunComfy. Build a Codex-compatible Codex Pet spritesheet.webp + pet.json from a single reference image, drop it into ${CODEXHOME:-$HOME/.codex}/pets/ / and Codex picks it up as a custom Codex Pet next to the 8 built-ins. This skill produces the exact Codex Pet atlas Codex expects (1536x1872 PNG/WebP, 8 cols x 9 rows, 192x208 cells, 9 animation states — idle, running-right, running-left, waving, jumping, failed, waiting, running, review). Calls OpenAI GPT Image 2 edit ONCE via the local RunComfy CLI as runcomfy run openai/gpt-image-2/edit to produce a canonical Codex Pet pose, then assembles all 9 animation rows programmatically with ImageMagick micro-transforms — no Codex Pro, no $imagegen, no OPENAIAPIKEY required, only RUNCOMFYTOKEN. Triggers on "codex pet", "create codex pet", "make codex pet", "hatch codex pet", "/hatch image", "desktop pet codex", "codex pets", "spritesheet.webp", or any explicit ask to build a custom pet for OpenAI Codex.
full-output-enforcement
leonxlnx/taste-skill
Overrides default LLM truncation behavior. Enforces complete code generation, bans placeholder patterns, and handles token-limit splits cleanly. Apply to any task requiring exhaustive, unabridged output.
executing-plans
obra/superpowers
Use when executing an implementation plan in the current session as the implementer yourself — your human partner chose inline execution, or no subagent tool is available