How to Find and Use AI Agent Skills on OpenBooklet
You have heard about AI agent skills. Maybe you have even read about what they are. But how do you actually find the right skill for your use case and start using it? This guide covers the full workflow, from discovery to daily use.
Key Takeaways
- OpenBooklet offers three ways to find skills: browsing, keyword search, and semantic search
- Every skill has a detail page showing ratings, pull counts, compatibility, and version history
- You can pull skills via the web, CLI, MCP server, or REST API
- Skills auto-convert to your agent's format - no manual reformatting needed
- Evaluating a skill before using it takes 30 seconds if you know what to look for
Finding Skills: Three Approaches
Browse by Category
The simplest starting point is the skills browser. Skills are organized into categories like Development, DevOps, Data and AI, Testing, Content, and more. Each category page shows the most popular skills ranked by pull count.
This works well when you are exploring. Maybe you just started using Claude Code and want to see what skills exist for code review. Browse the Development category, sort by "Most Used," and you will see what other developers are reaching for.
Keyword Search
If you know roughly what you need, use the search bar. Type "code review" or "nextjs testing" and you get results ranked by relevance. The search looks at skill names, descriptions, and tags.
Be specific in your search terms. "Review" returns hundreds of results. "Nextjs security review" narrows it down to exactly what you need.
Semantic Search
This is where it gets interesting. OpenBooklet uses pgvector to power semantic search - you describe what you need in natural language, and the system finds skills by meaning, not just keyword matching.
For example, searching for "help me write better commit messages" will find commit message skills even if they do not contain those exact words. The system understands the intent behind your query.
Semantic search is available through the API and MCP server, which means your AI agent can discover skills on its own without you manually searching.
Evaluating a Skill
Not every skill is worth using. Here is what to look at on a skill's detail page before you pull it.
Trust Badges
Every skill has a verification badge:
| Badge | What It Means |
|---|---|
| Unverified | Published but not reviewed by anyone |
| Community | Upvoted by multiple users |
| Author Verified | Publisher proved ownership via GitHub OAuth |
| Certified | Reviewed and approved by the OpenBooklet team |
A community-verified skill with 500 pulls is generally safer than an unverified skill with 2 pulls. But even unverified skills go through automated safety scanning.
Pull Count and Ratings
Pull count tells you how many times the skill has been downloaded. High pull count means people are actually using it. Ratings (upvote/downvote) tell you if they found it useful.
A skill with 1,000 pulls and a 95% upvote rate is a strong signal. A skill with 50 pulls and mixed ratings might need more work.
Version History
Check the version history tab. A skill on version 3.2.0 with regular updates is being actively maintained. A skill stuck on 1.0.0 from six months ago might be abandoned.
Compatibility
The compatibility section shows which agents the skill works with. If you use Cursor, make sure the skill has been tested with Cursor. OpenBooklet auto-converts formats, but some skills are written specifically for certain agents and work better there.
Using a Skill: Four Methods
Once you have found a skill you want, there are four ways to get it into your project.
Method 1: The CLI (Recommended)
The fastest path for developers:
# Install the CLI globally
npm install -g openbooklet
# Pull a skill into your project
ob pull code-review-pro
# Pull a specific version
ob pull code-review-pro@2.1.0
# Pull in a specific agent format
ob pull code-review-pro --target cursor
By default, ob pull saves the skill to .claude/skills/ in the current directory. Claude Code picks it up automatically on the next conversation.
Method 2: The Web UI
On any skill's detail page, click the "Copy" button. This copies the raw SKILL.md content to your clipboard. Paste it into your agent's configuration directory.
You can also click the "Download" button to save the file directly, or switch between agent formats using the format tabs.
Method 3: The REST API
For programmatic access:
# Get skill metadata
curl https://openbooklet.com/api/v1/skills/code-review-pro
# Get raw skill content
curl https://openbooklet.com/s/code-review-pro/raw
The API supports version pinning, format selection, and ETag caching. Full API documentation is available.
Method 4: The MCP Server
If your agent supports MCP, it can discover and pull skills directly through the OpenBooklet MCP server. This is the most powerful option because the agent handles everything - you do not need to manually search or pull.
The MCP server exposes tools like search_skills, pull_skill, and get_skill_info. Configure it in your agent's MCP settings and let the agent find what it needs.
The MCP server is free for public skills. No API key required. For higher rate limits, generate a key from your settings page.
Organizing Your Skills
As you collect more skills, organization matters. Here are two approaches:
Local: Agent Config Directories
Most developers keep skills in their agent's native directory structure:
- Claude Code:
.claude/skills/[skill-name]/SKILL.md - Cursor:
.cursor/rules/[skill-name].mdc - Windsurf:
.windsurf/rules/[skill-name].md
These load automatically when the agent starts. No extra configuration.
Platform: Directories
If you want to organize skills across projects, use OpenBooklet Directories. Directories are like bookmark folders - they group skills together without copying them. Create a "Frontend Team Standards" directory, add your approved skills, and share it with your team.
Directories are especially useful for organizations that want to standardize which skills their teams use.
Common Mistakes to Avoid
Loading too many skills at once. Agents have finite context windows. If you load 20 skills, the agent spends most of its context on instructions instead of your actual task. Keep your active skill set small and focused - 3 to 5 skills for a given workflow is usually the sweet spot.
Not checking compatibility. A skill written for Claude with 200K context might reference tools or patterns that a smaller model cannot handle. Check the compatibility section before assuming it will work with your setup.
Ignoring version pins. If you find a skill that works well, pin the version. Skills update over time, and a new version might change behavior you depend on. Use ob pull skill-name@2.1.0 instead of always pulling latest.
FAQ
Are skills free to use?
Yes. All public skills on OpenBooklet are free to search, pull, and use. There are no usage fees, no freemium tiers, and no API keys required for basic access. Rate limits exist to prevent abuse, but they are generous enough for normal use.
Can I use skills with any AI agent?
Skills work with any agent that can read text instructions. OpenBooklet provides pre-converted formats for Claude Code, Cursor, Windsurf, GitHub Copilot, GPTs, and LangChain. If your agent is not on that list, you can still use the raw SKILL.md content - it is just Markdown with YAML frontmatter.
How do I know if a skill is safe?
Every skill on OpenBooklet goes through automated safety scanning that checks for prompt injection, data exfiltration patterns, and other risks. Skills that pass get a safety badge. However, no automated system is perfect - if a skill asks you to do something suspicious (like sending data to an external URL), report it through the skill's detail page.
Start Exploring
The best way to learn is by doing. Head to the skills browser, find something relevant to your current project, and pull it. Most developers find their first useful skill within 5 minutes of browsing.
If you find a gap - a skill that should exist but does not - that is your signal to publish one yourself.