Explore AI Agent Skills & Claude Prompts
Discover open-source agent skills for Claude Code, Codex, ChatGPT, and any tool that uses SKILL.md.
Enter through keywords, occupations, creators, and GitHub sources to see what kinds of skills are emerging across domains.
Use the same catalog through the API
Connect 381,784 public skills to your own search, analytics, or agent workflow with the REST API.
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frappe-errors-permissions
by z1coyanUse when debugging or handling permission errors in Frappe/ERPNext. Prevents broken document access from throwing in permission hooks. Covers PermissionError (403), has_permission hook failures, User Permission restricting too much or too little, perm_level blocking field access, System Manager bypass not working, Guest access denied, sharing permissions not applying, permission_query_conditions breaking get_list, owner-based permissions confusion, Apply User Permission checkbox behavior, and the permission debug workflow using frappe.permissions.get_doc_permissions. Keywords: PermissionError, has_permission, permission_query_conditions,, permission denied, cannot access, user blocked, sharing not working, role not enough. User Permission, perm_level, sharing, guest access, owner permission.
frappe-ops-deployment
by z1coyanUse when deploying Frappe/ERPNext to production, configuring Nginx or Supervisor, setting up Docker, enabling SSL, or hardening security. Prevents insecure deployments, missing reverse proxy config, and broken process management. Covers production setup, Nginx configuration, Supervisor/systemd, Docker Compose, Let's Encrypt SSL, firewall rules, security hardening. Keywords: deployment, production, nginx, supervisor, docker, ssl, letsencrypt, security, gunicorn, systemd, go live, production setup, HTTPS setup, server config, deploy to VPS, Docker setup..
frappe-ops-bench
by z1coyanUse when running bench commands, managing sites, configuring multi-tenancy, or setting up domains. Prevents misconfigured bench environments, broken site routing, and DNS mismatches. Covers bench CLI commands, site creation, bench init, multi-tenancy setup, DNS-based routing, common-site-config. Keywords: bench, site, multi-tenancy, domains, bench init, bench new-site, bench setup, common_site_config, bench command not working, site setup, multi-tenant, domain routing, new site..
frappe-core-utils
by z1coyanUse when working with utility functions in Frappe v14-v16. Covers frappe.utils.* for date/time, number/money, string, validation, and file path operations. Prevents reinventing stdlib alternatives that break timezone awareness, locale formatting, or multi-tenancy. Keywords: frappe.utils, nowdate, flt, cint, fmt_money, getdate,, date calculation, format number, money format, validate email, how to calculate days between. add_days, date_diff, validate_email, pretty_date, get_files_path.
frappe-errors-database
by z1coyanUse when handling database errors in Frappe/ERPNext. Covers DuplicateEntryError, LinkValidationError, MandatoryError, TimestampMismatchError, CharacterLengthExceededError, InReadOnlyMode, QueryTimeoutError, SQL injection errors, frappe.db.sql parameter format (% vs %s), get_value returning None, transaction deadlocks, MariaDB gone away, too many connections. Error-to-fix mapping for v14/v15/v16. Keywords: database error, DuplicateEntryError, TimestampMismatchError,, MariaDB error, MySQL error, column not found, table missing, duplicate entry, database crash. SQL injection, deadlock, MariaDB gone away, query timeout.
frappe-impl-workspace
by z1coyanUse when creating or customizing Workspace pages in Frappe v14-v16. Covers Workspace DocType structure, shortcuts, number cards, dashboard charts, custom HTML blocks, JSON content format, shipping workspaces with custom apps, and role-based access control. Prevents common mistakes with content/child-table desync and missing fixtures. Keywords: workspace, desk, dashboard, number card, chart, shortcut,, customize desk, dashboard setup, add shortcut, module page, sidebar customize. workspace builder, module, fixtures, sidebar.
frappe-impl-reports
by z1coyanUse when building Script Reports, Query Reports, dashboard charts, or Number Cards in ERPNext. Prevents empty report output from wrong column definitions, broken filters, and unoptimized SQL in large datasets. Covers Report Builder, Script Report (Python + JS), Query Report, Report filters, dashboard Chart DocType, Number Card, report permissions. Keywords: report, Script Report, Query Report, dashboard, chart, Number Card, filters, columns, execute, get_data, create report, custom report, dashboard chart, report empty, no data showing..
frappe-core-logging
by z1coyanUse when implementing logging, error tracking, or monitoring in Frappe v14-v16. Covers frappe.logger() for file-based logging, frappe.log_error() for Error Log DocType entries, request logging, Sentry integration, and production logging patterns. Prevents common mistakes with print(), swapped log_error arguments, and sensitive data. Keywords: frappe.logger, log_error, Error Log, logging, Sentry,, where are the logs, how to log errors, error tracking, print not showing, production logs. monitor, request logging, error tracking, debug, production.
frappe-impl-clientscripts
by z1coyanUse when implementing client-side form features in Frappe/ERPNext: field visibility, cascading filters, calculated fields, custom buttons, server calls, form validation, child table logic, debugging. Covers step-by-step workflows from Setup > Client Script through migration to custom app JS. Keywords: how to implement client script, form logic workflow, dynamic UI, calculate fields, frm.call, frappe.call, frappe.xcall, client script testing, field dependency, custom button, how to hide field, show field based on value, add button to form, calculate total, dynamic form.
frappe-syntax-scheduler
by z1coyanUse when configuring scheduler events and background jobs in Frappe/ERPNext v14/v15/v16. Covers scheduler_events in hooks.py, frappe.enqueue() for async jobs, queue configuration, job deduplication, error handling, and monitoring. Keywords: scheduler, background job, cron, RQ worker, job queue, async task, frappe.enqueue, scheduled task, cron syntax, how often does it run, background job example, enqueue example.
frappe-impl-jinja
by z1coyanUse when building Jinja templates in Frappe: Print Formats, Email Templates, Notification templates, Portal Pages, and custom Jinja methods. Covers template creation workflows, child table handling, conditional sections, styling, multi-language support, and debugging. Prevents N+1 queries, wrong formatting, and Report Print confusion. Keywords: create print format, email template, portal page, pdf, create print format, invoice template, email template, PDF layout, custom print. template, invoice template, jinja methods, notification template, web page template, print format styling.
frappe-agent-debugger
by z1coyanUse when debugging Frappe errors, using bench console for live inspection, analyzing tracebacks, or reading Frappe log files. Prevents wasted debugging time from ignoring log context, misreading tracebacks, and not using bench console effectively. Covers bench console, frappe.logger, error log DocType, traceback analysis, common error patterns, log file locations, pdb/debugger integration, VS Code DAP, profiling, Frappe Recorder, mariadb diagnostics. Keywords: debug, bench console, traceback, error log, frappe.logger, pdb, debugging, log analysis, inspect, VS Code, DAP, profiling, recorder, mariadb, monitor, ERPNext error, how to debug, find the bug, what went wrong, stack trace, error message..
Browse Agent Skills by Occupation
23 major groups · 867 SOC occupations
Browse by Category
Explore agent skills organized by their primary use case
Explore the agent skills ecosystem by occupation and creator
SkillMD is not just a keyword search box. It is an open map that organizes public skills by occupation, creator, and repository, helping you see which workflows, judgment criteria, and domain habits people are writing for AI agents.
Then follow creators and GitHub repositories back to the source: compare the skills a team maintains, whether the repo is active, and how the README frames the work before you open, install, or reuse anything.
Use it three ways: learn an unfamiliar field by occupation, study how creators organize skills, then use source context to decide what is worth opening or reusing.
01 Map a field
Browse 23 occupation groups and 867 SOC roles to learn what skills exist in adjacent domains and how they break down real work.
02 Follow creators
Use creator and repository pages to inspect maintained skill collections, recent updates, and source context before trusting a result.
03 Search with sources
Search 1.7M+ collected skills, then use occupation tags, creators, and GitHub source context to decide what is worth opening.
Start with the occupation map, then follow creators and repositories back to real code. SkillMD helps explain why a skill is worth opening, not only what it is named.
Standardizing Agent Capabilities with SKILL.md and Model Context Protocol (MCP)
In the rapidly evolving landscape of artificial intelligence, LLM agents (Large Language Model agents) have transitioned from simple text predictors to autonomous problem solvers. To orchestrate complex, multi-step agentic workflows, developers require a standardized format to specify agent capabilities, prompt instructions, system rules, and database bindings. This is where SKILL.md and the Model Context Protocol (MCP) have emerged as standard developer paradigms. SkillMD serves as the central directory for indexing, exploring, and sharing these critical agent configurations.
Our open-source registry currently tracks over 1.7 million collected SKILL.md configurations and system prompts. By compiling agent configurations from active developers on GitHub, we bridge the gap between prompt engineering research and production execution. Whether you are building agents with Anthropic's Claude Code, OpenAI's GPT-4, Google's Gemini, or local models using Ollama and LlamaIndex, standardized skill definitions ensure your agents behave predictably across different runtime environments.
What is the Model Context Protocol (MCP)?
The Model Context Protocol (MCP) is an open-source standard designed to connect LLMs to data sources, developer tools, and external environments. MCP establishes a bidirectional communication channel between client applications (like Cursor, Claude Desktop, or custom agent systems) and servers hosting data or capabilities. Standardizing instructions via SKILL.md enables LLMs to query databases, read local files, execute terminal commands, and integrate third-party APIs. SkillMD allows you to find ready-to-run MCP servers and prompt instructions for various occupations and technical tasks.
The Structure of a Professional SKILL.md File
A valid SKILL.md configuration is designed to be easily read by humans and parsed by LLMs. It contains precise system instructions, trigger conditions, required parameters, and execution examples. Below is the typical architectural blueprint of a professional agent skill:
- Metadata & Core Scope: Declares the name of the skill, author details, target models, and a description of the capability.
- Triggers & Intent Detection: Details semantic triggers that help the agent decide when to invoke this skill.
- System Prompts: Explicit system-level instructions that direct the agent's behavior, personality, safety guardrails, and formatting preferences.
- Capabilities & Tools: Lists the files, databases, or APIs the agent must access to complete the tasks.
- Few-Shot Examples: Demonstrates real inputs and outputs, helping the model generalize behavior through in-context learning.
Optimizing Agent Workflows for Modern LLMs
Writing effective agent skills requires deep knowledge of prompt engineering. With the release of advanced reasoning models like Claude 3.5 Sonnet, ChatGPT o1, and DeepSeek-V3, prompt templates must focus on structured thinking. Developers are encouraged to use XML tags (e.g., <thought>, <context>, and <rules>) to isolate execution boundaries. Standardized prompts prevent agents from suffering from context drift, ensuring that long-running tasks remain aligned with the initial system parameters.
Exploring by SOC Occupations and Creator Profiles
What makes SkillMD unique is its taxonomy. Instead of simple text search, we parse and organize files according to the Standard Occupational Classification (SOC) system. This means you can discover skills written for Computer and Mathematical roles, Business and Financial operations, Legal, Design, and and Educational Instruction fields. By tracking creator profiles, developers can study how different teams organize their custom instructions, compare version updates, and fork public configs for specialized enterprise use cases.
SkillMD operates as a high-performance index running on a fast Go backend and a highly responsive Astro SSR frontend. All search queries execute in milliseconds, featuring smart debouncing to prevent multiple API requests while keeping user data secure. Join our community of developers to standardize your AI agent instructions and optimize your LLM prompting workflows today.
Frequently Asked Questions
A practical guide to agent skills: what they are, how to inspect them, and how SkillMD helps you explore the ecosystem.