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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ir-velociraptor
by AgentSecOpsEndpoint visibility, digital forensics, and incident response using Velociraptor Query Language (VQL) for evidence collection and threat hunting at scale. Use when: (1) Conducting forensic investigations across multiple endpoints, (2) Hunting for indicators of compromise or suspicious activities, (3) Collecting endpoint telemetry and artifacts for incident analysis, (4) Performing live response and evidence preservation, (5) Monitoring endpoints for security events, (6) Creating custom forensic artifacts for specific threat scenarios.
ot-security-assessment
by AgentSecOpsOperational Technology (OT) security assessment using a two-stage methodology: (1) Identification/Discovery of OT devices and protocols, and (2) Vulnerability Assessment using online sources and Metasploit. Use when: (1) Conducting authorized OT/ICS security assessments, (2) Identifying and enumerating OT protocols (Modbus, S7, IEC 104, DNP3, BACnet, EtherNet/IP), (3) Discovering industrial control devices and PLCs, (4) Assessing OT protocol vulnerabilities and security weaknesses, (5) Performing compliance scanning aligned with IEC 62443 standards, (6) Validating network segmentation and access controls in OT environments.
sbom-syft
by AgentSecOpsSoftware Bill of Materials (SBOM) generation using Syft for container images, filesystems, and archives. Detects packages across 28+ ecosystems with multi-format output support (CycloneDX, SPDX, syft-json). Enables vulnerability assessment, license compliance, and supply chain security. Use when: (1) Generating SBOMs for container images or applications, (2) Analyzing software dependencies and packages for vulnerability scanning, (3) Tracking license compliance across dependencies, (4) Integrating SBOM generation into CI/CD for supply chain security, (5) Creating signed SBOM attestations for software provenance.
api-spectral
by AgentSecOpsAPI specification linting and security validation using Stoplight's Spectral with support for OpenAPI, AsyncAPI, and Arazzo specifications. Validates API definitions against security best practices, OWASP API Security Top 10, and custom organizational standards. Use when: (1) Validating OpenAPI/AsyncAPI specifications for security issues and design flaws, (2) Enforcing API design standards and governance policies across API portfolios, (3) Creating custom security rules for API specifications in CI/CD pipelines, (4) Detecting authentication, authorization, and data exposure issues in API definitions, (5) Ensuring API specifications comply with organizational security standards and regulatory requirements.
dast-ffuf
by AgentSecOpsFast web fuzzer for DAST testing with directory enumeration, parameter fuzzing, and virtual host discovery. Written in Go for high-performance HTTP fuzzing with extensive filtering capabilities. Supports multiple fuzzing modes (clusterbomb, pitchfork, sniper) and recursive scanning. Use when: (1) Discovering hidden directories, files, and endpoints on web applications, (2) Fuzzing GET and POST parameters to identify injection vulnerabilities, (3) Enumerating virtual hosts and subdomains, (4) Testing authentication endpoints with credential fuzzing, (5) Finding backup files and sensitive data exposures, (6) Performing comprehensive web application reconnaissance.
dast-nuclei
by AgentSecOpsFast, template-based vulnerability scanning using ProjectDiscovery's Nuclei with extensive community templates covering CVEs, OWASP Top 10, misconfigurations, and security issues across web applications, APIs, and infrastructure. Use when: (1) Performing rapid vulnerability scanning with automated CVE detection, (2) Testing for known vulnerabilities and security misconfigurations in web apps and APIs, (3) Running template-based security checks in CI/CD pipelines with customizable severity thresholds, (4) Creating custom security templates for organization-specific vulnerability patterns, (5) Scanning multiple targets efficiently with concurrent execution and rate limiting controls.
dast-zap
by AgentSecOpsDynamic application security testing (DAST) using OWASP ZAP (Zed Attack Proxy) with passive and active scanning, API testing, and OWASP Top 10 vulnerability detection. Use when: (1) Performing runtime security testing of web applications and APIs, (2) Detecting vulnerabilities like XSS, SQL injection, and authentication flaws in deployed applications, (3) Automating security scans in CI/CD pipelines with Docker containers, (4) Conducting authenticated testing with session management, (5) Generating security reports with OWASP and CWE mappings for compliance.
sast-bandit
by AgentSecOpsPython security vulnerability detection using Bandit SAST with CWE and OWASP mapping. Use when: (1) Scanning Python code for security vulnerabilities and anti-patterns, (2) Identifying hardcoded secrets, SQL injection, command injection, and insecure APIs, (3) Generating security reports with severity classifications for CI/CD pipelines, (4) Providing remediation guidance with security framework references, (5) Enforcing Python security best practices in development workflows.
sast-semgrep
by AgentSecOpsStatic application security testing (SAST) using Semgrep for vulnerability detection, security code review, and secure coding guidance with OWASP and CWE framework mapping. Use when: (1) Scanning code for security vulnerabilities across multiple languages, (2) Performing security code reviews with pattern-based detection, (3) Integrating SAST checks into CI/CD pipelines, (4) Providing remediation guidance with OWASP Top 10 and CWE mappings, (5) Creating custom security rules for organization-specific patterns, (6) Analyzing dependencies for known vulnerabilities.
sca-blackduck
by AgentSecOpsSoftware Composition Analysis (SCA) using Synopsys Black Duck for identifying open source vulnerabilities, license compliance risks, and supply chain security threats with CVE, CWE, and OWASP framework mapping. Use when: (1) Scanning dependencies for known vulnerabilities and security risks, (2) Analyzing open source license compliance and legal risks, (3) Identifying outdated or unmaintained dependencies, (4) Integrating SCA into CI/CD pipelines for continuous dependency monitoring, (5) Providing remediation guidance for vulnerable dependencies with CVE and CWE mappings, (6) Assessing supply chain security risks and third-party component threats.
policy-opa
by AgentSecOpsPolicy-as-code enforcement and compliance validation using Open Policy Agent (OPA). Use when: (1) Enforcing security and compliance policies across infrastructure and applications, (2) Validating Kubernetes admission control policies, (3) Implementing policy-as-code for compliance frameworks (SOC2, PCI-DSS, GDPR, HIPAA), (4) Testing and evaluating OPA Rego policies, (5) Integrating policy checks into CI/CD pipelines, (6) Auditing configuration drift against organizational security standards, (7) Implementing least-privilege access controls.
container-grype
by AgentSecOpsContainer vulnerability scanning and dependency risk assessment using Grype with CVSS severity ratings, EPSS exploit probability, and CISA KEV indicators. Use when: (1) Scanning container images and filesystems for known vulnerabilities, (2) Integrating vulnerability scanning into CI/CD pipelines with severity thresholds, (3) Analyzing SBOMs (Syft, SPDX, CycloneDX) for security risks, (4) Prioritizing remediation based on threat metrics (CVSS, EPSS, KEV), (5) Generating vulnerability reports in multiple formats (JSON, SARIF, CycloneDX) for security toolchain integration.
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.