ReddRadar
Agent skills
Skills you can use with AI coding agents, indexed from public GitHub repositories.
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realtime-patterns
layeddie/ai-rules
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git-workflow
Git and GitHub workflow automation skills for OpenCode agents
layeddie/ai-rules
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migration-patterns
Zero-downtime Elixir/Phoenix database migrations and rollback strategies
layeddie/ai-rules
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containerization
Docker and Kubernetes deployment patterns for Elixir/Phoenix applications
layeddie/ai-rules
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test-generation
Generates comprehensive Elixir tests using ExUnit following TDD principles.
layeddie/ai-rules
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jido_ai
layeddie/ai-rules
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advanced-database
layeddie/ai-rules
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security-patterns
Elixir-specific security patterns, OWASP mitigations, and compliance best practices
layeddie/ai-rules
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distributed-systems
Distributed systems patterns for BEAM/OTP including clustering, supervision, and multi-region deployment
layeddie/ai-rules
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reflection-manager
STEMMOM/m-pps-v1.1 9
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personal-schedule-manager
STEMMOM/m-pps-v1.1 9
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ledger-registry
Reads /ledger/manifest.json, verifies per-ledger checksums, and returns the active ledger map. **Version:** 1.1 **Author:** Entropy Control Theory **License:** MIT **Based on:** Structure DNA v1.0 + PROFILE-GENERATOR-SPEC v1.0
STEMMOM/m-pps-v1.1 9
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goal-manager
STEMMOM/m-pps-v1.1 9
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secure-flow
A comprehensive security skill that integrates with Secure Flow to help AI coding agents write secure code, perform security reviews, and implement security best practices. Use this skill when writing, reviewing, or modifying code to ensure secure-by-default practices are followed.
plutosecurity/secure-flow 5
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policy-opa
Policy-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.
AgentSecOps/SecOpsAgentKit 84
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ir-velociraptor
Endpoint 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.
AgentSecOps/SecOpsAgentKit 84
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forensics-osquery
SQL-powered forensic investigation and system interrogation using osquery to query operating systems as relational databases. Enables rapid evidence collection, threat hunting, and incident response across Linux, macOS, and Windows endpoints. Use when: (1) Investigating security incidents and collecting forensic artifacts, (2) Threat hunting across endpoints for suspicious activity, (3) Analyzing running processes, network connections, and persistence mechanisms, (4) Collecting system state during incident response, (5) Querying file hashes, user activity, and system configuration for compromise indicators, (6) Building detection queries for continuous monitoring with osqueryd.
AgentSecOps/SecOpsAgentKit 84
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detection-sigma
Generic detection rule creation and management using Sigma, the universal SIEM rule format. Sigma provides vendor-agnostic detection logic for log analysis across multiple SIEM platforms. Use when: (1) Creating detection rules for security monitoring, (2) Converting rules between SIEM platforms (Splunk, Elastic, QRadar, Sentinel), (3) Threat hunting with standardized detection patterns, (4) Building detection-as-code pipelines, (5) Mapping detections to MITRE ATT&CK tactics, (6) Implementing compliance-based monitoring rules.
AgentSecOps/SecOpsAgentKit 84
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skill-name
[REQUIRED] Comprehensive description of what this skill does and when to use it. Include: (1) Primary functionality, (2) Specific use cases, (3) Security operations context. Must include specific "Use when:" clause for skill discovery. Example: "SAST vulnerability analysis and remediation guidance using Semgrep and industry security standards. Use when: (1) Analyzing static code for security vulnerabilities, (2) Prioritizing security findings by severity, (3) Providing secure coding remediation, (4) Integrating security checks into CI/CD pipelines." Maximum 1024 characters.
AgentSecOps/SecOpsAgentKit 84
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pytm
Python-based threat modeling using pytm library for programmatic STRIDE analysis, data flow diagram generation, and automated security threat identification. Use when: (1) Creating threat models programmatically using Python code, (2) Generating data flow diagrams (DFDs) with automatic STRIDE threat identification, (3) Integrating threat modeling into CI/CD pipelines and shift-left security practices, (4) Analyzing system architecture for security threats across trust boundaries, (5) Producing threat reports with STRIDE categories and mitigation recommendations, (6) Maintaining threat models as code for version control and automation.
AgentSecOps/SecOpsAgentKit 84
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container-grype
Container 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.
AgentSecOps/SecOpsAgentKit 84
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iac-checkov
Infrastructure as Code (IaC) security scanning using Checkov with 750+ built-in policies for Terraform, CloudFormation, Kubernetes, Dockerfile, and ARM templates. Use when: (1) Scanning IaC files for security misconfigurations and compliance violations, (2) Validating cloud infrastructure against CIS, PCI-DSS, HIPAA, and SOC2 benchmarks, (3) Detecting secrets and hardcoded credentials in IaC, (4) Implementing policy-as-code in CI/CD pipelines, (5) Generating compliance reports with remediation guidance for cloud security posture management.
AgentSecOps/SecOpsAgentKit 84
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secrets-gitleaks
Hardcoded secret detection and prevention in git repositories and codebases using Gitleaks. Identifies passwords, API keys, tokens, and credentials through regex-based pattern matching and entropy analysis. Use when: (1) Scanning repositories for exposed secrets and credentials, (2) Implementing pre-commit hooks to prevent secret leakage, (3) Integrating secret detection into CI/CD pipelines, (4) Auditing codebases for compliance violations (PCI-DSS, SOC2, GDPR), (5) Establishing baseline secret detection and tracking new exposures, (6) Remediating historical secret exposures in git history.
AgentSecOps/SecOpsAgentKit 84
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sca-trivy
Software Composition Analysis (SCA) and container vulnerability scanning using Aqua Trivy for identifying CVE vulnerabilities in dependencies, container images, IaC misconfigurations, and license compliance risks. Use when: (1) Scanning container images and filesystems for vulnerabilities and misconfigurations, (2) Analyzing dependencies for known CVEs across multiple languages (Go, Python, Node.js, Java, etc.), (3) Detecting IaC security issues in Terraform, Kubernetes, Dockerfile, (4) Integrating vulnerability scanning into CI/CD pipelines with SARIF output, (5) Generating Software Bill of Materials (SBOM) in CycloneDX or SPDX format, (6) Prioritizing remediation by CVSS score and exploitability.
AgentSecOps/SecOpsAgentKit 84