claude

yana-ai

Personal agent operating system for Claude Code. Safety hooks, memory tiers, agents, commands, and cross-engine hard enforcement.

13 on GitHubby Vũ Văn Tâmv1.5.2Apache-2.0updated todaysafety
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Plugin yana-ai from marketplace yana-ai in Horonomos-laps/Yana-AI. Commands read from the repo's manifest — today.

What it installs

Skills (200)

  • 0x4m4--hexstrike-ai

    HexStrike AI — MCP server cho 150+ cybersecurity tools: Nmap, SQLMap, Nuclei, Ghidra, Prowler... AI agent tự chọn tool, chạy pentest, bug bounty automation. Cần authorization.

  • 666ghj--mirofish

    MiroFish — Swarm Intelligence Engine: upload seed data → simulate thousands of agents → predict future trajectories. GraphRAG + multi-agent simulation + interactive chat.

  • 9router-gateway

    Set up 9Router as a local AI gateway so coding agents never stop when a provider quota runs out — one OpenAI-compatible endpoint (localhost:20128) fanning out to 40+ providers with automatic fallback. Use when asked to 'set up 9router', 'cài 9router', 'hết quota Claude thì làm sao', 'fallback provid

  • a2a-protocol-patterns

    Agent-to-Agent (A2A) protocol — Google 2025, 150+ org backing. Agent Cards discovery, task lifecycle (submitted→working→completed), artifacts (text/structured/video), opaque task model. MCP vs A2A split. Auth: bearer/mTLS/signed. Sources: rohitg00/ai-engineering-from-scratch (Apache-2.0).

  • acceptance-orchestrator

    Use when a coding task should be driven end-to-end from issue intake through implementation, review, deployment, and acceptance verification with minimal human re-intervention.

  • accessibility-audit

    Audit UI code for WCAG 2.1 AA compliance — color contrast, keyboard navigation, ARIA roles, focus management, and screen reader compatibility. Use when the user asks to "check accessibility", "make this accessible", "WCAG audit", "a11y review", or before marking any public-facing UI as done. Do NOT

  • accessibility

    Design, implement, and audit inclusive digital products using WCAG 2.2 Level AA

  • acquiring-disk-image-with-dd-and-dcfldd

    Create forensically sound bit-for-bit disk images using dd and dcfldd

  • api-and-interface-design

    Guides stable API and interface design. Use when designing APIs, module boundaries, or any public interface. Use when creating REST or GraphQL endpoints, defining type contracts between modules, or establishing boundaries between frontend and backend.

  • browser-testing-with-devtools

    Tests in real browsers via Chrome DevTools MCP. Use when building or debugging anything that runs in a browser. Use when you need to inspect the DOM, capture console errors, analyze network requests, profile performance, or verify visual output with real runtime data. Requires the chrome-devtools MC

  • ci-cd-and-automation

    Automates CI/CD pipeline setup. Use when setting up or modifying build and deployment pipelines. Use when you need to automate quality gates, configure test runners in CI, or establish deployment strategies.

  • code-review-and-quality

    Conducts multi-axis code review. Use before merging any change. Use when reviewing code written by yourself, another agent, or a human. Use when you need to assess code quality across multiple dimensions before it enters the main branch.

  • code-simplification

    Simplifies code for clarity. Use when refactoring code for clarity without changing behavior. Use when code works but is harder to read, maintain, or extend than it should be. Use when reviewing code that has accumulated unnecessary complexity.

  • context-engineering

    Optimizes agent context setup. Use when starting a new session, when agent output quality degrades, when switching between tasks, or when you need to configure rules files and context for a project.

  • debugging-and-error-recovery

    Guides systematic root-cause debugging. Use when tests fail, builds break, behavior doesn't match expectations, or you encounter any unexpected error. Use when you need a systematic approach to finding and fixing the root cause rather than guessing.

  • deprecation-and-migration

    Manages deprecation and migration. Use when removing old systems, APIs, or features. Use when migrating users from one implementation to another. Use when deciding whether to maintain or sunset existing code.

  • documentation-and-adrs

    Records decisions and documentation. Use when making architectural decisions, changing public APIs, shipping features, or when you need to record context that future engineers and agents will need to understand the codebase.

  • doubt-driven-development

    Subjects every non-trivial decision to a fresh-context adversarial review before it stands. Use when correctness matters more than speed, when working in unfamiliar code, when stakes are high (production, security-sensitive logic, irreversible operations), or any time a confident output would be che

  • frontend-ui-engineering

    Builds production-quality UIs. Use when building or modifying user-facing interfaces. Use when creating components, implementing layouts, managing state, or when the output needs to look and feel production-quality rather than AI-generated.

  • git-workflow-and-versioning

    Structures git workflow practices. Use when making any code change. Use when committing, branching, resolving conflicts, or when you need to organize work across multiple parallel streams.

  • idea-refine

    Refines raw ideas into sharp, actionable concepts through structured divergent and convergent thinking. Use when an idea is still vague, when you need to stress-test assumptions before committing to a plan, or when you want to expand options before converging on one. Triggers on "ideate", "refine th

  • incremental-implementation

    Delivers changes incrementally. Use when implementing any feature or change that touches more than one file. Use when you're about to write a large amount of code at once, or when a task feels too big to land in one step.

  • interview-me

    Extracts what the user actually wants instead of what they think they should want. Achieves this through one-question-at-a-time interview until ~95% confidence about the underlying intent. Use when an ask is underspecified ("build me X" without "for whom" or "why now"), when the user explicitly invo

  • observability-and-instrumentation

    Instruments code so production behavior is visible and diagnosable. Use when adding logging, metrics, tracing, or alerting. Use when shipping any feature that runs in production and you need evidence it works. Use when production issues are reported but you can't tell what happened from the availabl

  • performance-optimization

    Optimizes application performance. Use when performance requirements exist, when you suspect performance regressions, or when Core Web Vitals or load times need improvement. Use when profiling reveals bottlenecks that need fixing.

  • planning-and-task-breakdown

    Breaks work into ordered tasks. Use when you have a spec or clear requirements and need to break work into implementable tasks. Use when a task feels too large to start, when you need to estimate scope, or when parallel work is possible.

  • security-and-hardening

    Hardens code against vulnerabilities. Use when handling user input, authentication, data storage, or external integrations. Use when building any feature that accepts untrusted data, manages user sessions, or interacts with third-party services.

  • shipping-and-launch

    Prepares production launches. Use when preparing to deploy to production. Use when you need a pre-launch checklist, when setting up monitoring, when planning a staged rollout, or when you need a rollback strategy.

  • source-driven-development

    Grounds every implementation decision in official documentation. Use when you want authoritative, source-cited code free from outdated patterns. Use when building with any framework or library where correctness matters.

  • spec-driven-development

    Creates specs before coding. Use when starting a new project, feature, or significant change and no specification exists yet. Use when requirements are unclear, ambiguous, or only exist as a vague idea.

  • test-driven-development

    Drives development with tests. Use when implementing any logic, fixing any bug, or changing any behavior. Use when you need to prove that code works, when a bug report arrives, or when you're about to modify existing functionality.

  • using-agent-skills

    Discovers and invokes agent skills. Use when starting a session or when you need to discover which skill applies to the current task. This is the meta-skill that governs how all other skills are discovered and invoked.

  • adr-writing

    Write and maintain Architecture Decision Records (ADRs) — when to write one, the standard format, status lifecycle, how to link related decisions, and how to surface ADRs in a codebase. Use when asked to "write an ADR", "document this decision", "architecture decision record", "why did we choose X o

  • advanced-color-math

    Advanced color science and dynamic palette generation from 20 production repos. LCH/OKLAB perceptual math, dark-mode pair algorithms, contrast enforcement, gamut mapping, CSS color-mix(), and color extraction from images. Sources: chroma.js, culori, color.js, tinycolor2, d3-color, radix-ui/colors, p

  • advanced-motion-easing

    Production-grade motion engineering from 20 repos. Spring physics, custom easing curves, GPU compositing rules, scroll-driven animations, micro-interactions, Lottie integration, reduced-motion, and stagger choreography. Sources: framer/motion, pmndrs/react-spring, popmotion, animejs, GSAP, auto-anim

  • advanced-typography

    Advanced typography engineering from 20 production repos. Fluid type scales, optical sizing, font subsetting, vertical metrics normalization, CJK/Vietnamese spacing, text-wrap balance, variable fonts, and readability constraints. Sources: rsms/inter, nicowillis/capsize, fontsource, typetura, modular

  • adversarial-prompt-testing

    Test LLM applications for prompt injection, jailbreak, data exfiltration, and indirect injection attacks — attack taxonomy, test harness design, automated red-team probes, defense patterns, and evaluation rubrics. Use when asked about "prompt injection", "jailbreak", "LLM red team", "adversarial pro

  • adversarial-team-pattern

    Template pattern for multi-agent analysis where agents hold opposing mandates. Use when spawning subagents for complex research, code review, architecture decisions, or risk assessment. Triggers on: 'adversarial team', 'devil's advocate analysis', 'multi-perspective review', 'challenge this decision

  • aesthetic-anchor

    Lock a specific visual aesthetic before building UI — choose one of 8 design anchors (Swiss, Industrial, Brutalist, Aurora Maximalism, Chaotic Maximalism, Retro-Futuristic, Organic, Lo-Fi) and apply its palette, typography, and texture tokens consistently throughout the build. Use when the user says

  • affaan-m--ecc

    Harness-native operator system cho agentic work — skills, instincts, memory optimization, security scanning, cross-harness workflows. 205K stars.

  • ag-kit

    Use when asked to set up AI agent templates with coordinator mode, implement persistent agent memory, compress context for long-running agents, build multi-agent workflows with skills/agents/workflows structure, or use the .agents/ folder convention for AI-native editors. Triggers on: 'ag-kit', 'ant

  • agency-agents

    Library of 232 AI agent personalities across 16 business divisions — Engineering, Design, Sales, Marketing, Security, Finance, Game Dev, GIS, Academic and more. Platform-agnostic (Claude Code, Cursor, Copilot, Windsurf, Aider, Gemini CLI). Triggers on: 'agency agents', 'agent library', 'agent person

  • agent-architecture-audit

    Full-stack diagnostic for agent and LLM applications. Audits the 12-layer agent stack for wrapper regression, memory pollution, tool discipline failures, hidden repair loops, and rendering corruption. Produces severity-ranked findings with code-first fixes. Essential for developers building agent ap

  • agent-attack-surface

    Attack surface mapping for LLM agent systems. Threat model, blast radius calculation, entry points, trust boundaries, lateral movement paths, and MITRE ATLAS techniques for AI agents. Sources: MITRE/ATLAS, OWASP LLM Top 10, microsoft/promptbench, greshake/indirect-prompt-injection, google/sec-gemini

  • agent-eval

    Head-to-head comparison of coding agents (Claude Code, Aider, Codex, etc.) on custom tasks with pass rate, cost, time, and consistency metrics

  • agent-evaluation

    Testing and benchmarking LLM agents including behavioral testing,

  • agent-harness-construction

    Design and optimize AI agent action spaces, tool definitions, and observation formatting for higher completion rates.

  • agent-introspection-debugging

    Structured self-debugging workflow for AI agent failures using capture, diagnosis, contained recovery, and introspection reports.

  • agent-memory-security

    Agent memory system security — poisoning prevention, L1/L2 integrity, context window attacks, memory exfiltration defense, and session isolation. Sources: anthropic/model-spec (minimal footprint), OWASP LLM01/LLM02, langchain-ai/langchain (memory modules), memgpt/memgpt, microsoft/autogen (agent mem

  • agent-messaging-patterns

    Wire inter-agent communication — signal files, shared state via files/KV, approval queues, budget delegation, capability passing, and broadcast/ subscribe patterns for agents running in parallel terminals or processes. Use when asked about "agents communicating", "agent signals", "how agent A tells

  • agent-middleware-gate

    Intercept-layer skill for wrapping all agent tool calls through a sanitize-mutate-execute proxy pipeline. Onion middleware composition (koa), request/response interceptors (axios), scope-aware handler chains (express), near-zero-latency proxy routing (caddy), and in-memory pipe streams (piping-serve

  • agent-orchestrator

    Meta-skill que orquestra todos os agentes do ecossistema. Scan automatico de skills, match por capacidades, coordenacao de workflows multi-skill e registry management.

  • agent-payment-x402

    Add x402 payment execution to AI agents with per-task budgets, spending controls, and non-custodial wallets. Supports Base through agentwallet-sdk and X Layer through OKX Payments / OKX Agent Payments Protocol.

  • agent-reach

    Use when an agent needs to read the internet without paid API keys — Twitter/X, Reddit, YouTube, Bilibili, GitHub, TikTok, Xiaohongshu, RSS, web pages. Triggers on: 'agent-reach', 'agent đọc internet', 'đọc Twitter không API', 'đọc Reddit không API', 'agent xem YouTube', 'agent đọc Bilibili', 'agent

  • agent-safety-patterns

    Design safe AI agent systems — capability restriction, sandboxed execution, human-in-the-loop gates, anomaly detection, rollback on unexpected behavior, blast radius limiting, and output verification before acting. Use when asked about "agent safety", "safe agent design", "AI agent guardrails", "cap

  • agent-sort

    Build an evidence-backed ECC install plan for a specific repo by sorting skills, commands, rules, hooks, and extras into DAILY vs LIBRARY buckets using parallel repo-aware review passes. Use when ECC should be trimmed to what a project actually needs instead of loading the full bundle.

  • agent-telemetry

    Telemetry and observability patterns for AI agent systems. Structured multi-transport logging, OpenTelemetry traces/spans through action gates, crash diagnostics, ultra-low-overhead logging, and percentile latency metrics. Sources: winstonjs/winston, open-telemetry/opentelemetry-js, nodejs/node-repo

  • agent-verification-gate

    Deterministic verification gate for agent task close-out. Reads scope contract, rule report, feedback log, and diff — emits a single verification_report.json verdict. Block-severity failures cannot be overridden by the agent. Sources: rohitg00/ai-engineering-from-scratch (Apache-2.0).

  • agentfolio

    Skill for discovering and researching autonomous AI agents, tools, and ecosystems using the AgentFolio directory.

  • agenthub

    Multi-agent collaboration plugin that spawns N parallel subagents competing on the same task via git worktree isolation. Agents work independently, results are evaluated by metric or LLM judge, and the best branch is merged. Use when: user wants multiple approaches tried in parallel — code optimizat

  • agentic-actions-auditor

    Audits GitHub Actions workflows for security vulnerabilities in AI agent integrations including Claude Code Action, Gemini CLI, OpenAI Codex, and GitHub AI Inference. Detects attack vectors where attacker-controlled input reaches. AI agents running in CI/CD pipelines.

  • agentic-engineering

    Operate as an agentic engineer using eval-first execution, decomposition, and cost-aware model routing.

  • agentic-failure-modes

    MASFT taxonomy of multi-agent failure modes (Berkeley 2025) — 14 modes in 3 categories. Five industry-recurring modes: hallucinated actions, scope creep, cascading errors, context loss, tool misuse. Detection, monitoring, and mitigation patterns. Sources: rohitg00/ai-engineering-from-scratch (Apache

  • agentic-os

    Build persistent multi-agent operating systems on Claude Code. Covers kernel architecture, specialist agents, slash commands, file-based memory, scheduled automation, and state management without external databases.

  • agentshield-security-scanner

    AI agent configuration security scanner — 102 rules across secrets, permissions, hooks, MCP servers, and agent definitions. Detects hardcoded secrets, permission misconfigurations, hook injection, MCP vulnerabilities, and prompt injection. Use before deploying any Claude Code/AI agent configuration.

  • agentskills--spec

    Specification và docs cho Agent Skills format — chuẩn open format để extend AI agent capabilities. Dùng khi viết SKILL.md mới hoặc cần hiểu spec.

  • agenttrace-session-audit

    Audit local AI coding-agent sessions with agenttrace for cost, tool failures, latency, anomalies, health, diffs, and CI gates.

  • agno

    Build production AI agents with Agno (formerly Phidata) — define Agent with model/tools/instructions/memory/knowledge, compose Agent Teams with coordinator routing, add Storage for persistence, and integrate RAG via built-in KnowledgeBase with PDF/URL/text sources.

  • ai-code-maintainability

    Write production-safe code that survives maintenance — avoid the 15 patterns AI agents commonly generate that work on day 1 but break 3 months later; enforce error handling, logging, type safety, no magic values, and testable structure before writing any code.

  • ai-first-engineering

    Engineering practices for teams where AI generates most code. Use when planning architecture for AI-assisted projects, defining code review standards for AI-generated code, structuring requirements for agent handoff, or asking "how do we work with AI at scale?", "our AI code keeps breaking", "agents

  • ai-gateway-patterns

    AI gateways for LLM serving — provider routing, fallback, retries, rate limiting, secrets, observability, guardrails. LiteLLM (OSS, <500 RPS), Portkey (guardrails, Apache 2.0 2026), Kong AI Gateway (228% faster than Portkey at scale), Bifrost (retry/fallback). Sources: rohitg00/ai-engineering-from-s

  • ai-md

    Convert human-written CLAUDE.md into AI-native structured-label format. Battle-tested across 4 models. Same rules, fewer tokens, higher compliance.

  • ai-native-cli

    Design spec with 98 rules for building CLI tools that AI agents can safely use. Covers structured JSON output, error handling, input contracts, safety guardrails, exit codes, and agent self-description.

  • ai-product

    Every product will be AI-powered. The question is whether you'll

  • ai-regression-testing

    Write regression tests targeting AI-introduced bugs and blind spots. Use when "a bug was found and fixed — prevent re-introduction", "AI agent modified API routes or backend logic", "running /bug-check", "we keep seeing the same type of bug come back", "AI keeps making the same mistake". Do NOT use

  • ai-system-prompts-intel

    Intelligence on leaked/published system prompts from 30+ AI coding tools (Cursor, Windsurf, Claude Code, GitHub Copilot, Devin, v0, Lovable, Replit, Warp) and general chat products (Claude, ChatGPT, Gemini, Grok, Perplexity, Mistral, Notion AI). Use for competitive analysis, prompt engineering resea

  • ai-team-workflow

    Organize AI agents as a structured team — role assignment, proposal/vote/ review/ship cycle, cross-agent code review, consensus mechanisms, and escalation to human for deadlocks. Use when asked about "AI team", "agents working as a team", "multi-agent workflow", "agent roles", "agent review", "agent

  • agency-client

    Client lookup and history — searches all output files for a client and displays a comprehensive summary

  • agency-onboard

    Full Agency Onboard — launches 5 parallel audit teams and produces a unified client-ready report with composite scoring

  • agency-pipeline

    Prospect Pipeline Manager — scans all audit files to build a scored, staged pipeline view with revenue projections

  • aiagency--agency-propose
  • aiagency--agency-quick
  • aiagency--agency-report-pdf
  • aiagency--agency-status
  • airflow-dag-patterns
  • alibaba--open-code-review
  • alirezarezvani--agent-factory
  • alirezarezvani--app-store-optimization
  • alirezarezvani--aws-solution-architect
  • alirezarezvani--claude-md-enhancer
  • alirezarezvani--codex-cli-bridge
  • alirezarezvani--content-trend-researcher
  • alirezarezvani--hook-factory
  • alirezarezvani--ms365-tenant-manager
  • alirezarezvani--prompt-factory
  • alirezarezvani--scrum-master-agent
  • alirezarezvani--slash-command-factory
  • alirezarezvani--social-media-analyzer
  • alirezarezvani--tdd-guide
  • alirezarezvani--tech-stack-evaluator
  • analyzing-active-directory-acl-abuse
  • analyzing-android-malware-with-apktool
  • analyzing-api-gateway-access-logs
  • analyzing-apt-group-with-mitre-navigator
  • analyzing-azure-activity-logs-for-threats
  • analyzing-bootkit-and-rootkit-samples
  • analyzing-browser-forensics-with-hindsight
  • analyzing-campaign-attribution-evidence
  • analyzing-certificate-transparency-for-phishing
  • analyzing-cloud-storage-access-patterns
  • analyzing-cobalt-strike-beacon-configuration
  • analyzing-cobaltstrike-malleable-c2-profiles
  • analyzing-command-and-control-communication
  • analyzing-cyber-kill-chain
  • analyzing-disk-image-with-autopsy
  • analyzing-dns-logs-for-exfiltration
  • analyzing-docker-container-forensics
  • analyzing-email-headers-for-phishing-investigation
  • analyzing-ethereum-smart-contract-vulnerabilities
  • analyzing-golang-malware-with-ghidra
  • analyzing-heap-spray-exploitation
  • analyzing-indicators-of-compromise
  • analyzing-ios-app-security-with-objection
  • analyzing-kubernetes-audit-logs
  • analyzing-linux-audit-logs-for-intrusion
  • analyzing-linux-elf-malware
  • analyzing-linux-kernel-rootkits
  • analyzing-linux-system-artifacts
  • analyzing-lnk-file-and-jump-list-artifacts
  • analyzing-macro-malware-in-office-documents
  • analyzing-malicious-pdf-with-peepdf
  • analyzing-malicious-url-with-urlscan
  • analyzing-malware-behavior-with-cuckoo-sandbox
  • analyzing-malware-family-relationships-with-malpedia
  • analyzing-malware-persistence-with-autoruns
  • analyzing-malware-sandbox-evasion-techniques
  • analyzing-memory-dumps-with-volatility
  • analyzing-memory-forensics-with-lime-and-volatility
  • analyzing-mft-for-deleted-file-recovery
  • analyzing-network-covert-channels-in-malware
  • analyzing-network-flow-data-with-netflow
  • analyzing-network-packets-with-scapy
  • analyzing-network-traffic-for-incidents
  • analyzing-network-traffic-of-malware
  • analyzing-network-traffic-with-wireshark
  • analyzing-office365-audit-logs-for-compromise
  • analyzing-outlook-pst-for-email-forensics
  • analyzing-packed-malware-with-upx-unpacker
  • analyzing-pdf-malware-with-pdfid
  • analyzing-persistence-mechanisms-in-linux
  • analyzing-powershell-empire-artifacts
  • analyzing-powershell-script-block-logging
  • analyzing-prefetch-files-for-execution-history
  • analyzing-ransomware-encryption-mechanisms
  • analyzing-ransomware-leak-site-intelligence
  • analyzing-ransomware-network-indicators
  • analyzing-ransomware-payment-wallets
  • analyzing-sbom-for-supply-chain-vulnerabilities
  • analyzing-security-logs-with-splunk
  • analyzing-slack-space-and-file-system-artifacts
  • analyzing-supply-chain-malware-artifacts
  • analyzing-threat-actor-ttps-with-mitre-attack
  • analyzing-threat-actor-ttps-with-mitre-navigator
  • analyzing-threat-intelligence-feeds
  • analyzing-threat-landscape-with-misp
  • analyzing-tls-certificate-transparency-logs
  • analyzing-typosquatting-domains-with-dnstwist
  • analyzing-uefi-bootkit-persistence
  • analyzing-usb-device-connection-history
  • analyzing-web-server-logs-for-intrusion
  • analyzing-windows-amcache-artifacts
  • analyzing-windows-event-logs-in-splunk
  • analyzing-windows-lnk-files-for-artifacts
  • analyzing-windows-prefetch-with-python
  • analyzing-windows-registry-for-artifacts
  • analyzing-windows-shellbag-artifacts
  • android-clean-architecture
  • angular-best-practices
  • angular-developer
  • angular-state-management
  • angular-ui-patterns
  • angular
  • animation-principles
  • animejs-animation
  • api-connector-builder
  • api-design-patterns
  • api-design
  • api-rate-limiting
  • app-store-preflight
  • appdeploy
  • append-only-hypercore
  • apply-premium-background
  • architecture-decision-records
  • architecture
  • archive-stream-patterns
  • argocd-gitops
  • article-writing
  • artifacts-builder
  • arxiv-research
  • ashishpatel26--500-ai-projects
View source on GitHub yanacuti1121.github.io

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