Claude Skills by thedixitjain

Agent skill for v3-queen-coordinator - invoke with $agent-v3-queen-coordinator

Agent skill for v3-security-architect - invoke with $agent-v3-security-architect

Agent skill for worker-specialist - invoke with $agent-worker-specialist

Agent skill for workflow-automation - invoke with $agent-workflow-automation

Design production-grade multi-agent workflows with clear pattern choice (sequential, parallel, hierarchical), handoff contracts, failure handling, and cost/context controls. Use when architecting a multi-step agent pipeline, choosing between single-agent vs multi-agent approaches, or refactoring an LLM workflow that suffers from context bloat or unreliable handoffs.

../../../engineering/skills/agent-workflow-designer/SKILL.md

Agent skill for workflow - invoke with $agent-workflow

Spin up isolated sandboxes (\\\"boxes\\\") for coding agents, run them in parallel, queue background runs with -i, and push commits safely through the host relay. Use when the user wants to run Claude Code / Codex / OpenCode in a sandbox, start more boxes, attach to a running box, or otherwise operate the `agentbox` CLI on their laptop.

Master advanced AgentDB features including QUIC synchronization, multi-database management, custom distance metrics, hybrid search, and distributed systems integration. Use when building distributed AI systems, multi-agent coordination, or advanced vector search applications.

Master advanced AgentDB features including QUIC synchronization, multi-database management, custom distance metrics, hybrid search, and distributed systems integration. Use when building distributed AI systems, multi-agent coordination, or advanced vector search applications.

Create and train AI learning plugins with AgentDB's 9 reinforcement learning algorithms. Includes Decision Transformer, Q-Learning, SARSA, Actor-Critic, and more. Use when building self-learning agents, implementing RL, or optimizing agent behavior through experience.

Orchestrate autonomous AI development pipelines through your Kanban board (Asana, GitHub Projects, Linear). Manages multi-worker Claude Code dispatch, deterministic quality gates, adversarial review, per-task cost tracking, and crash-proof pipeline execution.

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

Send explicit, user-requested Telegram messages and files from an agent session through the local Agentgram command-line tool.

> 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.

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, including env var intermediary patterns, direct expression injection, dangerous sandbox configurations, and wildcard user allowlists. Use when reviewing workflow files that invoke AI coding agents, auditing CI/CD pipeline securit...

作为代理工程师，采用评估优先执行、分解和成本感知模型路由进行操作。

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

評価ファースト実行、分解、コスト対応モデルルーティングを使用してエージェニックエンジニアとして動作します。

> Operate as an agentic engineer using eval-first execution, decomposition, and cost-aware model routing. Use when AI agents perform most implementation work and humans enforce quality and risk controls.

| Patterns and techniques for evaluating and improving AI agent outputs. Use this skill when: Implementing self-critique and reflection loops Building evaluator-optimizer pipelines for quality-critical generation Creating test-driven code refinement workflows Designing rubric-based or LLM-as-judge evaluation systems Adding iterative improvement to agent outputs (code, reports, analysis) Measuring and improving agent response quality

| Quantum-resistant, self-learning version control for AI agents with ReasoningBank intelligence and multi-agent coordination

Quantum-resistant, self-learning version control for AI agents with ReasoningBank intelligence and multi-agent coordination

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.

Claude Code 上に永続的なマルチエージェントオペレーティングシステムを構築します。カーネルアーキテクチャ、スペシャリストエージェント、スラッシュコマンド、ファイルベースのメモリ、スケジュールされた自動化、外部データベースなしの状態管理をカバーします。

Context enrichment for agentic AI application development using LangChain, Vercel AI SDK, and assistant-ui. Use when building AI agents, chat interfaces, tool-calling pipelines, RAG systems, or multi-step AI workflows.

Agentic Workflow Pattern

Route gh-aw workflow design/create/debug/upgrade requests to the right prompts.

Conversational AI-first interface with minimal controls, clear outcomes, and delegated task flows for agentic workflows.

Guide for integrating Agentica SDK with Claude Code CLI proxy

Build Python agents with Agentica SDK - @agentic decorator, spawn(), persistence, MCP integration

Spawn Agentica multi-agent patterns

Email infrastructure for AI agents. Create accounts, send/receive emails, manage webhooks, and check karma balance via the AgentMail API.

Give the agent its own inbox: send and receive email.

Build AI phone agents with AgentPhone API. Use when the user wants to make phone calls, send/receive SMS, manage phone numbers, create voice agents, set up webhooks, or check usage — anything related to telephony, phone numbers, or voice AI.

Use for Agentry setup or use; analytics, logging, error monitoring, deploy attribution, telemetry, production investigation, or agentic automation.

Maintain AGENTS.md-based project instructions for tools that support AGENTS.md. Use for instruction audits, session learnings, AGENTS.md updates, or migrating useful CLAUDE.md rules into a shared instruction source. Not for general docs, code review, runtime debugging, or global memory unless asked.

This skill should be used when the user asks to \"create AGENTS.md\", \"update AGENTS.md\", \"maintain agent docs\", \"set up CLAUDE.md\", or needs to keep agent instructions concise. Enforces research-backed best practices for minimal, high-signal agent documentation.

Build container-based Foundry Agents with Azure AI Projects SDK (ImageBasedHostedAgentDefinition). Use when creating hosted agents with custom container images in Azure AI Foundry.

Audit local AI coding-agent sessions with agenttrace. Use when the user asks to inspect Claude Code, Codex CLI, Gemini CLI, Qwen Code, Cline, Aider, Cursor exports, Hermes Agent, OpenCode, OpenClaw, Pi, Oh My Pi, Kimi CLI, Copilot-style logs, or generic JSON/JSONL traces for cost, tokens, tool failures, latency, anomalies, health, diffs, or CI gates.

Use when framing the system and describing the model for an Agricultural Systems (AgSy) manuscript — defining system boundaries, components, hierarchical levels, and feedbacks, then choosing, describing, and calibrating the model (process/simulation, whole-farm, bio-economic, agent-based, or integrated assessment). This is the distinctive core of an AgSy paper. Structures the model and system; it does not run code for you.

> Keep the AG-UI .NET SDK at feature and wire-format PARITY with the canonical reference SDKs (TypeScript is the source of truth; Python is types/encoder only). USE FOR: porting a feature/event/behavior that landed in the TS (or Python) SDK into .NET, verifying the .NET wire format (JSON, SSE, protobuf) matches the reference, locating where the reference implementation and compatibility fixtures live, mapping a TS concept to the .NET event/client/encoder model, resolving an upstream protocol ...

> Keep the AG-UI .NET SDK docs (sdks/dotnet/AGENTS.md and docs/architecture.md) in sync with the real code tree after structural changes. USE FOR: \"update AGENTS.md / docs/architecture.md\", \"check the dotnet docs are current\", verifying docs after a .NET SDK refactor (package rename, added/removed project, changed endpoint pattern, new/renamed test project, sample step added, new convention). DO NOT USE FOR: writing product code or tests (follow AGENTS.md itself), Python/TypeScript SDK do...

> Orchestrator/hub for implementing a feature or change in the AG-UI .NET SDK (sdks/dotnet). USE FOR: \"what's the workflow\", \"what order do I do things in\", \"how do I implement a feature in the .NET SDK\", starting any non-trivial AG-UI .NET SDK change, planning the end-to-end steps and definition-of-done (code + AOT serialization + client/server mapping + unit/integration/cross-language tests + docs + PublicAPI + AGENTS.md sync). DO NOT USE FOR: the deep how-to of a single step — this s...

Use an explicitly selected AGY runtime for

Compare Claude Code and Codex on the same real code-change task with isolated worktrees, identical gates, transcripts, time, and cost.

AI agent development workflow for building autonomous agents, multi-agent systems, and agent orchestration with CrewAI, LangGraph, and custom agents.

Expert in designing and building autonomous AI agents. Masters tool use, memory systems, planning strategies, and multi-agent orchestration.

AI驱动的综合健康分析系统，整合多维度健康数据、识别异常模式、预测健康风险、提供个性化建议。支持智能问答和AI健康报告生成。

>- Use after generating code, after accepting AI suggestions, or when reviewing AI-written modules. Also use when code works but feels brittle, when error handling seems thin, when orphaned resources or missing cleanup are suspected, or when the agent claims done but hidden debt may exist. Catches the specific failure patterns AI agents produce that humans would not.