AI & ML

stevenke1981 Skill

當使用者需要「Jira 工作流管理員」處理專案管理相關任務時啟動。本 Agent 會先確認目標、資料來源、限制與驗收標準，再建立範圍、責任、里程碑、風險、依賴與驗收清楚的執行計畫，並輸出證據、風險、下一步與需要人工覆核的事項。

stevenke1981 Skill

當使用者需要「語音 AI 整合工程師」處理工程研發相關任務時啟動。本 Agent 會先確認目標、資料來源、限制與驗收標準，再把需求轉成可實作、可測試、可回滾的工程方案，並輸出證據、風險、下一步與需要人工覆核的事項。

stevenke1981 Skill

當使用者需要「微信小程式工程師」處理工程研發相關任務時啟動。本 Agent 會先確認目標、資料來源、限制與驗收標準，再把需求轉成可實作、可測試、可回滾的工程方案，並輸出證據、風險、下一步與需要人工覆核的事項。

stevenke1981 Skill

當使用者需要「3D 列印線材優化專家」處理工程研發相關任務時啟動。本 Agent 會先確認目標、資料來源、限制與驗收標準，再把需求轉成可實作、可測試、可回滾的工程方案，並輸出證據、風險、下一步與需要人工覆核的事項。

stevenke1981 Skill

當使用者需要「Solidity 智慧合約工程師」處理工程研發相關任務時啟動。本 Agent 會先確認目標、資料來源、限制與驗收標準，再把需求轉成可實作、可測試、可回滾的工程方案，並輸出證據、風險、下一步與需要人工覆核的事項。

liqiongyu Bundle

Design/redesign org structure and operating model: current-state map, target blueprint, transition plan.

human-avatar Skill

Measures uncertainty, surprise, and information content using Shannon entropy. Use when asked 'how much information does this actually contain', 'how uncertain is this source', 'is this result surprising', 'what should I update on', 'where is the real information in this dataset', or when you need to distinguish high-information from low-information inputs.

human-avatar Skill

Evaluate a third-party vendor, supplier, partner, or integration against ethical standards before signing a contract or shipping their code or service. Use when considering a new supplier, SaaS tool, data provider, API integration, outsourcing arrangement, or partnership. TRIGGERS: 'vet this vendor', 'is this supplier ok', 'ethics check on this partner', 'should we use this third party', any third-party evaluation where labour practices, data handling, business model, or alignment with values is a consideration.

stevenke1981 Skill

當使用者需要「文化智慧策略師」處理專業支援相關任務時啟動。本 Agent 會先確認目標、資料來源、限制與驗收標準，再把目標、受眾與風格限制轉成可直接使用的創作交付物，並輸出證據、風險、下一步與需要人工覆核的事項。

stevenke1981 Skill

當使用者需要「自主優化架構師」處理工程研發相關任務時啟動。本 Agent 會先確認目標、資料來源、限制與驗收標準，再把需求轉成可實作、可測試、可回滾的工程方案，並輸出證據、風險、下一步與需要人工覆核的事項。

harshahosur81 Skill

Build production-ready LLM applications, advanced RAG systems, and intelligent agents. Implements vector search, multimodal AI, agent orchestration, and enterprise AI integrations. Use PROACTIVELY for LLM features, chatbots, AI agents, or AI-powered applications.

harshahosur81 Skill

Build production ML systems with PyTorch 2.x, TensorFlow, and modern ML frameworks. Implements model serving, feature engineering, A/B testing, and monitoring. Use PROACTIVELY for ML model deployment, inference optimization, or production ML infrastructure.

jamie-bitflight Skill

Guide for creating Claude Code plugin hooks — language selection heuristic (Node.js default, match project runtime when obvious), hooks.json configuration, event selection, prompt-based vs command hooks, ${CLAUDE_PLUGIN_ROOT} paths, stdio suppression, timeout sizing, and testing. Use when adding hooks to a plugin, creating PreToolUse/PostToolUse/Stop/SubagentStop/SessionStart/UserPromptSubmit hooks, or wiring hook scripts to hooks.json.

jamie-bitflight Bundle

Decompose substantive work into phases, dispatch each phase to a sub-agent, and adjudicate what comes back. Use whenever a request asks for implementation, investigation, a fix, a review, or any change to files — including small ones — and whenever you are about to read source or run a diagnostic yourself instead of handing it off. Also use when a report from a sub-agent needs judging, when a phase needs re-dispatching, or when a user names one instance of a pattern. Does not apply when your own prompt begins "Your ROLE_TYPE is sub-agent." — then follow references/sub-agent-contract.md instead.

jamie-bitflight Skill

Orchestrate parallel agent dispatch as a manager — not a micromanager. Use when coordinating 2+ independent workers, running SAM task waves, relaying discoveries between worker waves, handling blockers, or synthesizing results. Covers both SAM structured dispatch (the task does the work) and ad-hoc dispatch (reference agent-orchestration for prompt template).

jamie-bitflight Bundle

Create high-quality Claude Code agents from scratch or by adapting existing agents as templates. Use when the user wants to create a new agent, modify agent configurations, build specialized subagents, or design agent architectures. Guides through requirements gathering, template selection, and agent file generation following Anthropic best practices (v2.1.63+).

liqiongyu Bundle

Convert a Refound/Lenny Skill into an agent-executable Skill Pack.

harshahosur81 Skill

Systematic improvement of existing agents through performance analysis, prompt engineering, and continuous iteration.

human-avatar Skill

Surfaces and audits the internal representations that drive perception and decision-making. Use when asked 'what assumptions am I making', 'why do I keep seeing this the same way', 'what model is driving this decision', 'I think I'm missing something about how this works', 'what's my mental model here', or when a belief or decision pattern needs to be examined from the inside.

human-avatar Skill

Apply Edward de Bono's Random Entry technique — use an unrelated word, object, or image as a creative springboard to break out of cognitive ruts. Use when the user is stuck, wants unexpected inspiration, asks for a random creative prompt, wants to approach something from a completely fresh angle, or says they've exhausted their usual thinking. The randomness is the point — don't skip it.

jamie-bitflight Skill

Hook recipes and working examples — plugin hooks, frontmatter hooks in skills/agents/commands, prompt-based LLM hooks, and complete code examples in Python and Node.js. Use when building hook scripts, integrating hooks into plugins, implementing prompt-based hooks, or looking for hook configuration patterns.

harshahosur81 Skill

Elite AI context engineering specialist mastering dynamic context management, vector databases, knowledge graphs, and intelligent memory systems. Orchestrates context across multi-agent workflows, enterprise AI systems, and long-running projects with 2024/2025 best practices. Use PROACTIVELY for complex AI orchestration.

harshahosur81 Skill

Implement comprehensive evaluation strategies for LLM applications using automated metrics, human feedback, and benchmarking. Use when testing LLM performance, measuring AI application quality, or establishing evaluation frameworks.

harshahosur81 Skill

You are an expert LangChain agent developer specializing in production-grade AI systems using LangChain 0.1+ and LangGraph.

harshahosur81 Skill

Expert prompt engineer specializing in advanced prompting techniques, LLM optimization, and AI system design. Masters chain-of-thought, constitutional AI, and production prompt strategies. Use when building AI features, improving agent performance, or crafting system prompts.

harshahosur81 Skill

You are an expert prompt engineer specializing in crafting effective prompts for LLMs through advanced techniques including constitutional AI, chain-of-thought reasoning, and model-specific optimizati

jamie-bitflight Skill

Rules for orchestrators handling sub-agent results without lossy re-summarization. Activates when receiving agent output, relaying research results, passing data between agents, or combining agent findings. Prevents the failure mode where 'not found' becomes 'doesn't exist' and counts get dropped.

jamie-bitflight Bundle

Use when the primary outcome is creating a new portable Agent Skill directory from one local documentation file, documentation directory, or Git repository, including mixed text and capability-gated binary sources that require exhaustive source-to-output accounting.

jamie-bitflight Skill

Use when executing a SAM task — claims the task via MCP to set it IN PROGRESS, writes active-task context for hooks, loads task-level skills, implements against acceptance criteria, and marks complete via --complete flag. Triggers on task execution within the implement-feature loop or when an agent picks up a specific task from a plan file.

jamie-bitflight Bundle

Per-project plugin configuration via .local.md files — covers the .claude/plugin-name.local.md pattern for storing user-configurable settings with YAML frontmatter and markdown body. Use when implementing plugin settings, reading YAML frontmatter from hooks, creating configuration-driven behavior, managing agent state files, or adding per-project plugin configuration. Covers file structure, parsing techniques, common patterns (temporarily active hooks, agent state management, configuration-driven behavior), security considerations, and best practices.

jamie-bitflight Skill

Start a complete plugin refactoring workflow that analyzes plugin structure, creates a refactoring plan with tasks, and guides through execution. Use when you need to refactor an entire plugin — triggers assessment, design, planning, and parallel agent execution phases.

jamie-bitflight Bundle

Use when implementing a Python feature, adding CLI commands, writing pytest suites, reviewing Python code, debugging, or refactoring. The primary Python engineering workflow orchestrator — classifies the task and delegates through this plugin's own specialist agents (architect → implement → test → review), sized to the task. Delegates to python-cli-architect (implementation), python-pytest-architect (tests), code-reviewer (review), python-cli-design-spec (architecture). Triggers on any Python task requiring specialist agent coordination or multi-agent execution.

jackspace Bundle

OpenAI's traditional stateless APIs: Chat Completions (GPT-5, GPT-5-mini, GPT-5-nano, GPT-4o, GPT-4 Turbo), Embeddings (text-embedding-3-small/large), Images (DALL-E 3 generation, GPT- Image-1 editing), Audio (Whisper transcription and TTS), and Moderation. Covers the openai Node.js SDK and plain fetch for edge runtimes, SSE streaming, function calling and tools, structured outputs with JSON schemas, vision, GPT-5 reasoning_effort and verbosity, error handling, and rate limits. Use when integrating OpenAI into an application, streaming chat completions, generating embeddings for RAG, creating images, transcribing or synthesizing speech, moderating content, deploying OpenAI calls on Cloudflare Workers, or debugging 429 rate limits, 401 invalid API keys, function calling failures, streaming parse errors, embedding dimension mismatches, or token limit exceeded.

jackspace Bundle

Backend AI functionality with Vercel AI SDK v5 - text generation, structured output with Zod, tool calling, and agents. Multi-provider support for OpenAI, Anthropic, Google, and Cloudflare Workers AI. Use when: implementing server-side AI features, generating text/chat completions, creating structured AI outputs with Zod schemas, building AI agents with tools, streaming AI responses, integrating OpenAI/Anthropic/Google/Cloudflare providers, or encountering AI SDK errors like AI_APICallError, AI_NoObjectGeneratedError, streaming failures, or worker startup limits. Keywords: ai sdk core, vercel ai sdk, generateText, streamText, generateObject, streamObject, ai sdk node, ai sdk server, zod ai schema, ai tools calling, ai agent class, openai sdk, anthropic sdk, google gemini sdk, workers-ai-provider, ai streaming backend, multi-provider ai, ai sdk errors, AI_APICallError, AI_NoObjectGeneratedError, streamText fails, worker startup limit ai

jamie-bitflight Skill

Multi-phase Python quality improvement system for file paths passed as arguments. Runs prek/ruff/ty static analysis with auto-fixes, inventories Any types and typing gaps, plans Protocol/Generic/TypeGuard/TypedDict/dataclass modernization, forks a code-reviewer agent to critique the plan, refines the plan, discovers documentation changes, designs interfaces first, forks python-pytest-architect for failing tests, then hands off to snakepolish for implementation. Use when eliminating Any types, addressing technical debt, applying modern Python 3.11+ patterns, modernizing library usage (httpx, orjson), or refactoring for stronger type safety.

jamie-bitflight Bundle

Use when building, extending, or debugging FastMCP v4 (or v3) Python MCP servers. Activates on FastMCP tool/resource/prompt creation, provider and transform implementation (CodeMode, Tool Search), auth setup (MultiAuth, PropelAuth, KeycloakProvider), client SDK usage, FastMCPApp and Generative UI server building, fastmcp-slim client-only installs, nginx reverse proxy deployment, Prefab Apps, OTEL observability, testing, and v3→v4 migration. Grounded in official FastMCP v4 docs plus locally-verified v3 gotchas — zero speculation.