AI & ML

jamie-bitflight Bundle

Audit agent lifecycle — validates agent execution capability against configuration. Accepts plugin path, runs 8 semantic audits (capability vs config alignment, skill loading correctness, inter-agent contracts, prompt contradictions, tool sufficiency, dead agents, scriptable patterns, pattern learning), writes reports to .plugin-creator/audits/. Use when auditing agent lifecycle, checking agent capabilities, verifying tool access, finding dead agents, validating agent contract alignment, or confirming agents can execute workflows.

jamie-bitflight Bundle

This skill should be used when analyzing Claude Code session transcripts, reviewing agent performance, finding anti-patterns or tool misuse, mining workflow patterns, running kaizen analysis, debugging agent behavior, or performing session forensics.

jamie-bitflight Bundle

Use when the plan_ref returned by add-new-feature is provided. Executes the SAM implementation loop — dispatches ready tasks to specialist agents in parallel, manages bookend tasks (T0 baseline capture and TN verification), tracks concerns and contract violations per task, and relies on hooks to update task status. Manages task batches via sam_plan and sam_task MCP tools.

jamie-bitflight Skill

Design and run controlled experiments using the experiment-registry MCP server — domain-agnostic, pluggable, mechanically enforced. Use when you need evidence that a change actually improves behaviour.

jamie-bitflight Skill

Provides Python-specific code review rules for the dh code-reviewer agent. Activates on pyproject.toml or *.py file detection — enforces uv, ruff, ty, pytest, type annotation, error handling, and Python 3.11+ idioms including pathlib, match statements, and modern union syntax.

lifangda Bundle

Comprehensive healthcare AI toolkit for developing, testing, and deploying machine learning models with clinical data. This skill should be used when working with electronic health records (EHR), clinical prediction tasks (mortality, readmission, drug recommendation), medical coding systems (ICD, NDC, ATC), physiological signals (EEG, ECG), healthcare datasets (MIMIC-III/IV, eICU, OMOP), or implementing deep learning models for healthcare applications (RETAIN, SafeDrug, Transformer, GNN).

enuno Skill

MemPalace local-first AI memory system. Use when setting up persistent memory for Claude Code sessions, mining project files or conversation transcripts, querying past context, configuring MCP tools, managing the knowledge graph, or troubleshooting palace operations.

enuno Bundle

LangChain Neo4j integration — Neo4jGraph for Cypher queries and schema inspection, GraphCypherQAChain for natural-language-to-Cypher Q&A, Neo4jVector for vector/hybrid RAG, Neo4jSaver LangGraph checkpointer, Neo4jChatMessageHistory, and GraphDocument/Node/Relationship for knowledge graph construction.

enuno Bundle

LangChain Redis integration — RedisVectorStore for RAG, RedisCache and RedisSemanticCache for LLM response caching, RedisChatMessageHistory for persistent conversation memory, and RedisConfig for connection management. Requires Redis Stack (redis/redis-stack-server).

enuno Skill

ElizaOS - TypeScript framework for building autonomous AI agents with multi-platform support (Discord, Telegram, Twitter, Farcaster), blockchain integration (EVM, Solana), plugin architecture, multi-agent orchestration, and 90+ community plugins

enuno Bundle

LangChain PostgreSQL integration — PGVectorStore (v2, recommended) and PGVector (v1 legacy) for pgvector RAG, PostgresChatMessageHistory for persistent chat, HNSW/IVFFlat index management, hybrid search, async-first engine via PGEngine, and custom metadata columns.

enuno Skill

LangGraph Graph API (Python) — build explicit DAG agent workflows with StateGraph, typed state, nodes, edges, Command routing, Send fan-out, checkpointers, interrupts, and streaming. Use when you need explicit control flow and graph topology.

harshahosur81 Skill

Design LLM applications using the LangChain framework with agents, memory, and tool integration patterns. Use when building LangChain applications, implementing AI agents, or creating complex LLM workflows.

lifangda Bundle

Work with state-of-the-art machine learning models for NLP, computer vision, audio, and multimodal tasks using HuggingFace Transformers. This skill should be used when fine-tuning pre-trained models, performing inference with pipelines, generating text, training sequence models, or working with BERT, GPT, T5, ViT, and other transformer architectures. Covers model loading, tokenization, training with Trainer API, text generation strategies, and task-specific patterns for classification, NER, QA, summarization, translation, and image tasks. (plugin:scientific-packages@claude-scientific-skills)

delorenj Bundle

Comprehensive n8n workflow automation skill covering workflow architecture patterns (webhook, HTTP API, database, AI agent, scheduled tasks, batch processing), node configuration (operation-aware setup, displayOptions, property dependencies, patchNodeField), expressions ({{}} syntax, $json/$node/$input/$helpers/DateTime), Code nodes (JavaScript and Python with sandbox limits, $helpers.httpRequest, SplitInBatches, pairedItem), n8n-mcp MCP tool usage (search_nodes, get_node_essentials, validate_node_operation, validate_workflow, n8n_create_workflow, n8n_update_partial_workflow), and validation (validate_node, validate_workflow, profiles strict/runtime/ai-friendly/minimal, error catalog, false positives). Use for any n8n development task: building workflows, configuring nodes, writing expressions or Code nodes, validating configurations, debugging failures, deploying to n8n instances, or managing n8n via MCP. Biases towards retrieval via n8n-mcp tools over pre-trained knowledge because n8n's node catalog and par

enuno Bundle

LangChain Perplexity AI integration — ChatPerplexity (chat model with built-in web search and date/domain filtering), PerplexitySearchRetriever for RAG, PerplexitySearchResults tool, PerplexityEmbeddings, and reasoning output parsers (ReasoningJsonOutputParser, strip_think_tags).

enuno Bundle

AI-driven deployment management using Dokploy MCP server for projects, applications, and databases

enuno Bundle

LangChain MCP Adapters — connect LangChain agents to MCP (Model Context Protocol) servers. Load MCP tools, prompts, and resources as LangChain-compatible objects. Supports stdio, SSE, StreamableHTTP, and WebSocket transports. Includes interceptors, callbacks, and multi-server management.

enuno Skill

LangGraph Functional API (Python) — build stateful agent workflows with @entrypoint and @task decorators. Imperative Python style with LangGraph persistence, streaming, HITL, and durable execution. Ideal for wrapping existing agents (CrewAI, AutoGen, Strands) or complex parallel task logic.

enuno Bundle

Database operations for Supabase: query/write/migration/logs/type generation. Triggers: query/statistics/export/insert/update/delete/fix/backfill/migrate/logs/alerts/type generation. Does not trigger for: pure architecture discussion or code planning. Write operations require confirmation; UPDATE/DELETE without WHERE is refused. MCP is optional — works with CLI/Console too.

enuno Bundle

Execute database operations via Supabase MCP (query/write/migration/logs/type generation). Triggers: query/statistics/export/insert/update/delete/fix/backfill/migrate/logs/alerts/type generation. Does not trigger for: pure architecture discussion or code planning. Write operations require confirmation; UPDATE/DELETE without WHERE is refused.

harshahosur81 Skill

Create detailed 3-5 year financial model with revenue, costs, cash flow, and scenarios

delorenj Bundle

Agno AI agent framework. Use for building multi-agent systems, AgentOS runtime, MCP server integration, and agentic AI development.

jamie-bitflight Skill

Research community usage patterns, real-world gotchas, and client compatibility for a specific known library, tool, or protocol feature. Use when a technical-researcher orchestrator needs community-sourced evidence about a named library or feature — bug reports, workarounds, compatibility gaps, and patterns from issue trackers and discussions. Distinct from the broad ecosystem-researcher agent — this skill targets a KNOWN entity and mines what real users have actually experienced, not what exists in a domain.

jamie-bitflight Skill

Use when the PLAN artifact from SAM Stage 2 needs contextualization against actual codebase state — grounds the design plan in reality by performing scope analysis (NEW/MODIFY/COMPLETE classification), conflict detection between plan assumptions and codebase patterns, and resource mapping to concrete file paths and integration points. Produces an updated ARTIFACT:PLAN registered via MCP with a Contextualization section appended.

harshahosur81 Skill

Expert in vector databases, embedding strategies, and semantic search implementation. Masters Pinecone, Weaviate, Qdrant, Milvus, and pgvector for RAG applications, recommendation systems, and similar

delorenj Bundle

Generate speech using the self-hosted voxxy (vox) TTS service at https://vox.delo.sh. Use when the user asks to speak, say, narrate, synthesize speech, clone a voice, create a voice, add or register a voice, pipe TTS, or control voice qualities by description (e.g. "a young woman with a cheerful voice"). Handles HTTP API usage, voice profile management, description-based voice design, cloning, MCP registration, and integration patterns for new platforms.

delorenj Bundle

Create, wire, and maintain 33god/DeLoNET projects. Covers PJangler/CommonProject bootstrap, repo-local `.project.json`, Hermes PM provisioning requests (sentinel duties fold into the PM heartbeat), mise/.env.op, BMAD, Hindsight/Bloodbank hook wiring, and project-scoped hook + skill fan-out adoption. Use when running `pj init`, `pj hermes-agent --yes`, or `mise run init-project`; adding a PM; wiring mise/op inject; installing BMAD; configuring hooks; or adopting `.agents/local.json`, `defer_to_global`, and `hooks.master.json`. Do NOT use for developing pjangler (project-jangler), generic fan-out mechanics (agent-config-fanout), fleet updates/backfills (agent-fleet-operations), live Plane issues, Bloodbank schemas, or host conventions.

delorenj Bundle

Persistent agent memory via self-hosted Hindsight. Retain knowledge, recall context, reflect on patterns. Includes multi-bank routing architecture for agent orgs.

delorenj Skill

How to use worktrunk (`wt`), the installed CLI for git worktree management built for parallel AI agents. Use when creating, switching, listing, rebasing, merging, or removing git worktrees; when running parallel agents that must not share a working directory; when a task needs isolation from a dirty or shared checkout; or when `wt` commands, hooks, or config need debugging. Covers the command surface, agent-specific invocation patterns, and the fleet-standard config. Policy (WHEN/WHERE/MAINTAIN) lives in the 33GOD `worktrees` skill — this skill is the HOW.

jamie-bitflight Bundle

Runs the description-drift experiment — spawns all Claude Code agents simultaneously to collect self-reported capabilities, then compares them against static frontmatter descriptions to reveal how reliable orchestrator routing based on descriptions actually is. Use when measuring description drift across the agent fleet, re-running the capability collection experiment, analyzing a specific agent's self-reported capabilities, or auditing whether frontmatter descriptions accurately reflect agent behavior.

jamie-bitflight Bundle

Reference spec and schema for Claude Code subagents — covers built-in agents (Explore, Plan, general-purpose), all frontmatter fields (name, description, tools, disallowedTools, model, permissionMode, maxTurns, skills, mcpServers, hooks, memory, background, effort, isolation, color, initialPrompt), scope and file locations, invocation patterns (@-mention, --agent, --agents CLI), tool restrictions, and example subagent definitions. Use when creating, configuring, or debugging a subagent definition file, looking up a frontmatter field, choosing between subagents and agent teams, or understanding what loads at subagent startup.

jamie-bitflight Bundle

Store instructional prose once and reference it from multiple skills or agents instead of duplicating it. Use when the same steps, rules, or reference material appear in two or more SKILL.md or agent files in one plugin, when deciding whether a shared doc belongs in the plugin-root docs directory or a single skill's references directory, or when tempted to use a symlink or a ../ path to share a file between components.

jamie-bitflight Skill

Use when searching a codebase by behavior, intent, or natural language description rather than exact identifiers. Activates the CocoIndex Code MCP server for semantic code search — finding implementations without knowing exact names, exploring unfamiliar codebases, or locating code by concept.

harshahosur81 Skill

Master advanced prompt engineering techniques to maximize LLM performance, reliability, and controllability in production. Use when optimizing prompts, improving LLM outputs, or designing production prompt templates.

harshahosur81 Skill

Use when working with performance testing review multi agent review