Agent Workflow Claude Skills
4 121 agent workflow skills from 665 authors. They configure the agents themselves: memory, prompts, context and other skills. Half of them fit into 1 845 tokens or less — that is what one costs your context window when the agent loads it. 778 ship runnable scripts rather than instructions alone. 5 of them cannot work without an MCP server, most often task. We also found 541 copies of these same skills sitting in other people's repositories — counted once here, not 541 times.
4 121 unique 665 authors 2 767 updated this month 506 from vendors
Covers the Neo4j Go Driver v6 — driver lifecycle, ExecuteQuery, managed and explicit transactions, session config, error handling, data type mapping, and connection tuning. Use when writing Go code that connects to Neo4j, setting up NewDriver or ExecuteQuery, debugging sessions/transactions/result handling, or working with neo4j-go-driver v5→v6 migration. Triggers on NewDriver, ExecuteQuery, SessionConfig, ManagedTransaction, neo4j-go-driver. Does NOT handle Cypher query authoring — use neo4j-cypher-skill. Does NOT cover driver version migration steps — use neo4j-migration-skill.
Neo4j Java Driver v6 — driver lifecycle, Maven/Gradle setup, executableQuery, executeRead/Write managed transactions, explicit transactions, async/reactive patterns, error handling, data type mapping, connection pool tuning, causal consistency/bookmarks. Use when writing Java or Kotlin code that connects to Neo4j via GraphDatabase.driver, executableQuery, SessionConfig, executeRead, executeWrite, or TransactionCallback. Does NOT handle Cypher authoring — use neo4j-cypher-skill. Does NOT cover driver version upgrades — use neo4j-migration-skill. Does NOT cover Spring Data Neo4j (@Node, Neo4jRepository) — use neo4j-spring-data-skill.
Neo4j JavaScript/TypeScript Driver v6 — driver lifecycle, executeQuery, managed transactions (executeRead/executeWrite), session.run, Integer handling, JSON serialization, record access, async/await patterns, TypeScript types, error handling, and connection setup for Node.js and browser. Use when writing JS/TS code that connects Does NOT handle Cypher query authoring — use neo4j-cypher-skill. Does NOT cover driver version migration — use neo4j-migration-skill.
Orchestrates zero-to-running-app in 8 stages — prerequisites → context → provision → model → load → explore → query → build. Each stage reads its own reference file. Supports HITL and fully autonomous operation. Use when starting a new Neo4j project from scratch, provisioning Aura, generating synthetic data, building a notebook or app, or running the full onboarding pipeline. Time budget ≤15 min autonomous, ≤90 min HITL. Does NOT cover Cypher query authoring — use neo4j-cypher-skill. Does NOT cover driver upgrades or Cypher migration — use neo4j-migration-skill. Does NOT cover CLI/admin tasks on an existing DB — use neo4j-cli-tools-skill.
Neo4j Graph Data Science (GDS) embedded plugin via Python client or Cypher — covers GraphDataScience, gds.v2 plugin endpoints, gds.version, native projection, Cypher projection, graph catalog operations, stream/stats/mutate/write modes, memory estimation, PageRank, Louvain, WCC, FastRP, KNN, Node Similarity, ML pipelines, and cleanup. Use for Aura Pro, self-managed, local, or offline Neo4j DBMS with the GDS plugin installed. Does NOT cover Aura Graph Analytics GDS Sessions, AuraGraphDataScience, GdsSessions, gds.graph.project.remote, or AuraDB Cypher API projection/session management — use neo4j-aura-graph-analytics-skill. Does NOT handle Cypher authoring — use neo4j-cypher-skill. Does NOT cover driver setup — use neo4j-driver-python-skill or other driver skill.
Build GraphRAG retrieval pipelines on Neo4j using the neo4j-graphrag Python package (v1.16.0+). Covers retriever selection (VectorRetriever, HybridRetriever, VectorCypherRetriever, HybridCypherRetriever, Text2CypherRetriever, ToolsRetriever), external vector DB retrievers (Weaviate, Pinecone, Qdrant), retrieval_query Cypher fragments, query_params, filters, GraphRAG pipeline wiring (GraphRAG + LLM + prompt), all LLM providers (OpenAI, Anthropic, VertexAI, Bedrock, Cohere, Mistral, Ollama), embedder setup, index creation, token usage tracking, Cypher 25 SEARCH clause, and LangChain/LlamaIndex integration. Does NOT handle KG construction — use neo4j-document-import-skill. Does NOT handle plain vector search — use neo4j-vector-index-skill. Does NOT handle GDS analytics — use neo4j-gds-skill. Does NOT handle agent memory — use neo4j-agent-memory-skill.
Design, review, and refactor Neo4j graph data models. Use when choosing node labels vs relationship types vs properties, migrating relational/document schemas to graph, detecting anti-patterns (generic labels, supernodes, missing constraints), designing intermediate nodes for n-ary relationships, enforcing schema with constraints and indexes, or assessing an existing model against graph modeling best practices. Does NOT handle Cypher query authoring — use neo4j-cypher-skill. Does NOT handle Spring Data Neo4j entity mapping — use neo4j-spring-data-skill. Does NOT handle GraphQL type definitions — use neo4j-graphql-skill. Does NOT handle data import — use neo4j-import-skill.
Configure and operate the Neo4j Connector for Kafka (sink + source) and the native Neo4j CDC API. Covers Cypher/Pattern/CUD sink strategies, CDC-based and query-based source, exactly-once semantics, DLQ error handling, Confluent Cloud managed connector, schema registry (Avro/JSON), and native db.cdc.query cursor-loop patterns (Neo4j 5.13+ Enterprise/Aura BC/VDC). Use when streaming Kafka events into Neo4j, streaming Neo4j changes to Kafka, or querying Neo4j change events without Kafka. Does NOT handle Cypher query authoring — use neo4j-cypher-skill. Does NOT handle bulk CSV/file import — use neo4j-import-skill. Does NOT handle GDS algorithms — use neo4j-gds-skill.
Use when installing, configuring, or troubleshooting the official Neo4j MCP server Kiro, or other MCP-compatible editors to a Neo4j database via stdio or HTTP transport. Covers the four MCP tools (get-schema, read-cypher, write-cypher, list-gds-procedures), read-only mode, and multi-database configuration. Does NOT cover writing Cypher queries via those tools — use neo4j-cypher-skill. Does NOT cover agent memory — use neo4j-agent-memory-skill. Does NOT cover Aura instance provisioning — use neo4j-aura-provisioning-skill.
Diagnoses and fixes slow Neo4j Cypher queries by reading execution plans, identifying bad operators (AllNodesScan, CartesianProduct, Eager, NodeByLabelScan), and prescribing fixes (indexes, hints, query rewrites, runtime selection). Use when a query is slow, when EXPLAIN or PROFILE output needs interpretation, when dbHits or pageCacheHitRatio are poor, when cardinality estimation diverges from actuals, or when deciding between slotted/pipelined/parallel runtimes. Covers USING INDEX / USING SCAN / USING JOIN hints, db.stats.retrieve, SHOW QUERIES, SHOW TRANSACTIONS, TERMINATE TRANSACTION. Does NOT write new Cypher from scratch — use neo4j-cypher-skill. Does NOT cover GDS algorithm tuning — use neo4j-gds-skill. Does NOT cover index/constraint creation syntax details — use neo4j-cypher-skill references/indexes.md.
Programmatic security management in Neo4j — RBAC/ABAC, user lifecycle (CREATE/ALTER/DROP USER), role lifecycle (CREATE/GRANT ROLE/DROP ROLE), privilege grants and denies (GRANT/DENY/REVOKE on graph, database, DBMS), property-level access control, sub-graph access control, SHOW PRIVILEGES inspection, and auth provider config reference (LDAP, OIDC/SSO). Use when an agent needs to manage users, roles, or privileges programmatically via Cypher on the system database. Does NOT handle Cypher query writing — use neo4j-cypher-skill. Does NOT handle cluster ops or backups — use neo4j-cli-tools-skill. Property-level security and ABAC require Enterprise Edition.
Use when reading from or writing to Neo4j with Apache Spark or Databricks using the setup, DataFrame reads via labels/Cypher/relationship scan, DataFrame writes with SaveMode, node.keys for MERGE, relationship write mapping, partition and batch tuning, PySpark and Scala examples, Databricks cluster config, Databricks secrets for credentials, Delta Lake to Neo4j pipelines. Does NOT handle Cypher authoring — use neo4j-cypher-skill. Does NOT handle the Python bolt driver — use neo4j-driver-python-skill. Does NOT handle GDS algorithms — use neo4j-gds-skill.
Use when building Spring Boot applications with Neo4j using Spring Data Neo4j (SDN 7.x/8.x): @Node entity mapping, @Relationship, @RelationshipProperties, Neo4jRepository, ReactiveNeo4jRepository, @Query annotations, application.yml configuration, projections, Neo4jClient, Neo4jTemplate, transactions, auditing, or Spring AI Neo4jVectorStore vector search. Does NOT handle raw Java driver code without Spring — use neo4j-driver-java-skill. Does NOT handle Cypher query authoring — use neo4j-cypher-skill. Does NOT handle driver version upgrades — use neo4j-migration-skill.
Initialize, validate, and troubleshoot Deep Agents projects in Python or JavaScript using the `deepagents` package. Use when users need to create agents with built-in planning/filesystem/subagents, configure middleware/backends/checkpointing/HITL, migrate from `create_react_agent` or `create_agent`, scaffold projects with repo scripts, validate agent config files, and confirm compatibility with current LangChain/LangGraph/LangSmith docs.
Implement multi-agent coordination patterns (supervisor-subagent, router, orchestrator-worker, handoffs) for LangGraph applications. Use when users want to (1) implement multi-agent systems, (2) coordinate multiple specialized agents, (3) choose between coordination patterns, (4) set up supervisor-subagent workflows, (5) implement router-based agent selection, (6) create parallel orchestrator-worker patterns, (7) implement agent handoffs, (8) design state schemas for multi-agent systems, or (9) debug multi-agent coordination issues.
Your habits, imprinted on AI. Learns how you work from conversation, builds a portable profile, and applies judgment that adapts to you: when to act, when to check with you, when to follow the project's rules over your own defaults. Use this skill whenever the user starts a new session, opens a project, writes or reviews code, debugs, plans, or writes commits. If .dna.md does not exist yet, start the onboarding conversation before doing anything else. Active in almost every working session.
Skill hub for the solana-ai-kit Claude Code plugin. Routes the bundled go-to-market skills and the opt-in add-on catalog, and points to upstream marketplaces (and the install.sh full install) for protocol, security, and ecosystem depth. Progressive disclosure — read only what you need.
> Full-site blog health assessment scanning all blog files for quality scores, orphan pages, topic cannibalization, stale content, and AI citation readiness. Spawns parallel subagents for comprehensive analysis. Produces per-post scores and a prioritized action queue. Use when user says "audit blog", "blog audit", "site audit", "blog health", "audit all posts", "check all blogs".
Create developer handoff specifications with measurements, behaviors, assets, and edge cases.
Design a new PM skill through guided conversation. Use when you have raw content or an idea and want to shape it into a compliant skill.
Build, modify, optimize, debug, and deploy agents with Agentforce Agent Script. TRIGGER when: user creates, modifies, optimizes, or asks about .agent files or aiAuthoringBundle metadata; changes agent behavior, responses, or conversation logic; designs agent actions, tools, subagents, or flow control; writes or reviews an Agent Spec; wants to optimize, improve, or refactor an agent; previews, debugs, deploys, publishes, or tests agents; uses Agent Script CLI commands (sf agent generate/preview/publish/test); registers/creates/lists/updates/deletes MCP servers, whitelists/approves MCP tools, fetches MCP assets, or configures MCP authentication (sf agent mcp). DO NOT TRIGGER when: Apex development, Flow building, Prompt Template authoring, Experience Cloud configuration, or general Salesforce CLI tasks unrelated to Agent Script.
Mine the user's Claude Code + Cowork session history into a structured task profile, what they do with AI, how often, how successfully where friction lives, then propose atomic skills that would reduce iteration. Use when the user asks to "analyse my Claude use", "build a task profile", "what tasks do I do with Claude", "where am I spending tokens", "what skills would help me", or mentions reviewing past sessions for patterns. Produces profile.csv (shareable), explorer.html (personal coaching view with AI-first principle comparison + token-spend chart), and skill-proposals.md.
Personal diagnosis of where your Claude Code + Cowork spend goes. Reads local transcripts, prints your conversation length distribution, marathon share, cache rebuild costs, and per-project diagnosis (good projects and problem projects) right in the terminal. Then offers a deeper dive that fans out parallel Haiku subagents over your most expensive (and most efficient) sessions and writes a tight Markdown report. Use when the user asks "why is my Claude spend so high", "where am I burning tokens", "diagnose my Claude habits", "audit my Claude usage", or asks for a personal token-cost diagnosis.
Turn a task, plan, or feature request into a ready-to-paste Claude Code /goal command — a single completion condition with a measurable end state, a demonstrable proof, and the constraints that must not drift. Use when the user says "give me a goal", "goal prompt", "make this a /goal", "turn this into a goal", or wants an autonomous long-running objective for Claude Code.
Write a session handoff at the end of a session so the next session can start from where this one stopped without rereading the whole conversation. Use when user says "handoff", "wrap up", "write a handoff", "end of session", "park this session", "save where we are", or to RESUME with "/handoff read", "pick up the handoff", "read the handoff". Writes a tight resume note (HANDOFF.md) into the working directory, not a full transcript. Scope is the current project's resume note only: not searching or summarizing past sessions, and not any project-specific "resume" command the environment may have.
Find context from past Claude Code (CLI) and Claude Cowork (desktop) sessions on this Mac. Use when the user wants to recall something they did before but can't find it , phrasings like "where did I work on X", "find that session where I…", "when did I last do Y", "pull up the conversation about Z", "that time I built/tried/discussed …". Searches by kind (code/cowork), time range, title, working directory, or free-text content across all transcripts.
Build an MCP server end to end, tailored to how it will be used. Use when asked to build an MCP, create an MCP server, wrap an API as a tool, make a tool for Claude, expose a service to an agent, build a Claude connector, or turn a service into MCP tools. Asks up front who the server is for (just me, my org, or public) and what it wraps, then walks through analyze, build, deploy, scale, and distribute with steps tailored to that answer. Builds on the example-skills:mcp-builder skill for implementation depth.
Bundle skills, hooks, agents, or an MCP server into one installable Claude Code plugin and ship it. Use when asked to bundle tools into one plugin, package tools for a colleague, publish a plugin to a marketplace, share my tools with my team, or ship a plugin. Asks who it's for and where it's hosted, then walks analyze, assemble, ship, and maintain, tailored to that answer. Sibling to build-mcp.
Iris is Redis's umbrella for AI-focused products. Use this skill when integrating with the Iris Redis Agent Memory (RAM) data plane on Redis Cloud — recording session events for an AI agent, creating or searching long-term memories, configuring a memory store, or tuning background memory promotion. Code examples use the official `redis-agent-memory` (Python) and `@redis-iris/agent-memory` (TypeScript) SDKs.
How an agent operates inside a PyWry chat widget — reading user messages, attachments, @-context, tool-call result cards, edit/resend, settings changes.
>- stage), dates, location, special sessions / calls for papers, official links, and a 5-year acceptance-rate trend. Use when the user asks about future AI conference deadlines, wants to plan submissions, compare venues, or track a set of conferences by area/reputation/difficulty. Works in any agent that has a web-search / web-fetch capability (Claude Code, Codex, etc.).
Guidelines for creating AI agent skills. Use when writing new skills, documenting coding patterns, or reviewing skill files. Triggers when creating or modifying files in the skills/ directory.
Compile a skill from a brief. Supports --batch for multiple briefs. Use when the user requests to "create a skill" or "compile a skill.
Design a skill scope through guided discovery. Use when the user requests to "create a skill brief" or "brief a skill".
Consolidated project stack skill with integration patterns — code-mode (analyzes manifests) or compose-mode (synthesizes from existing skills + architecture doc). Use when the user requests to "create a stack skill", "forge a stack", or "stack this project".
Drift detection between skill and current source code. Use when the user requests to "audit a skill" or "audit skill" for drift.
Package for distribution and inject context into CLAUDE.md/AGENTS.md/.cursorrules. Use when the user requests to "export" or "package a skill.
Drop a specific skill version or an entire skill — soft (deprecate) or hard (purge) with platform context rebuild. Use when the user requests to "drop" or "remove a skill.
Skill compilation specialist — the forge master. Use when the user asks to "talk to Ferris" or requests the "Skill Forge agent.
Fast skill from a package name or GitHub URL — no brief needed. Use when the user requests a "quick skill" or "skill from URL" or "skill from package.
Rename a skill across all its versions — transactional copy-verify-delete with platform context rebuild. Use when the user requests to "rename a skill.
Smart regeneration preserving [MANUAL] sections after source changes. Use when the user requests to "update a skill" or "regenerate a skill.
Cognitive completeness verification — quality gate before export. Use when the user requests to "test a skill" or "verify skill completeness.
Authors or extends a skill in mc-agent-toolkit. Gates for forbidden buckets and name collisions, applies CONTRIBUTING's extend-or-split rules, then edits a peer skill or hands off to Anthropic's skill-creator and walks the registration checklist.
| Reinforces an AI agent by turning Monte Carlo's reinforcement loop diagnosis into code fixes. Reads the daily reinforcement loop report for an agent's workflows, ranks the diagnosed issues, proposes what to fix, and — with the user's approval at each step — opens a pull request. Activates on "fix my agent", "improve my agent's health", "reinforce my agent", "what should I fix in my agent". Not for investigating a specific agent alert or trace (monte-carlo-troubleshoot-agent-traces), creating agent monitors (monte-carlo-monitoring-advisor), or instrumenting a new agent (monte-carlo-instrument-agent).
Troubleshoots Monte Carlo AI agent alerts and traces — eval score drops, latency/token spikes, trajectory and validation breaches. Not for data incidents (monte-carlo-analyze-root-cause) or monitor creation (monte-carlo-monitoring-advisor).
Interactive copilot that offloads grunt work to a cheaper engine while Claude orchestrates. Greets each session with your live token limits and a driving mode (auto-pilot / you-drive / hybrid), auto-conserves when your Claude window runs hot, and picks models by live benchmarks. Triggers: outsource, offload, delegate, conserve tokens, use GLM/Devin/Codex, or get a second opinion.
>- Agent-native DeepRefine refinement loop — same control flow as DeepRefine.refine(), graphify search instead of FAISS, session LLM, dry-run review before approved graph writes.