Comprehensive development workflow for building AI agents with the Atomic Agents framework. Includes specialized agents for schema design, architecture planning, code review, and tool development. Features guided workflows, progressive-disclosure skills, and best practice validation.
Plugin atomic-agents from marketplace claude-plugins-official in anthropics/claude-plugins-official. Commands read from the repo's manifest — today.
create-atomic-agentBuild and wire an `AtomicAgent[InSchema, OutSchema]` — schemas, `AgentConfig`, `SystemPromptGenerator`, provider client, history, hooks, optional context providers. Use when the user asks to "create an agent", "add another agent", "build an `AtomicAgent`", "wire up an agent", "make a planner/router/
create-atomic-context-providerBuild a `BaseDynamicContextProvider` that injects a named, titled block into an agent's system prompt at every `run()` — current time, user identity, retrieved RAG docs, session state, cached DB schema. Use when the user asks to "add a context provider", "inject X into the prompt", "give the agent d
create-atomic-schemaDesign and write a `BaseIOSchema` input/output pair for an Atomic Agents agent or tool — docstrings, field descriptions, validators, error variants. Use when the user asks to "create a schema", "design the input/output schema", "define an `IOSchema`", "write a `BaseIOSchema`", "model the agent's out
create-atomic-toolBuild a `BaseTool[InSchema, OutSchema]` subclass — input/output schemas, `BaseToolConfig`, `run()` (and optional `run_async()`), env-driven secrets, typed failure outputs. Use when the user asks to "add a tool", "create a tool", "wrap an API as a tool", "build a `BaseTool`", "make a calculator/searc
frameworkGuide for the Atomic Agents Python framework — schemas, agents, tools, context providers, prompts, orchestration, and provider configuration. Use when code imports from `atomic_agents`, defines an `AtomicAgent`, `BaseTool`, or `BaseIOSchema`, or the user asks about multi-agent orchestration or LLM-p
new-appScaffold a new Atomic Agents project from scratch — create the directory, `pyproject.toml`, env file, first agent, and a runnable entry point. Use when the user asks to start a new atomic-agents project from scratch, says "scaffold" / "new project" / "start from zero", or runs `/atomic-agents:new-ap
troubleshootDiagnose and fix a failing or misbehaving Atomic Agents app — import errors, schema validation failures, empty or malformed LLM output, provider role/mode errors, history and context problems, MCP transport errors. Use when the user reports an error, traceback, or wrong behavior in atomic-agents cod
atomic-explorerMaps existing Atomic Agents Python codebases — catalogs agents, tools, schemas, context providers, and orchestration patterns; traces data flow between them; returns a compact architecture summary with file:line references. Use PROACTIVELY when the user asks to "explore", "map", "understand", "analy
atomic-reviewerReviews Atomic Agents Python code for framework-specific correctness — BaseIOSchema invariants, AtomicAgent/AgentConfig wiring, BaseTool generics, context-provider I/O hygiene, orchestration hazards, Instructor integration — using confidence-based filtering. Use PROACTIVELY after any change to atomi
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44 skills · 1 MCP server
Connect Claude Code directly to your CockroachDB clusters for hands-on database work — explore schemas, write optimized SQL, debug queries, and manage distributed database clusters. This plugin provides 14 tools across two active MCP backends (self-hosted MCP Toolbox and managed CockroachDB Cloud MCP Server), three specialized agents (DBA, Developer, Operator), 32 skills across 6 operational domains, and built-in safety hooks.
34 skills · 3 agents · 3 MCP servers · hooks
Databricks skills for the CLI, Apps, Lakebase, Model Serving, Lakeflow Jobs, Spark Declarative Pipelines, Declarative Automation Bundles (DABs), and classic-to-serverless migration.
37 skills · 2 commands · hooks
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38 skills · hooks
Use Amplitude as an expert analyst — instrument Amplitude, discover product opportunities, analyze charts, create dashboards, manage experiments, and understand users and accounts.
36 skills · 1 MCP server
This plugin provides a specialized suite of skills for data engineers and database practitioners working on Google Cloud. It acts as an expert assistant, allowing you to use natural language prompts in your preferred coding agent to architect complex data pipelines, transform data with dbt, write Spark and BigQuery SQL notebooks, and orchestrate end-to-end workflows across GCP's data ecosystem.
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15 skills · hooks
Up-to-date documentation lookup. Pull version-specific documentation and code examples directly from source repositories into your coding agent's context.
1 MCP server
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5 commands
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12 skills
Use Alibaba Open Code Review from local Codex.
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Claude Code skill for creating and presenting Slidev slidedecks
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