langchain-deep-agents
Build a LangGraph 1.0 Deep Agent \u2014 planner + subagents + virtual\ \ filesystem +\nreflection loop \u2014 without the state-growth and prompt-inheritance\ \ traps. Use\nwhen building a long-horizon agent that must plan, delegate subtasks,\ \ work\nagainst a scratchpad filesystem, and reflect on progress.\nTrigger with\ \ \"langchain deep agent\", \"planner subagent\", \"virtual filesystem\nagent\"\ , \"reflection loop\", \"langgraph deep agent\".\n"
npx skills add jeremylongshore/claude-code-plugins-plus-skills --skill langchain-deep-agents --agent claude-code
Same command for any agent — swap --agent for codex, cursor, copilot.
Weekly change comes from our own snapshots, not the repository page — it measures attention, not adoption.
# LangChain Deep Agents (Python) ## Overview Two pains bite every team reproducing LangChain's late-2025 Deep Agents blueprint. **Virtual-FS state grows unboundedly (P51).** The planner and every subagent write plans, scratch notes, intermediate drafts, and tool outputs into `state["files"]`. Nothing ever evicts them. After 50 tool calls, the checkpointed state is **8 MB**; every `MemorySaver.put(
What does the langchain-deep-agents skill do?
Build a LangGraph 1.0 Deep Agent \u2014 planner + subagents + virtual\ \ filesystem +\nreflection loop \u2014 without the state-growth and prompt-inheritance\ \ traps. Use\nwhen building a long-horizon agent that must plan, delegate subtasks,\ \ work\nagainst a scratchpad filesystem, and reflect on progress.\nTrigger with\ \ \"langchain deep agent\", \"planner subagent\", \"virtual filesystem\nagent\"\ , \"reflection loop\", \"langgraph deep agent\".\n"
How do I install it?
Run `npx skills add jeremylongshore/claude-code-plugins-plus-skills --skill langchain-deep-agents --agent claude-code` — it drops the skill into your project so the agent can pick it up. Swap the --agent value for codex, cursor or copilot if you use one of those.
Where does this skill come from?
From jeremylongshore/claude-code-plugins-plus-skills, a repository with 2,596 stars. We read it straight from the repository tree rather than a submitted listing, so what you see here is what is actually published.
Is a popular skill a good skill?
Not necessarily. Stars measure attention, not adoption — a repository can trend for a week and be abandoned. That is why we show the weekly change from our own snapshots next to the total, instead of a single flattering number.