langchain-stack
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- Author updated Live
- Author repo skills-registry
- Domain
- AI
- Compatible agents
-
- Claude Code
- Cursor
- Cline
- Codex
- Windsurf
- Gemini CLI
- +20
- Trust score
- 88 / 100 · community maintained
- Author / version / license
- @tomevault-io · no license declared
- Token usage
- Lean
- Setup complexity
- Plug-and-play
- External API key
- Not required
- Operating systems
- Unspecified (assume cross-platform)
- Runtime requirements
- No special requirements
- Permissions
-
- Read-only
- Write / modify
- Network behavior
- Local-only
- Install commands
- 26 variants
Profile is derived at build time from SKILL.md and install vectors. Subject to drift from author intent.
Heads up: 未限定 allowed-tools，默认拥有全部工具权限。
---
name: langchain-stack
description: Router for LangChain, LangGraph, and Deep Agents skills. Load this ONCE — it tells you which sub…
category: ai
runtime: no special runtime
---
# langchain-stack output preview
## PART A: Task fit
- Use case: Router for LangChain, LangGraph, and Deep Agents skills. Load this ONCE — it tells you which sub-skill file to read for the specific task. Use when this capability is needed..
- Inputs: target material, constraints, expected output, and acceptance criteria.
- Evidence boundary: follow “Step 1: Pick framework / Step 2: Load the relevant sub-skill(s) / LangChain (simple agents, tool calling)” and do not present inference as author intent.
## PART B: Execution result
- **01** The card summarizes the use case; runtime output centers on “Router for LangChain, LangGraph, and Deep Agents skills. Load this ONCE — it tells you which sub-skill file to read for the specific task. Use when this capability is needed.”.
- **02** When the source has headings, the agent prioritizes “Step 1: Pick framework / Step 2: Load the relevant sub-skill(s) / LangChain (simple agents, tool calling)” so the result follows the author’s structure.
- **03** Typical output includes task judgment, concrete steps, required commands or file edits, validation, and follow-up options.
- **04** Risk context follows the fingerprint: read files, write/modify files; mostly runs locally; usually needs no extra API key.
## Running Rules
- read files, write/modify files; mostly runs locally; usually needs no extra API key.
- Validate with a small sample before expanding scope.
- Return the result, validation criteria, and next iteration options. Choose the trigger
The source does not require a stable slash command. After installation, invoke the skill by name and describe the task.
Provide inputs and boundaries
Name target files or source material, expected output, forbidden changes, and whether network or shell access is allowed. Permission fingerprint: read files, write/modify files.
Validate with a small run
Start with a small task and check whether the result follows “Step 1: Pick framework / Step 2: Load the relevant sub-skill(s) / LangChain (simple agents, tool calling)”. Inspect diffs, logs, previews, or tests before expanding scope.
Review before delivery
Confirm the final output includes a concrete result, evidence, and next action. If it stays generic, tighten inputs, boundaries, and acceptance criteria.
---
name: langchain-stack
description: Router for LangChain, LangGraph, and Deep Agents skills. Load this ONCE — it tells you which sub…
category: ai
source: tomevault-io/skills-registry
---
# langchain-stack
## When to use
- Router for LangChain, LangGraph, and Deep Agents skills. Load this ONCE — it tells you which sub-skill file to read fo…
- Use it when the task has clear inputs, repeatable steps, and validation criteria.
## What to provide
- Target material, scope, expected result, and forbidden changes.
- Whether network, commands, file writes, or external services are allowed.
## Execution rules
- Organize steps around “Step 1: Pick framework / Step 2: Load the relevant sub-skill(s) / LangChain (simple agents, tool calling)” and keep inference separate from source facts.
- read files, write/modify files; mostly runs locally; usually needs no extra API key.
- Validate with a small sample before expanding the task.
## Output requirements
- Return the deliverable, key evidence, validation method, and next action.
- Mark missing information as unknown; do not invent commands, platforms, or dependencies. Evidence boundary and execution chain
The author source anchors workflow facts; repository files anchor sources and commands; Fluxly only adds fit, limitations, and quality judgment.
skill "langchain-stack" {
input -> user goal + target files + boundaries + acceptance criteria
context -> Step 1: Pick framework / Step 2: Load the relevant sub-skill(s) / LangChain (simple agents, tool calling)
rules -> SKILL.md triggers / order / output contract
runtime -> no special runtime | read files, write/modify files | mostly runs locally
guardrails -> usually needs no extra API key + small-sample validation + diff/log review
output -> copyable result + checklist + next iteration
}LangChain / LangGraph / Deep Agents — Skill Router
Do NOT load all sub-skills. Read ONLY the file(s) relevant to the current task.
Step 1: Pick framework
If unsure which framework to use, read framework-selection first:
→ ~/.skills-library/langchain/framework-selection/SKILL.md (163 lines)
Step 2: Load the relevant sub-skill(s)
LangChain (simple agents, tool calling)
| When | Read |
|---|---|
| Creating agents, defining tools, basic agent loop | ~/.skills-library/langchain/langchain-fundamentals/SKILL.md (394 lines) |
| Human-in-the-loop approval, custom middleware, structured output | ~/.skills-library/langchain/langchain-middleware/SKILL.md (388 lines) |
| RAG: document loaders, splitters, embeddings, vector stores | ~/.skills-library/langchain/langchain-rag/SKILL.md (517 lines) |
| Package versions, installation, dependency management | ~/.skills-library/langchain/langchain-dependencies/SKILL.md (419 lines) |
LangGraph (stateful graphs, complex workflows)
| When | Read |
|---|---|
| StateGraph, nodes, edges, Command, Send, streaming | ~/.skills-library/langchain/langgraph-fundamentals/SKILL.md (811 lines) |
| interrupt(), approval workflows, error handling tiers | ~/.skills-library/langchain/langgraph-human-in-the-loop/SKILL.md (532 lines) |
| Checkpointers, thread_id, time travel, Store, subgraph persistence | ~/.skills-library/langchain/langgraph-persistence/SKILL.md (560 lines) |
Deep Agents (hierarchical agent systems)
| When | Read |
|---|---|
| create_deep_agent(), harness architecture, SKILL.md format | ~/.skills-library/langchain/deep-agents-core/SKILL.md (423 lines) |
| SubAgentMiddleware, TodoList planning, HITL interrupts | ~/.skills-library/langchain/deep-agents-orchestration/SKILL.md (471 lines) |
| StateBackend, StoreBackend, FilesystemMiddleware, CompositeBackend | ~/.skills-library/langchain/deep-agents-memory/SKILL.md (301 lines) |
~/.skills-library/langchain is a symlink to the langchain-skills submodule — don't hardcode the submodule path, use this alias so the skill stays portable if the submodule moves.
Rules
- Read the sub-skill file with the Read tool — it contains full API reference and examples
- For multi-concern tasks, read multiple files (e.g. langgraph-fundamentals + langgraph-persistence)
- Never guess APIs from memory — always read the file first
Source: andres-ortizl/dotfiles — distributed by TomeVault.
Decide Fit First
Design Intent
How To Use It
Boundaries And Review