Add Example Agent
GetBindu/Bindu
Add a new self-contained example agent under examples/. An agent skill from GetBindu/Bindu.
LangChain / LangGraph engineering pitfalls and verified fixes.
Install Langchain Dev Guide
$ npx skills add ob-labs/agentseek --skill langchain-dev-guide -a claude-codeProject install by default; add -g for ~/.claude/skills/.
$ gh skill install ob-labs/agentseek langchain-dev-guide --agent claude-codeProject scope by default; add --scope user for a personal install. Needs GitHub CLI 2.90.0 or later (public preview).
$ git clone --depth 1 https://github.com/ob-labs/agentseek.git skills-src && mkdir -p .claude/skills && cp -r skills-src/skills/langchain-dev-guide .claude/skills/langchain-dev-guide && rm -rf skills-srcUse ~/.claude/skills/ instead of .claude/skills for a personal install. The folder must contain SKILL.md.
Claude Code skills documentation · loads skills from .claude/skills/
Install the "langchain-dev-guide" agent skill from https://github.com/ob-labs/agentseek/tree/main/skills/langchain-dev-guide into .claude/skills/langchain-dev-guide/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "langchain-dev-guide", then confirm the skill loads.Claude Code copies the folder itself, the same result as the manual copy. Check what it changed before you commit it.
$skill-installer install https://github.com/ob-labs/agentseek/tree/main/skills/langchain-dev-guideType this inside Codex. $skill-installer <name> installs a curated skill from openai/skills. The installer writes to $CODEX_HOME/skills (default ~/.codex/skills). Restart Codex if the skill does not show up.
$ npx skills add ob-labs/agentseek --skill langchain-dev-guide -a codexProject install goes to .agents/skills/; add -g for ~/.codex/skills/.
$ gh skill install ob-labs/agentseek langchain-dev-guide --agent codexProject scope by default (.agents/skills/); add --scope user for a personal install.
$ git clone --depth 1 https://github.com/ob-labs/agentseek.git skills-src && mkdir -p .agents/skills && cp -r skills-src/skills/langchain-dev-guide .agents/skills/langchain-dev-guide && rm -rf skills-srcUse ~/.agents/skills/ instead of .agents/skills for a personal install.
Codex skills documentation · loads skills from .agents/skills/
Install the "langchain-dev-guide" agent skill from https://github.com/ob-labs/agentseek/tree/main/skills/langchain-dev-guide into .agents/skills/langchain-dev-guide/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "langchain-dev-guide", then confirm the skill loads.Codex copies the folder itself, the same result as the manual copy. Check what it changed before you commit it.
$ npx skills add ob-labs/agentseek --skill langchain-dev-guide -a cursorProject install goes to .agents/skills/; add -g for ~/.cursor/skills/.
$ gh skill install ob-labs/agentseek langchain-dev-guide --agent cursorProject scope by default (.agents/skills/); add --scope user for a personal install.
$ git clone --depth 1 https://github.com/ob-labs/agentseek.git skills-src && mkdir -p .cursor/skills && cp -r skills-src/skills/langchain-dev-guide .cursor/skills/langchain-dev-guide && rm -rf skills-srcUse ~/.cursor/skills/ instead of .cursor/skills for a personal install.
Cursor skills documentation · loads skills from .cursor/skills/, .agents/skills/, .claude/skills/, .codex/skills/
Install the "langchain-dev-guide" agent skill from https://github.com/ob-labs/agentseek/tree/main/skills/langchain-dev-guide into .cursor/skills/langchain-dev-guide/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "langchain-dev-guide", then confirm the skill loads.Cursor copies the folder itself, the same result as the manual copy. Check what it changed before you commit it.
$ gemini skills install https://github.com/ob-labs/agentseek.git --path skills/langchain-dev-guide--scope user (default) or --scope workspace; --path is the subfolder of the repo that holds the skill; --consent skips the security confirmation prompt.
$ npx skills add ob-labs/agentseek --skill langchain-dev-guide -a gemini-cliProject install goes to .agents/skills/; add -g for ~/.gemini/skills/.
$ gh skill install ob-labs/agentseek langchain-dev-guide --agent gemini-cliProject scope by default (.agents/skills/); add --scope user for a personal install.
$ git clone --depth 1 https://github.com/ob-labs/agentseek.git skills-src && mkdir -p .gemini/skills && cp -r skills-src/skills/langchain-dev-guide .gemini/skills/langchain-dev-guide && rm -rf skills-srcUse ~/.gemini/skills/ instead of .gemini/skills for a personal install, then run /skills reload.
Gemini CLI skills documentation · loads skills from .gemini/skills/, .agents/skills/
Install the "langchain-dev-guide" agent skill from https://github.com/ob-labs/agentseek/tree/main/skills/langchain-dev-guide into .gemini/skills/langchain-dev-guide/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "langchain-dev-guide", then confirm the skill loads.Gemini CLI copies the folder itself, the same result as the manual copy. Check what it changed before you commit it.
$ gh skill install ob-labs/agentseek langchain-dev-guideInstalls for Copilot at project scope by default; add --scope user for a personal install. Preview a skill first with gh skill preview. Needs GitHub CLI 2.90.0 or later (public preview).
$ npx skills add ob-labs/agentseek --skill langchain-dev-guide -a github-copilotProject install goes to .agents/skills/; add -g for ~/.copilot/skills/.
$ git clone --depth 1 https://github.com/ob-labs/agentseek.git skills-src && mkdir -p .github/skills && cp -r skills-src/skills/langchain-dev-guide .github/skills/langchain-dev-guide && rm -rf skills-srcUse ~/.copilot/skills/ instead of .github/skills for a personal install. Commit .github/skills so cloud agent and code review can use it.
GitHub Copilot skills documentation · loads skills from .github/skills/, .claude/skills/, .agents/skills/
Install the "langchain-dev-guide" agent skill from https://github.com/ob-labs/agentseek/tree/main/skills/langchain-dev-guide into .github/skills/langchain-dev-guide/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "langchain-dev-guide", then confirm the skill loads.GitHub Copilot copies the folder itself, the same result as the manual copy. Check what it changed before you commit it.
$ npx skills add ob-labs/agentseek --skill langchain-dev-guide -a opencodeOpenCode documents no install command of its own. Project install goes to .agents/skills/; add -g for ~/.config/opencode/skills/.
$ gh skill install ob-labs/agentseek langchain-dev-guide --agent opencodeProject scope by default (.agents/skills/); add --scope user for a personal install.
$ git clone --depth 1 https://github.com/ob-labs/agentseek.git skills-src && mkdir -p .opencode/skills && cp -r skills-src/skills/langchain-dev-guide .opencode/skills/langchain-dev-guide && rm -rf skills-srcUse ~/.config/opencode/skills/ instead of .opencode/skills for a personal install.
OpenCode skills documentation · loads skills from .opencode/skills/, .claude/skills/, .agents/skills/
Install the "langchain-dev-guide" agent skill from https://github.com/ob-labs/agentseek/tree/main/skills/langchain-dev-guide into .opencode/skills/langchain-dev-guide/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "langchain-dev-guide", then confirm the skill loads.OpenCode copies the folder itself, the same result as the manual copy. Check what it changed before you commit it.
Facts
- Skill name
langchain-dev-guide- GitHub stars
- 192
- Token cost
- ~1.8k tokens
- SKILL.md length
- 716 words
- Files
- 14
- Skills in repo
- 4
- Repo updated
- First seen
- Licence
- Apache-2.0
At a glance
LangChain / LangGraph engineering pitfalls and verified fixes.
- Works in 4 steps: First use the "Scenario Index" below to… → When unsure which category applies,… → For ContextSeek / semantic memory: start… → …
- Hitting unexpected behavior
- SKILL.md covers How to Use, Scenario Index and Common Issues Quick Reference
- Runs Python scripts from its folder
What it does
Langchain Dev Guide is an agent skill from ob-labs/agentseek. LangChain / LangGraph engineering pitfalls and verified fixes. Covers DeepAgents, structured output, OpenAI-compatible model integration (including Chinese provider adapters: DeepSeek, Qwen, GLM, etc.), middleware, streaming, multi-agent orchestration, and other common development issues. Use when hitting unexpected behavior, making architecture decisions, or integrating Chinese LLM providers during LangChain development.
Its SKILL.md is about 1.8k tokens, which your agent loads only when the skill is triggered. The skill folder holds 16 other files (for example `reference/cn-models/README.md`, `reference/cn-models/integration-tests.md` and `reference/common-issues.md`).
It sits in AI & LLM Engineering, covering Building AI agents. It works with LangChain, OpenAI, LangGraph and DeepSeek. The repository describes itself as: AgentSeek is an application development lifecycle toolkit for AI ecosystem apps, built by OceanBase OSS Team. The licence is Apache-2.0.
When your agent uses it
- Hitting unexpected behavior
- Making architecture decisions
- Integrating Chinese LLM providers during LangChain development
Example prompts
- “/langchain-dev-guide”
Requirements
- Python 3
Workflow steps
4 steps, taken from the first numbered list in SKILL.md.
- First use the "Scenario Index" below to locate the category file your problem belongs to.
- When unsure which category applies, search keywords directly in the "Common Issues Quick Reference".
- For ContextSeek / semantic memory: start with contextseek-middleware.md to identify your scenario, then go to contextseek-params.md for…
- Once you find the relevant section, read it in depth — every entry follows the structure Symptom → Cause → Solution → Lessons learned.
What it can do on your machine
Read from SKILL.md and the folder at commit 8abad49. It shows what the files ask for, not the result of running them.
Tool permissions
Pre-approves nothing: there is no allowed-tools line, so your agent's usual permission prompts apply.
From allowed-tools in the SKILL.md frontmatter.
Runs code
Ships script files (Python), which the agent can run.
From the folder's file list and the shell code blocks in SKILL.md.
Network
No URLs in SKILL.md.
From URLs in SKILL.md, links to its own repository left out.
Credentials
Names no API keys, tokens, secrets or passwords.
From names ending in _API_KEY, _TOKEN, _SECRET, _KEY or _PASSWORD in SKILL.md.
Context cost
Langchain Dev Guide loads about 1.8k tokens when it runs. Until then it costs about 111 tokens; SKILL.md has 716 words of instructions outside code blocks.
Estimates: characters ÷ 4, the usual rule of thumb; real counts depend on the model's tokenizer. Scripts and assets cost tokens only if the agent reads them.
Safety
Auto-check passed
The automated check found no risky patterns in SKILL.md.
Automated static check — not a guarantee. Review scripts before installing. It scans the text of SKILL.md for risky patterns (piping downloads into a shell, reading credential files, hidden Unicode, destructive commands); files beside SKILL.md are not scanned.
SKILL.md
The full file from ob-labs/agentseek at commit 8abad49, republished under its Apache-2.0 licence (© ob-labs). 716 words, ~1,847 tokens.
Download SKILL.mdSave it as
.claude/skills/langchain-dev-guide/SKILL.md (or your agent's skills folder). This skill also uses 13 other files; get the full folder from GitHub.- name
- langchain-dev-guide
- description
- LangChain / LangGraph engineering pitfalls and verified fixes. Covers DeepAgents, structured output, OpenAI-compatible model integration (including Chinese provider adapters: DeepSeek, Qwen, GLM, etc.), middleware, streaming, multi-agent orchestration, and other common development issues. Use when hitting unexpected behavior, making architecture decisions, or integrating Chinese LLM providers during LangChain development.
LangChain Dev Guide
A systematic summary of typical issues, non-obvious behaviors, and verified solutions encountered in real engineering with the LangChain / LangGraph ecosystem. Every entry comes from a real development scenario and is organized by category.
[!IMPORTANT] This skill is an engineering practice reference, not an introductory tutorial. Each entry assumes the developer is already familiar with basic LangChain concepts (agent, tool, message, graph).
How to Use
- First use the "Scenario Index" below to locate the category file your problem belongs to.
- When unsure which category applies, search keywords directly in the "Common Issues Quick Reference".
- For ContextSeek / semantic memory: start with contextseek-middleware.md to identify your scenario, then go to contextseek-params.md for specific parameter configuration issues.
- Once you find the relevant section, read it in depth — every entry follows the structure Symptom → Cause → Solution → Lessons learned.
Scenario Index
| Category | File | Trigger Scenarios |
|---|---|---|
| Deep Agents | reference/deepagents.md | Model selection, filesystem backend, disabling the general-purpose sub-agent, file permissions, long-term memory, long SKILL.md truncated by read_file 100-line default |
| Structured Output | reference/structured-output.md | Model-level method selection, create_agent strategies, missing fields, unsupported tool_choice, provider-side 400 errors on forced schema tool selection |
| OpenAI-compatible Model Integration | reference/model-integration.md | Pitfalls when using ChatOpenAI against OpenAI-compatible providers, integrating Reasoning models (chain-of-thought / reasoning_content) |
| CN Model Integration | reference/cn-models/README.md | Generating LangChain integration classes for Chinese providers (DeepSeek, Qwen, GLM, Moonshot) |
| Middleware | reference/middleware.md | Middleware execution order, state_schema merging, HITL resume values, modifying state from wrap_model_call |
| Streaming Output | reference/streaming.md | Choosing between stream_events and stream, distinguishing tokens from multiple LLMs, disabling streaming, custom progress events |
| Multi-Agent Orchestration | reference/multi-agent.md | subagents vs handoffs, tool-per-agent vs dispatch, retrieving subagent state, trimming subagent boilerplate, quickly building handoff setups |
| Other Common Issues | reference/common-issues.md | High-frequency standalone issues that don't fit the categories above. Currently includes: tools returning data to both the model and the application layer, MCP tools unable to access runtime context, invalid_tool_calls, and dynamic system prompt placeholders |
| ContextSeek — Use Case Scenarios | reference/contextseek-middleware.md | Agent loses context across sessions, tool call auditing, cross-topic knowledge discovery (dream), SRE provenance / confidence tracing, enterprise knowledge cold-start (DataPlug) |
| ContextSeek — Parameter & Config Issues | reference/contextseek-params.md | scope isolation, auto_store / record_tool_calls write volume, auto_compact throttling and shutdown, retrieval_tags / min_score filtering, tool_arg_overrides, dream trigger conditions, dream item decay, evidence_chain vs chain_confidence, DataPlug vs ctx.add(), plug() scope priority, auto_dream dual-gate triggering |
Show full SKILL.md (345 more words)Show less
Common Issues Quick Reference
| Keyword / Error | Where to Look |
|---|---|
| Which model to choose / Deep Agent performing poorly | deepagents issue 1 |
| Filesystem backend / local files / file permissions | deepagents issues 2 / 4 |
| Disabling the default sub-agent / general-purpose | deepagents issue 3 |
| Long-term memory / store | deepagents issue 5 |
SKILL.md truncated / only first 100 lines read / read_file limit / progressive disclosure | deepagents issue 6 |
with_structured_output returning None / missing fields | structured-output issue 1 |
create_agent / response_format / ProviderStrategy / ToolStrategy | structured-output issue 1 |
with_structured_output / function_calling / tool_choice unsupported / deepseek-reasoner does not support this tool_choice | structured-output issue 2 |
OpenAI-compatible model / ChatOpenAI not working | model-integration issue 1 |
Reasoning model / reasoning_content / chain-of-thought lost | model-integration issue 2 |
| Chinese model / CN provider / DeepSeek / Qwen / GLM / Moonshot | cn-models README |
langchain-cn-models (embedded) / generate integration class | cn-models README |
| Middleware order messed up / before/after counterintuitive | middleware issue 1 |
state_schema fields not merged / input/output control | middleware issue 2 |
interrupt resume value missing / HITL | middleware issue 3 |
Modifying state inside wrap_model_call has no effect | middleware issue 4 |
Choosing between astream_events and astream for streaming | streaming issue 1 |
| Distinguishing token sources across multiple LLMs | streaming issue 2 |
| Disabling streaming for a specific model | streaming issue 3 |
| Custom events from inside a tool not being emitted | streaming issue 4 |
| Multi-agent: subagents vs handoffs | multi-agent issue 1 |
| Single dispatch tool vs one tool per agent | multi-agent issue 2 |
interrupt can't see subagent state | multi-agent issue 3 |
| Too much subagent wrapper boilerplate | multi-agent issue 4 |
| Quickly building a handoff-based multi-agent setup | multi-agent issue 5 |
Tool returning data to both the model and the app layer / artifact / Command(update=...) | common-issues issue 1 |
MCP tool can't access user_id / store / state / API key | common-issues issue 2 |
invalid_tool_calls / tool never executes / malformed tool-call JSON | common-issues issue 3 |
Dynamic system prompt placeholders / format_prompt / Jinja2 prompt variables | common-issues issue 4 |
| Agent loses context across sessions — personal assistant or support bot | contextseek-middleware issue 1 |
| Multi-tool data-pipeline agent — auditing tool call decisions | contextseek-middleware issue 2 |
| Research agent accumulates raw notes — cross-topic pattern discovery | contextseek-middleware issue 3 |
| SRE incident postmortem agent — tracing knowledge confidence and conflicts | contextseek-middleware issue 4 |
| Enterprise knowledge migration — agent is retrieval-ready on day one | contextseek-middleware issue 5 |
© ob-labs, Apache-2.0. Rendered from Markdown: HTML in the file is shown as text, images as links, and headings moved down two levels. Raw file
Files
SKILL.md and 13 other files in skills/langchain-dev-guide of ob-labs/agentseek.
- SKILL.md
- reference/cn-models/README.md
- reference/cn-models/integration-tests.md
- reference/common-issues.md
- reference/contextseek-middleware.md
- reference/contextseek-params.md
- reference/deepagents.md
- reference/middleware.md
- reference/model-integration.md
- reference/multi-agent.md
- reference/streaming.md
- reference/structured-output.md
- reference/user-queries.md
- template/chat_model.py
Open the folder on GitHubat commit 8abad49
Compare with similar skills
Langchain Dev Guide next to the 5 skills that share the most tags, products or categories with it. Stars are the repository's; “used in” counts other GitHub owners with a copy.
| Skill | Stars | Used in | Tokens | Auto-check | Licence | Repo updated |
|---|---|---|---|---|---|---|
| Langchain Dev Guide this skillob-labs/agentseek | 192 | — | ~1.8k | Automated safety check: Pass | Apache-2.0 | |
| Add Example AgentGetBindu/Bindu | 10k | — | ~1.1k | Automated safety check: Notes | Custom licence | |
| Agent Prompt Engineeringagentailor/fullstack-langgraph-nextjs-agent | 132 | — | ~3.6k | Automated safety check: Pass | MIT | |
| Llmobs IntegrationDataDog/dd-trace-js | 836 | — | ~1.4k | Automated safety check: Pass | Custom licence | |
| Agent Inspectrajudandigam/agent-inspect | 165 | — | ~424 | Automated safety check: Pass | MIT | |
| Tool Designagentailor/fullstack-langgraph-nextjs-agent | 132 | — | ~3.2k | Automated safety check: Pass | MIT |
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Categories
Questions about Langchain Dev Guide
What does Langchain Dev Guide do?
LangChain / LangGraph engineering pitfalls and verified fixes. Langchain Dev Guide is an agent skill from ob-labs/agentseek. LangChain / LangGraph engineering pitfalls and verified fixes.
When should I use Langchain Dev Guide?
Langchain Dev Guide fits situations like: hitting unexpected behavior; making architecture decisions; integrating Chinese LLM providers during LangChain development.
How do I install Langchain Dev Guide in Claude Code?
Run `npx skills add ob-labs/agentseek --skill langchain-dev-guide -a claude-code`. Or copy the skill folder (skills/langchain-dev-guide in ob-labs/agentseek) into .claude/skills/langchain-dev-guide in your project. Claude Code loads it when a task matches its description.
How do I install Langchain Dev Guide in Codex?
Run `npx skills add ob-labs/agentseek --skill langchain-dev-guide -a codex`. Or copy the skill folder (skills/langchain-dev-guide in ob-labs/agentseek) into .agents/skills/langchain-dev-guide in your project. Codex loads it when a task matches its description.
Can I use Langchain Dev Guide in Cursor, Gemini CLI or GitHub Copilot?
Cursor, Gemini CLI, GitHub Copilot and OpenCode also load SKILL.md folders. With the skills CLI, run `npx skills add ob-labs/agentseek --skill langchain-dev-guide -a cursor` (or -a gemini-cli, github-copilot or opencode for the others). To copy it by hand, put the folder in .cursor/skills/langchain-dev-guide, .gemini/skills/langchain-dev-guide, .github/skills/langchain-dev-guide and .opencode/skills/langchain-dev-guide in your project.
What does Langchain Dev Guide need to run?
Going by SKILL.md and its folder, Langchain Dev Guide needs Python for the scripts in its folder. Our summary lists: Python 3.
Does Langchain Dev Guide access the network?
SKILL.md contains no URLs. Any network use would come from the scripts or tools the agent runs. This is read from the text; nothing was executed.
Is Langchain Dev Guide safe to install?
Our automated static check of SKILL.md found no risky patterns, such as piping downloads into a shell, reading credential files or hidden Unicode. It is not a guarantee. Review the folder before installing.
What licence does Langchain Dev Guide use?
Langchain Dev Guide is published under the Apache-2.0 licence (the repository's licence). It allows redistribution, so the full SKILL.md is shown on this page.
How many tokens does Langchain Dev Guide use?
About 1.8k tokens (SKILL.md is roughly 7.4k characters). Agents keep only the skill's name and description in context until a task matches; then they load SKILL.md in full.
What are the alternatives to Langchain Dev Guide?
Skills that share tags, products or a category with Langchain Dev Guide: Add Example Agent (GetBindu/Bindu, 10k stars), Agent Prompt Engineering (agentailor/fullstack-langgraph-nextjs-agent, 132 stars), Llmobs Integration (DataDog/dd-trace-js, 836 stars) and Agent Inspect (rajudandigam/agent-inspect, 165 stars). The comparison table on this page puts their stars, adoption, token cost, safety result and licence side by side.
Who maintains Langchain Dev Guide?
ob-labs (a GitHub organization) maintains it in ob-labs/agentseek, which has 192 GitHub stars. The repository holds 4 skills in this directory. The repository was last updated on September 21, 2026.
Source: ob-labs/agentseek on GitHub. Facts on this page come from the repository at the commit we read; the author's words are quoted as theirs.