Agent skill

Langsmith Deployment

by soba-labs in soba-labs/langchain-agent-skills

Deploy and operate production agent servers with LangSmith Deployment.

MITAuto-check passedAI & LLM Engineering

Install Langsmith Deployment

skills CLI
$ npx skills add soba-labs/langchain-agent-skills --skill langsmith-deployment -a claude-code

Project install by default; add -g for ~/.claude/skills/.

GitHub CLI
$ gh skill install soba-labs/langchain-agent-skills langsmith-deployment --agent claude-code

Project scope by default; add --scope user for a personal install. Needs GitHub CLI 2.90.0 or later (public preview).

Manual copy
$ git clone --depth 1 https://github.com/soba-labs/langchain-agent-skills.git skills-src && mkdir -p .claude/skills && cp -r skills-src/skills/langsmith-deployment .claude/skills/langsmith-deployment && rm -rf skills-src

Use ~/.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/

Facts

Skill name
langsmith-deployment
GitHub stars
107
Token cost
~1.7k tokens
SKILL.md length
561 words
Files
16 (incl. scripts, references, assets)
Skills in repo
9
Repo updated
First seen
Licence
MIT

At a glance

Deploy and operate production agent servers with LangSmith Deployment.

  • Works in 7 steps: Validate langgraph.json → Create a Cloud deployment (US default) → Create a Cloud deployment (EU) → …
  • Work involves choosing Cloud vs Hybrid/Self-hosted-with-control-plane vs Standalone
  • SKILL.md covers Use This Skill When, Deployment Model Selection, Core Workflow and Script-First Commands, plus 7 more sections
  • Runs Python and TypeScript scripts from its folder; calls uv; needs LANGSMITH_API_KEY

What it does

Langsmith Deployment is an agent skill from soba-labs/langchain-agent-skills. Deploy and operate production agent servers with LangSmith Deployment. Use when work involves choosing Cloud vs Hybrid/Self-hosted-with-control-plane vs Standalone, preparing/validating langgraph.json, creating deployments or revisions, rolling back revisions, wiring CI/CD to control-plane APIs, configuring environment variables and secrets, setting monitoring/alerts/webhooks, or troubleshooting deployment/runtime/scaling issues for LangChain/LangGraph applications.

Its SKILL.md is about 1.7k tokens, which your agent loads only when the skill is triggered. The skill folder holds 19 other files, including scripts, reference files and assets (for example `assets/templates/github-actions-deploy.yml`, `assets/templates/kubernetes-deployment.yaml` and `assets/templates/langgraph-cloud.json`).

It sits in AI & LLM Engineering, covering Deployment, LLM observability and Building AI agents. It works with LangSmith, LangGraph and LangChain. The repository describes itself as: A collection of agent-optimized LangChain, LangGraph and LangSmith skills for AI coding assistants. The licence is MIT.

When your agent uses it

  • Work involves choosing Cloud vs Hybrid/Self-hosted-with-control-plane vs Standalone
  • Preparing/validating langgraph.json
  • Creating deployments
  • Rolling back revisions

Example prompts

  • “/langsmith-deployment”

Requirements

  • Python 3
  • Node.js
  • A credential in LANGSMITH_API_KEY

Workflow steps

7 steps, taken from the step headings in SKILL.md.

  1. Validate langgraph.json
  2. Create a Cloud deployment (US default)
  3. Create a Cloud deployment (EU)
  4. Use a self-hosted control plane
  5. Create a revision for an existing deployment
  6. Roll back deployment revision
  7. Generate monitoring + alert setup plan

What it can do on your machine

Read from SKILL.md and the folder at commit a2d4a10. 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 5 files in scripts/ (Python and TypeScript), which the agent can run.

    Shell commands in SKILL.md call:

    • uv

    From the folder's file list and the shell code blocks in SKILL.md.

  • Network

    No URLs in SKILL.md. Its commands use uv, which can reach the network depending on how they are called.

    From URLs in SKILL.md, links to its own repository left out.

  • Credentials

    Names these keys or tokens, usually read from environment variables:

    • LANGSMITH_API_KEY

    From names ending in _API_KEY, _TOKEN, _SECRET, _KEY or _PASSWORD in SKILL.md.

Context cost

Langsmith Deployment loads about 1.7k tokens when it runs, and up to ~7.6k if it reads all its reference files. Until then it costs about 123 tokens; SKILL.md has 561 words of instructions outside code blocks.

Always · name and description, kept in context so the agent knows when to use it
~123
When it runs · the whole SKILL.md, loaded when a task matches
~1.7k
With references · SKILL.md plus every file in references/, read only if the agent opens them
~7.6k

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); the scripts in this folder are not scanned.

SKILL.md

The full file from soba-labs/langchain-agent-skills at commit a2d4a10, republished under its MIT licence (© soba-labs). 561 words, ~1,706 tokens.

Download SKILL.mdSave it as .claude/skills/langsmith-deployment/SKILL.md (or your agent's skills folder). This skill also uses 15 other files; get the full folder from GitHub.
name
langsmith-deployment
description
Deploy and operate production agent servers with LangSmith Deployment. Use when work involves choosing Cloud vs Hybrid/Self-hosted-with-control-plane vs Standalone, preparing/validating langgraph.json, creating deployments or revisions, rolling back revisions, wiring CI/CD to control-plane APIs, configuring environment variables and secrets, setting monitoring/alerts/webhooks, or troubleshooting deployment/runtime/scaling issues for LangChain/LangGraph applications.

LangSmith Deployment

Use this skill to deploy, revise, monitor, and troubleshoot LangGraph-based agents in LangSmith Deployment.

Use This Skill When

  • You need to deploy a new agent to LangSmith Cloud.
  • You need to create a new deployment revision from Git changes or env changes.
  • You need rollback guidance for a failing revision.
  • You need to choose deployment model: Cloud, Hybrid/Self-hosted with control plane, or Standalone server.
  • You need CI/CD automation using LangSmith Deployment control-plane APIs.
  • You need monitoring and alert setup aligned with current LangSmith alert model.
  • You need langgraph.json validation and deployment compatibility checks.

Deployment Model Selection

ModelUse whenBuild/SourceOperates infra
CloudFastest managed production pathGitHub repo via control planeLangSmith
Hybrid/Self-hosted with control planeYou need private data plane + centralized deployment UI/APIContainer image + control planeYou
Standalone serverYou want direct Agent Server hosting without control planeContainerized serverYou

Core Workflow

  1. Validate local deployment config.
  2. Choose deployment model and endpoint strategy.
  3. Create deployment or revision.
  4. Configure environment variables and secrets correctly.
  5. Configure monitoring and alerts.
  6. Verify runtime behavior and keep rollback path ready.

Script-First Commands

1) Validate langgraph.json
bash
uv run python skills/langsmith-deployment/scripts/validate_deployment.py --config langgraph.json --target cloud
2) Create a Cloud deployment (US default)
bash
uv run python skills/langsmith-deployment/scripts/deploy_to_langsmith.py \
  --name "my-agent-prod" \
  --owner my-org \
  --repo my-agent-repo \
  --branch main \
  --config langgraph.json
3) Create a Cloud deployment (EU)
bash
uv run python skills/langsmith-deployment/scripts/deploy_to_langsmith.py \
  --name "my-agent-prod" \
  --owner my-org \
  --repo my-agent-repo \
  --region eu
4) Use a self-hosted control plane
bash
uv run python skills/langsmith-deployment/scripts/deploy_to_langsmith.py \
  --name "my-agent-prod" \
  --owner my-org \
  --repo my-agent-repo \
  --control-plane-url https://<your-langsmith-host>/api-host
5) Create a revision for an existing deployment
bash
uv run python skills/langsmith-deployment/scripts/deploy_to_langsmith.py \
  --name "my-agent-prod" \
  --owner my-org \
  --repo my-agent-repo \
  --deployment-id <deployment-id> \
  --branch main
6) Roll back deployment revision
bash
uv run python skills/langsmith-deployment/scripts/rollback_deployment.py \
  --deployment-id <deployment-id> \
  --list-revisions

uv run python skills/langsmith-deployment/scripts/rollback_deployment.py \
  --deployment-id <deployment-id>
7) Generate monitoring + alert setup plan
bash
uv run python skills/langsmith-deployment/scripts/setup_monitoring.py \
  --project my-agent-prod \
  --output-json /tmp/monitoring-plan.json

Note: setup_monitoring.py generates a docs-aligned setup plan/templates. Alerts are configured in LangSmith UI per project.

Configuration Rules To Enforce

  • graphs is required in langgraph.json.
  • For Python projects, dependencies is required.
  • For JS projects (node_version present), dependencies may be handled via package.json.
  • env may be either a string path to an env file or an inline object map.
  • python_version should be one of 3.11, 3.12, 3.13 when set.
  • pip_installer should be one of auto, pip, uv when set.
  • node_version currently documented for LangGraph.js as 20.

API/Endpoint Notes

  • LangSmith Deployment control-plane API defaults are:
  • US: https://api.host.langchain.com.
  • EU: https://eu.api.host.langchain.com.
  • Self-hosted control-plane base URL is typically https://<host>/api-host.
  • For org-scoped API keys, include workspace/tenant id (X-Tenant-Id), exposed by scripts as --tenant-id.
Show full SKILL.md (216 more words)Show less

Secrets And Environment Guidance

  • Never hardcode secrets in langgraph.json or source code.
  • Prefer environment injection from deployment UI, Kubernetes Secrets, or cloud secret managers.
  • Avoid passing secrets in shell arguments when possible; prefer LANGSMITH_API_KEY env var.
  • In control-plane deployment flows, tracing auth env handling differs from standalone; rely on deployment model docs before overriding tracing/auth vars.
  • For standalone server, ensure required runtime vars are present (DATABASE_URI, REDIS_URI, license key, and any app provider keys).

Verification After Deploy

  • Check deployment/revision status in LangSmith Deployments UI.
  • Verify server API and health endpoints from deployment runtime (/docs etc.).
  • Run a smoke invocation against your assistant/graph.
  • Confirm traces, latency, and error metrics in Monitoring dashboards.

References To Load By Task

  • references/deployment-guide.md: Deployment model choice and end-to-end execution.
  • references/cicd-integration.md: CI/CD stages, control-plane automation patterns, preview/prod strategy.
  • references/environment-management.md: Env var sources, secrets patterns, standalone required vars.
  • references/monitoring-alerts.md: Dashboards, alert model, webhook payload guidance.
  • references/scaling-configuration.md: Scaling responsibilities by model and tuning knobs.
  • references/troubleshooting-deployment.md: Failure triage and rollback strategy.

Script Map

  • scripts/validate_deployment.py: Validate langgraph.json and deployment readiness.
  • scripts/deploy_to_langsmith.py: Create deployment or revision via control-plane API.
  • scripts/deploy_to_langsmith.ts: TypeScript equivalent deploy/revision script.
  • scripts/rollback_deployment.py: List and rollback revisions.
  • scripts/setup_monitoring.py: Generate alert/dashboard/webhook setup plan.

Assets

  • assets/templates/langgraph-cloud.json: Cloud-oriented starter config.
  • assets/templates/github-actions-deploy.yml: CI/CD template for deployment automation.
  • assets/templates/kubernetes-deployment.yaml: Kubernetes template for self-managed environments.
  • assets/templates/.env.example: Env var template for safe sharing.

© soba-labs, MIT. 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 15 other files (scripts, references, assets) in skills/langsmith-deployment of soba-labs/langchain-agent-skills.

  • SKILL.md
  • assets/templates/.env.example
  • assets/templates/github-actions-deploy.yml
  • assets/templates/kubernetes-deployment.yaml
  • assets/templates/langgraph-cloud.json
  • references/cicd-integration.md
  • references/deployment-guide.md
  • references/environment-management.md
  • references/monitoring-alerts.md
  • references/scaling-configuration.md
  • references/troubleshooting-deployment.md
  • scripts/deploy_to_langsmith.py
  • scripts/deploy_to_langsmith.ts
  • scripts/rollback_deployment.py
  • scripts/setup_monitoring.py
  • scripts/validate_deployment.py

Open the folder on GitHubat commit a2d4a10

Compare with similar skills

Langsmith Deployment 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.

Langsmith Deployment compared with similar skills
SkillStarsUsed inTokensAuto-checkLicenceRepo updated
Langsmith Deployment this skillsoba-labs/langchain-agent-skills107—~1.7kAutomated safety check: PassMIT
Agentsop Observability Setupagentsope/SkillAlchemy459—~4.4kAutomated safety check: PassMIT
LangSmith Trace DebuggingComposioHQ/awesome-claude-skills77k9 repos~2.7kAutomated safety check: PassNone
Langchain Dependencieslangchain-ai/langchain-skills1.3k1 repos~3.6kAutomated safety check: PassMIT
Langsmithlangchain-ai/docs425—~935Automated safety check: PassMIT
Verify Against Sourcelangchain-ai/docs425—~1.6kAutomated safety check: PassMIT

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Questions about Langsmith Deployment

What does Langsmith Deployment do?

Deploy and operate production agent servers with LangSmith Deployment. Langsmith Deployment is an agent skill from soba-labs/langchain-agent-skills. Deploy and operate production agent servers with LangSmith Deployment.

When should I use Langsmith Deployment?

Langsmith Deployment fits situations like: work involves choosing Cloud vs Hybrid/Self-hosted-with-control-plane vs Standalone; preparing/validating langgraph.json; creating deployments; rolling back revisions.

How do I install Langsmith Deployment in Claude Code?

Run `npx skills add soba-labs/langchain-agent-skills --skill langsmith-deployment -a claude-code`. Or copy the skill folder (skills/langsmith-deployment in soba-labs/langchain-agent-skills) into .claude/skills/langsmith-deployment in your project. Claude Code loads it when a task matches its description.

How do I install Langsmith Deployment in Codex?

Run `npx skills add soba-labs/langchain-agent-skills --skill langsmith-deployment -a codex`. Or copy the skill folder (skills/langsmith-deployment in soba-labs/langchain-agent-skills) into .agents/skills/langsmith-deployment in your project. Codex loads it when a task matches its description.

Can I use Langsmith Deployment 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 soba-labs/langchain-agent-skills --skill langsmith-deployment -a cursor` (or -a gemini-cli, github-copilot or opencode for the others). To copy it by hand, put the folder in .cursor/skills/langsmith-deployment, .gemini/skills/langsmith-deployment, .github/skills/langsmith-deployment and .opencode/skills/langsmith-deployment in your project.

What does Langsmith Deployment need to run?

Going by SKILL.md and its folder, Langsmith Deployment needs Python and TypeScript for the scripts in its folder, the command-line tools its instructions call (uv) and credentials named LANGSMITH_API_KEY. Our summary lists: Python 3; Node.js; A credential in LANGSMITH_API_KEY.

Does Langsmith Deployment access the network?

SKILL.md contains no URLs. Its commands use uv, which can reach the network depending on how they are called. This is read from the text; nothing was executed.

Is Langsmith Deployment 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. The check reads SKILL.md only: the scripts in the folder are not scanned, so read them before running anything.

What licence does Langsmith Deployment use?

Langsmith Deployment is published under the MIT licence (the repository's licence). It allows redistribution, so the full SKILL.md is shown on this page.

How many tokens does Langsmith Deployment use?

About 1.7k tokens (SKILL.md is roughly 6.8k characters). Agents keep only the skill's name and description in context until a task matches; then they load SKILL.md in full. Its references folder adds about 5.9k tokens, read only when the agent opens those files.

What are the alternatives to Langsmith Deployment?

Skills that share tags, products or a category with Langsmith Deployment: Agentsop Observability Setup (agentsope/SkillAlchemy, 459 stars), LangSmith Trace Debugging (ComposioHQ/awesome-claude-skills, 77k stars), Langchain Dependencies (langchain-ai/langchain-skills, 1.3k stars) and Langsmith (langchain-ai/docs, 425 stars). The comparison table on this page puts their stars, adoption, token cost, safety result and licence side by side.

Who maintains Langsmith Deployment?

soba-labs (a GitHub organization) maintains it in soba-labs/langchain-agent-skills, which has 107 GitHub stars. The repository holds 9 skills in this directory. The repository was last updated on August 17, 2026.

Source: soba-labs/langchain-agent-skills on GitHub. Facts on this page come from the repository at the commit we read; the author's words are quoted as theirs.