跳到主要内容

smoke-test 精选

End-to-end smoke test skill for DeerFlow. Guides through: 1) Pulling latest code, 2) Docker OR Local installation and deployment (user preference, default to Local if Docker network issues), 3) Service availability verification, 4) Health check, 5) Final test report. Use when the user says "run smoke test", "smoke test deployment", "verify installation", "test service availability", "end-to-end test", or similar.

在 GitHub 打开

安装方式

cp -r .agent/skills/smoke-test ~/.claude/skills/smoke-test

把该 skill 目录放进客户端 skills 目录。不同客户端的目录可能不同,Claude Code 默认是 ~/.claude/skills/

整仓一次性获取:git clone --depth 1 https://github.com/bytedance/deer-flow.git

依赖与权限

  • 需要 API Key —— 使用前需配置相应的密钥环境变量
  • 需要联网访问外部服务
  • 依赖外部命令:git node pnpm python uv docker make
  • 以上为按正文与 frontmatter 自动推断的信号,仅供参考;安装前建议先阅读原文。
触发场景
smoke test deploymentverify installationtest serv

SKILL.md 正文

来源 bytedance/deer-flow@b346b17 · 许可 MIT · 内容未修改

DeerFlow Smoke Test Skill

This skill guides the Agent through DeerFlow's full end-to-end smoke test workflow, including code updates, deployment (supporting both Docker and local installation modes), service availability verification, and health checks.

Deployment Mode Selection

This skill supports two deployment modes:

  • Local installation mode (recommended, especially when network issues occur) - Run all services directly on the local machine
  • Docker mode - Run all services inside Docker containers

Selection strategy:

  • If the user explicitly asks for Docker mode, use Docker
  • If network issues occur (such as slow image pulls), automatically switch to local mode
  • Default to local mode whenever possible

Structure

smoke-test/
├── SKILL.md                          ← You are here - core workflow and logic
├── scripts/
│   ├── check_docker.sh               ← Check the Docker environment
│   ├── check_local_env.sh            ← Check local environment dependencies
│   ├── frontend_check.sh             ← Frontend page smoke check
│   ├── pull_code.sh                  ← Pull the latest code
│   ├── deploy_docker.sh              ← Docker deployment
│   ├── deploy_local.sh               ← Local deployment
│   └── health_check.sh               ← Service health check
├── references/
│   ├── SOP.md                        ← Standard operating procedure
│   └── troubleshooting.md            ← Troubleshooting guide
└── templates/
    ├── report.local.template.md      ← Local mode smoke test report template
    └── report.docker.template.md     ← Docker mode smoke test report template

Standard Operating Procedure (SOP)

Phase 1: Code Update Check

  1. Confirm current directory - Verify that the current working directory is the DeerFlow project root
  2. Check Git status - See whether there are uncommitted changes
  3. Pull the latest code - Use git pull origin main to get the latest updates
  4. Confirm code update - Verify that the latest code was pulled successfully

Phase 2: Deployment Mode Selection and Environment Check

Choose deployment mode:

  • Ask for user preference, or choose automatically based on network conditions
  • Default to local installation mode

Local mode environment check:

  1. Check Node.js version - Requires 22+
  2. Check pnpm - Package manager
  3. Check uv - Python package manager
  4. Check nginx - Reverse proxy
  5. Check required ports - Confirm that ports 2026, 3000, and 8001 are not occupied

Docker mode environment check (if Docker is selected):

  1. Check whether Docker is installed - Run docker --version
  2. Check Docker daemon status - Run docker info
  3. Check Docker Compose availability - Run docker compose version
  4. Check required ports - Confirm that port 2026 is not occupied

Phase 3: Configuration Preparation

  1. Check whether config.yaml exists
  • If it does not exist, run make config to generate it
  • If it already exists, check whether it needs an upgrade with make config-upgrade
  1. Check the .env file
  • Verify that required environment variables are configured
  • Especially model API keys such as OPENAI_API_KEY

Phase 4: Deployment Execution

Local mode deployment:

  1. Check dependencies - Run make check
  2. Install dependencies - Run make install
  3. (Optional) Pre-pull the sandbox image - If needed, run make setup-sandbox
  4. Start services - Run make start (production mode)
  5. Wait for startup - Give all services enough time to start completely (90-120 seconds recommended)

Docker mode deployment (if Docker is selected):

  1. Initialize Docker environment - Run make docker-init
  2. Start Docker services - Run make up (production mode)
  3. Wait for startup - Give all containers enough time to start completely (60 seconds recommended)

Phase 5: Service Health Check

Local mode health check:

  1. Check process status - Confirm that Gateway, Frontend, and Nginx processes are all running
  2. Check frontend service - Visit http://localhost:2026 and verify that the page loads
  3. Check API Gateway - Verify the http://localhost:2026/health endpoint
  4. Check LangGraph-compatible API - Verify the /api/langgraph/* route exposed by Gateway
  5. Frontend route smoke check - Run bash .agent/skills/smoke-test/scripts/frontend_check.sh to verify key routes under /workspace. The script auto-detects whether authentication is enabled and, if so, registers / logs in a smoke-test user so the real pages are verified rather than the login redirect.

Docker mode health check (when using Docker):

  1. Check container status - Run docker ps and confirm that all containers are running
  2. Check frontend service - Visit http://localhost:2026 and verify that the page loads
  3. Check API Gateway - Verify the http://localhost:2026/health endpoint
  4. Check LangGraph-compatible API - Verify the /api/langgraph/* route exposed by Gateway
  5. Frontend route smoke check - Run bash .agent/skills/smoke-test/scripts/frontend_check.sh to verify key routes under /workspace. The script auto-detects whether authentication is enabled and, if so, registers / logs in a smoke-test user so the real pages are verified rather than the login redirect.

Optional Functional Verification

  1. List available models - Verify that model configuration loads correctly
  2. List available skills - Verify that the skill directory is mounted correctly
  3. Simple chat test - Send a simple message to verify the end-to-end flow

Phase 6: Generate Test Report

  1. Collect all test results - Summarize execution status for each phase
  2. Record encountered issues - If anything fails, record the error details
  3. Generate the final report - Use the template that matches the selected deployment mode to create the complete test report, including overall conclusion, detailed key test cases, and explicit frontend page / route results
  4. Provide follow-up recommendations - Offer suggestions based on the test results

Execution Rules

  • Follow the sequence - Execute strictly in the order described above
  • Idempotency - Every step should be safe to repeat
  • Error handling - If a step fails, stop and report the issue, then provide troubleshooting suggestions
  • Detailed logging - Record the execution result and status of each step
  • User confirmation - Ask for confirmation before potentially risky operations such as overwriting config
  • Mode preference - Prefer local mode to avoid network-related issues
  • Template requirement - The final report must use the matching template under templates/; do not output a free-form summary instead of the template-based report
  • Report clarity - The execution summary must include the overall pass/fail conclusion plus per-case result explanations, and frontend smoke check results must be listed explicitly in the report
  • Optional phase handling - If functional verification is not executed, do not present it as a separate skipped phase in the final report

Known Acceptable Warnings

The following warnings can appear during smoke testing and do not block a successful result:

  • Feishu/Lark SSL errors in Gateway logs (certificate verification failure) can be ignored if that channel is not enabled
  • Warnings in Gateway logs about missing methods in the custom checkpointer, such as adelete_for_runs or aprune, do not affect the core functionality
  • The frontend_check.sh script automatically handles authentication. When auth is enabled it registers / logs in a smoke-test user ([email protected] by default) to verify the real /workspace/* pages. The registration may produce a log entry from the auth provider, which is expected and harmless.

Key Tools

Use the following tools during execution:

  1. bash - Run shell commands
  2. present_file - Show generated reports and important files
  3. task_tool - Organize complex steps with subtasks when needed

Success Criteria

Smoke test pass criteria (local mode):

  • [x] Latest code is pulled successfully
  • [x] Local environment check passes (Node.js 22+, pnpm, uv, nginx)
  • [x] Configuration files are set up correctly
  • [x] make check passes
  • [x] make install completes successfully
  • [x] make dev starts successfully
  • [x] All service processes run normally
  • [x] Frontend page is accessible
  • [x] Frontend route smoke check passes (/workspace key routes)
  • [x] API Gateway health check passes
  • [x] Test report is generated completely

Smoke test pass criteria (Docker mode):

  • [x] Latest code is pulled successfully
  • [x] Docker environment check passes
  • [x] Configuration files are set up correctly
  • [x] make docker-init completes successfully
  • [x] make up completes successfully
  • [x] All Docker containers run normally
  • [x] Frontend page is accessible
  • [x] Frontend route smoke check passes (/workspace key routes)
  • [x] API Gateway health check passes
  • [x] Test report is generated completely

Read Reference Files

Before starting execution, read the following reference files:

  1. references/SOP.md - Detailed step-by-step operating instructions
  2. references/troubleshooting.md - Common issues and solutions
  3. templates/report.local.template.md - Local mode test report template
  4. templates/report.docker.template.md - Docker mode test report template

质量与来源

所属仓库
bytedance/deer-flow
仓库星标
8.4 万
最近更新
今天
采集时间
今天
commit
b346b17fce89
内容指纹
sha256:6872ae52ec3f701
文件路径
.agent/skills/smoke-test/SKILL.md

同仓库其它 Skill

查看全部 32 个
blocking-io-guard
Ensure async-path backend code that could block the asyncio event loop is protected by a teeth-verified runtime anchor in tests/blocking_io/. Use when changing backend Python under app/, packages/harness/deerflow/, or scripts/, when running a blocking-IO triage round over the whole repo, or when a reviewer/CI asks for blocking-IO coverage. Runs a deterministic scan (changed-lines or full-repo), routes each candidate, drafts/extends an anchor, and proves it fails when the blocking IO regresses.
精选 bytedance/deer-flow 8.4 万 原文
Codex CLIMCP 客户端
deerflow-maintainer-orchestrator
Use when a DeerFlow maintainer needs comment-only GitHub issue or PR handling: resolve issue/PR scopes with gh, analyze issues, post or draft issue comments, perform PR review comments, review PR or issue batches, compare competing PRs that target the same issue, give fix strategy, risk classification, and validation guidance. Intended for maintainers and trusted local agents, not general contributors.
精选 bytedance/deer-flow 8.4 万 原文
Codex CLIMCP 客户端
engineer-system-change
Evaluate and carry out non-trivial software-system changes from first principles. Use when assessing RFCs, issues, designs, features, refactors, migrations, dependency changes, or proposed fields, events, APIs, modules, and services whose need, consumers, system fit, validation, or rollback require scrutiny. Read the actual system, identify the concrete problem and named semantic consumers, choose the smallest sufficient solution, reject pseudo-requirements and speculative abstractions, and require evidence proportional to risk. Do not use for mechanical edits, source-code explanation, or a dedicated review of an already-complete diff.
精选 bytedance/deer-flow 8.4 万 原文
Codex CLIMCP 客户端
academic-paper-review
Use this skill when the user requests to review, analyze, critique, or summarize academic papers, research articles, preprints, or scientific publications. Supports comprehensive structured reviews covering methodology assessment, contribution evaluation, literature positioning, and constructive feedback generation. Trigger on queries involving paper URLs, uploaded PDFs, arXiv links, or requests like "review this paper", "analyze this research", "summarize this study", or "write a peer review".
精选 bytedance/deer-flow 8.4 万 原文
Codex CLIMCP 客户端
bootstrap
Generate a personalized SOUL.md through a warm, adaptive onboarding conversation. Trigger when the user wants to create, set up, or initialize their AI partner's identity — e.g., "create my SOUL.md", "bootstrap my agent", "set up my AI partner", "define who you are", "let's do onboarding", "personalize this AI", "make you mine", or when a SOUL.md is missing. Also trigger for updates: "update my SOUL.md", "change my AI's personality", "tweak the soul".
精选 bytedance/deer-flow 8.4 万 原文
Codex CLIMCP 客户端
chart-visualization
This skill should be used when the user wants to visualize data. It intelligently selects the most suitable chart type from 26 available options, extracts parameters based on detailed specifications, and generates a chart image using a JavaScript script.
精选 bytedance/deer-flow 8.4 万 原文
Codex CLIMCP 客户端

相似 Skill

更多「研究」
last30days
Research what people actually say about any topic in the last 30 days. Pulls posts and engagement from Reddit, X, YouTube, TikTok, Hacker News, Polymarket, GitHub, and the web. Includes a doctor health check to diagnose broken or missing sources.
精选 mvanhorn/last30days-skill 6.4 万 原文
Claude CodeCodex CLIMCP 客户端
agent-reach
MUST USE when user wants to 调研/research/搜索/search/查/找/look up anything on the internet — e.g. 全网调研 X / 帮我调研一下 X / 查一下 X / 搜搜 X / 看看大家怎么评价 X / X 上有什么讨论 / research this topic。 Also MUST USE when user mentions any platform or shares any URL/链接: 小红书/xiaohongshu/xhs, Twitter/推特/X, B站/bilibili, Reddit, Facebook, Instagram, V2EX, LinkedIn/领英/Boss直聘/招聘/求职/jobs, YouTube, GitHub code search, 小宇宙播客, 雪球/股票行情, RSS feeds, or any web URL. 16 platforms, multi-backend routing (OpenCLI / per-platform CLIs / APIs). Zero config for 6 channels. Run `agent-reach doctor --json` to see which backend serves each platform right now. NOT for: 写报告/数据分析/翻译等内容加工(本 skill 只负责从互联网获取内容); 发帖/评论/点赞等写操作;已有专门 skill 的平台(先用专门 skill)。 【路由方式】SKILL.md 包含路由表和常用命令,复杂场景需按需阅读对应分类的 references/*.md。 分类:search / social (小红书/推特/B站/V2EX/Reddit/Facebook/Instagram) / career(LinkedIn/Boss直聘) / dev(github) / web(网页/文章/RSS) / video(YouTube/B站/播客) / finance(雪球/股票)。
精选 Panniantong/Agent-Reach 9.6 万 原文
Claude CodeCursorMCP 客户端
academic-paper-reviewer
Multi-perspective academic paper review with dynamic reviewer personas. Runs a 5-seat, role-separated review panel (Journal-Fit Reviewer + 3 peer-review roles + Devil's Advocate) with field-specific expertise; role separation is not a claim of independent error processes. Supports full review, re-review (verification), quick assessment, methodology focus, Socratic guided, and calibration modes. Triggers on: review paper, peer review, manuscript review, referee report, review my paper, critique paper, simulate review, editorial review, calibrate reviewer, reviewer calibration, measure reviewer accuracy, 審查論文, 論文審查, 模擬審查, 同儕審查, 幫我審這篇, 以審查人角度評估, 審查者校準, 논문 심사, 동료 심사, 모의 심사, 심사자 관점에서 평가, 심사자 보정, revisar artículo, revisión entre pares, revisión de manuscrito, informe de árbitro, revisa mi artículo, criticar artículo, simular revisión, revisión editorial, calibrar revisor.
精选 Imbad0202/academic-research-skills 5.2 万 原文
Claude Code
academic-paper
12-agent academic paper writing pipeline. 11 modes (full/plan/outline/revision/revision-coach/abstract/lit-review/format-convert/citation-check/disclosure/rebuttal-audit). 6 paper types, 5 citation formats, bilingual abstracts, LaTeX/DOCX-via-Pandoc/PDF output. Style Calibration + Writing Quality Check + Anti-Patterns with IRON RULE markers. Triggers: write paper, academic paper, guide my paper, parse reviews, I got reviewer comments, revision roadmap, should we push back, conference rebuttal, grant panel response, audit my rebuttal, check my response draft, AI disclosure, check citations, citation check, check my references, verify references, look over the refs, 寫論文, 學術論文, 引導我寫論文, 審查意見, 我收到審查意見, 修訂路線圖, 評估回覆, 檢查引用, 引用檢查, 檢查參考文獻, 核對文獻, 논문 작성, 초록 작성, 논문 수정, 논문 계획을 도와줘, 심사 의견을 받았어, 심사 의견 반영, 답변서 점검, AI 사용 고지, 인용 확인, 인용 형식 검사, enmendar mi artículo, redactar artículo, guía mi artículo, analizar reseñas, auditar mi respuesta, verificar borrador de respuesta, verificar citas, divulgación de IA.
精选 Imbad0202/academic-research-skills 5.2 万 原文
Claude Code
academic-pipeline
Orchestrator for the full academic research pipeline: research -> write -> integrity check -> review -> revise -> re-review -> re-revise -> final integrity check -> finalize. Coordinates deep-research, academic-paper, and academic-paper-reviewer into a seamless 10-stage workflow with mandatory, coverage-bounded integrity checks, two-stage peer review, and auditable quality-assurance artifacts. Triggers on: academic pipeline, research to paper, full paper workflow, paper pipeline, end-to-end paper, research-to-publication, complete paper workflow, 연구부터 논문까지, 연구 주제 설정부터 논문 완성까지, 논문 전체 워크플로, flujo de trabajo académico, investigación a artículo, flujo completo de artículo, pipeline de investigación completa, publicación de investigación, flujo de trabajo completo del artículo.
精选 Imbad0202/academic-research-skills 5.2 万 原文
Claude Code
deep-research
Universal deep research agent team. 13-agent pipeline for rigorous academic research on any topic. 8 modes: full research, quick brief, paper review, lit-review, fact-check, three-way literature scan, Socratic guided research dialogue, and systematic review with optional meta-analysis. Covers research question formulation, Socratic mentoring, methodology design, systematic literature search, source verification, cross-source synthesis, risk of bias assessment, meta-analysis, APA 7.0 report compilation, editorial review, devil's advocate challenges, ethics review, and post-research literature monitoring. Triggers on: research, deep research, literature review, systematic review, meta-analysis, PRISMA, evidence synthesis, fact-check, WHY HOW WHAT papers, 3W literature scan, guide my research, help me think through, 研究, 深度研究, 文獻回顧, 文獻探討, 系統性回顧, 後設分析, 事實查核, 三段式文獻掃描, 引導我的研究, 幫我釐清, 幫我想想, 我不確定要研究什麼, 研究方向, 研究主題, 심층 연구, 문헌 조사, 체계적 문헌고찰, 메타분석, 사실 확인, 연구 방향을 잡아줘, 연구 주제 정하는 것을 도와줘, revisión de literatura, metaanálisis
精选 Imbad0202/academic-research-skills 5.2 万 原文
Claude Code