examples-auto-run

작성자: openai

예제를 자동 모드에서 병렬 실행, 스크립트별 로그, 시작/중지 도우미와 함께 실행합니다: start-all

npx skills add https://github.com/openai/openai-agents-js --skill examples-auto-run

examples-auto-run

What it does

  • Runs pnpm build && pnpm -r build-check first
  • Runs pnpm examples:start-all in auto-input mode (interactive prompts are auto-answered, HITL/MCP/apply-patch are auto-approved).
  • Executes starts in parallel (default concurrency 4) and pipes each start’s stdout/stderr into its own log file under .tmp/examples-start-logs/.
  • Provides start/stop/status/logs/tail helpers via run.sh.
  • If the Codex session ends (no disown/nohup), the child processes receive SIGHUP and exit; stop is also available to clean up manually.

Usage

# Start (auto mode, concurrency=4 by default)
.agents/skills/examples-auto-run/scripts/run.sh start [extra args to examples:start-all]
# If you invoke the skill name alone ($examples-auto-run):
#   - when `.tmp/examples-rerun.txt` exists and is non-empty, it will run `rerun` automatically
#   - otherwise it runs the default `start` command.

# Examples:
.agents/skills/examples-auto-run/scripts/run.sh start --filter basic
.agents/skills/examples-auto-run/scripts/run.sh start --include-server --include-audio

# Check status
.agents/skills/examples-auto-run/scripts/run.sh status

# Stop running job (kills pid from .tmp/examples-auto-run.pid)
.agents/skills/examples-auto-run/scripts/run.sh stop

# List logs (per start script)
.agents/skills/examples-auto-run/scripts/run.sh logs

# Tail latest log
.agents/skills/examples-auto-run/scripts/run.sh tail
.agents/skills/examples-auto-run/scripts/run.sh tail basic__start_hello-world.log

# After a run, build a rerun list from the latest main log (auto-skip list is imported from `scripts/run-example-starts.mjs` and server/audio/external skips are honored)
.agents/skills/examples-auto-run/scripts/run.sh collect
# Rerun only the entries in .tmp/examples-rerun.txt
.agents/skills/examples-auto-run/scripts/run.sh rerun
# Show the current auto-skip list (env or defaults)
.agents/skills/examples-auto-run/scripts/run.sh start --print-auto-skip --dry-run

Defaults (overridable via env)

  • EXAMPLES_INTERACTIVE_MODE=auto
  • AUTO_APPROVE_MCP=1, APPLY_PATCH_AUTO_APPROVE=1, AUTO_APPROVE_HITL=1 (set in runner)
  • EXAMPLES_CONCURRENCY=4
    • sandbox:start:memory-generation is still serialized by the runner because its pre-stop memory generation can contend with shared local resources. Other hosted, Unix-local, and Docker sandbox examples remain parallelized.
  • EXAMPLES_EXECA_TIMEOUT_MS=300000 (5m)
    financial-research-agent and computer-use use 10m inside the script.
  • Includes interactive; excludes server/audio/external by default:
    • EXAMPLES_INCLUDE_INTERACTIVE=1
    • EXAMPLES_INCLUDE_SERVER=0
    • EXAMPLES_INCLUDE_AUDIO=0
  • EXAMPLES_INCLUDE_EXTERNAL=0
    • This means realtime-* / nextjs (tagged as server/audio) are skipped unless you opt in with --include-server / --include-audio or the corresponding env flags.
  • Auto-skip list: EXAMPLES_AUTO_SKIP (comma/space separated) overrides the built-in defaults used by both run.sh and run-example-starts.mjs. Defaults include agent-patterns:start:llm-as-a-judge, connectors:start, mcp:start:hosted-mcp-on-approval, mcp:start:hosted-mcp-human-in-the-loop, sandbox:start:vercel, tools:start:codex, tools:start:codex-same-thread.

Codex execution environment

  • When Codex invokes start or rerun, run the command outside the Codex sandbox by default (sandbox_permissions=require_escalated). Several examples start nested sandboxes, browsers, npm helpers, or local service processes; running from inside the Codex sandbox can produce environment-only failures such as Playwright browser launch permission errors, npm cache permission errors, or nested sandbox setup errors.
  • Use sandboxed execution only when the user explicitly asks for it or when running a narrow dry-run / log inspection command that does not execute examples.

Cancellation / cleanup

  • Jobs are backgrounded but not disowned; if Codex suspends/ends the shell, the process group gets SIGHUP and stops.
  • Manual cleanup: run.sh stop (removes stale pid if already exited).

Log locations

  • .tmp/examples-start-logs/<package>__<script>.log (per start)
  • Main runner log path is printed when start is invoked.
  • Rerun list (generated by collect): .tmp/examples-rerun.txt (one package:script per line).

Notes

  • Auto-skip is centralized (same defaults as above) and can be overridden via EXAMPLES_AUTO_SKIP. Auto-skip entries are excluded from rerun collection and will be removed from rerun execution automatically.
  • Auto-input map covers common interactive prompts; HITL/MCP/apply-patch auto-approve via env is enabled by the runner.
  • Shell tool approvals are auto-approved in auto mode (SHELL_AUTO_APPROVE=1).
  • rerun runs entries sequentially, continues after failures, and rewrites .tmp/examples-rerun.txt with only the remaining failures. Auto-skip entries are not re-added.
  • Behavioral validation is not done in the runner, so Codex must immediately perform it after every start or rerun invocation without waiting for the user to ask. Required steps:
    1. Read the example source to infer intended flow from code/comments (tools invoked, expected outputs, guards, approvals).
    2. Read the matching log under .tmp/examples-start-logs/.
    3. Compare intent vs. log: confirm key actions/results happened; flag omissions or divergences.
    4. Do this for all exit-0 entries, not just samples.
    5. Summarize findings right after the run completes; when “OK”, note what was checked (e.g., “tools called + final message emitted”).
    6. When reporting, do not omit or ellipsize outputs that justify the validation; include the full relevant lines (keep it concise but untruncated).
  • The runner prints a full table after the summary: one row per start script with status, package:script, info (reason/exit/skipped), and the log path. If the run stops before the table appears, point the analyzer at the latest main_*.log to reconstruct a table and validations.

openai의 다른 스킬

user-context
openai
데이터 분석 플러그인의 지속적인 소스 라우팅 기본 설정, 온보딩 로직, 설정 진행 상황 및 의미 계층 레지스트리를 로드하거나 관리합니다.
official
notion-research-documentation
openai
Notion 콘텐츠를 조사하고 인용문과 함께 구조화된 브리핑, 보고서 또는 비교 자료로 종합합니다. 대상 질의를 사용해 Notion 페이지를 검색하고 가져온 후, 인라인 출처 인용과 참고 문헌 섹션을 포함해 주제별로 결과를 정리합니다. 범위와 사용자 목표에 따라 네 가지 출력 형식(빠른 브리핑, 연구 요약, 비교, 종합 보고서) 중에서 선택합니다. 내장 템플릿을 사용해 Notion 페이지를 생성 및 업데이트하고, 새 정보가 도착하면 출처를 직접 연결하고 변경 사항을 추적합니다...
official
rcsb-pdb-skill
openai
핵심 메타데이터, Search API 쿼리 및 FASTA 다운로드를 위한 간결한 RCSB PDB 요청을 제출합니다. 사용자가 간결한 RCSB 요약을 원할 때 사용하며, 원시 JSON 또는…을 저장합니다.
official
pdf
openai
PDF 읽기, 생성 및 검증 기능을 제공하며, 시각적 렌더링과 프로그래매틱 생성을 지원합니다. Poppler(pdftoppm)를 사용하여 PDF 페이지를 PNG로 렌더링하여 레이아웃, 간격, 타이포그래피를 시각적으로 검사할 수 있습니다. reportlab을 사용하여 프로그래매틱 방식으로 PDF를 생성하여 안정적인 포맷을 보장하며, pdfplumber 또는 pypdf를 통해 텍스트와 메타데이터를 추출합니다. 품질 기준을 준수합니다: 잘린 텍스트, 겹치는 요소, 깨진 표, 렌더링 아티팩트가 없어야 하며, ASCII 하이픈만 사용하고 사람이 읽을 수 있는 인용을 사용합니다.
official
test-coverage-improver
openai
Improve test coverage in the OpenAI Agents JS monorepo: run `pnpm test:coverage`, inspect coverage artifacts, identify low-coverage files and branches, propose…
official
playwright
openai
터미널 기반 브라우저 자동화로 요소 스냅샷 및 대화형 UI 워크플로우 지원. playwright-cli 래퍼 스크립트를 통해 작동하며(npx 필요), 헤드리스 및 헤드 모드 모두 지원하여 시각적 디버깅 가능. 핵심 워크플로우: 페이지 열기, 안정적인 요소 참조를 위한 스냅샷 생성, 참조를 사용한 상호작용, 탐색 또는 DOM 변경 후 재스냅샷. 양식 작성, 클릭, 타이핑, 다중 탭 관리, 스크린샷/PDF 캡처, 흐름 디버깅을 위한 트레이스 기록 포함. 요소 참조(예: e3, e15)...
official
ukb-topmed-phewas-skill
openai
단일 변이에 대한 간결한 UKB-TOPMed PheWAS 요약을 가져오며, rsID, GRCh37 또는 GRCh38 입력을 받아 필요한 GRCh38 쿼리로 변환합니다. 다음과 같은 경우에 사용하세요…
official
code-review-context
openai
모델 가시 컨텍스트
official