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examples-auto-run自动运行示例

Agent Skill

examples-auto-run 用于查找、检索和筛选相关信息,适合在 Codex、Claude、Cursor、Gemini CLI 中需要根据关键词、任务场景或来源线索快速定位候选结果时使用。可结合来源仓库、安装命令和原始 README 继续核验具体用法。安装前建议确认权限范围、维护状态,以及是否会触发联网、命令执行或文件读写。

总安装

539

周安装

22

GitHub Stars

公开资料未说明

下载量

172
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安装说明

本站只整理中文说明和来源信息,不托管安装包,也不代用户安装。

GitHub

来源数

2

许可证

MIT

最后核验

2026-05-01

来源状态

来源可访问

安装方式

通过对话安装

复制提示词发给支持本地命令或 Skills 的 AI 助手,先确认命令和权限,再让它执行。

请帮我安装这个 Agent Skill:examples-auto-run(自动运行示例)
来源仓库:https://github.com/openai/openai-agents-js
仓库路径:skills/examples-auto-run
安装命令:
npx skills add openai/openai-agents-js --skill "examples-auto-run"
安装前请先检查当前环境是否支持对应 CLI,并向我确认将要执行的命令、安装目录、联网范围和文件读写权限;确认后再执行。

命令行安装

复制命令到本机终端执行。该命令会通过 npx skills 从第三方来源获取 Skill;本站只展示命令,不托管安装包,也不自动执行。

AgentSkills.tonpx skills
npx skills add openai/openai-agents-js --skill "examples-auto-run"

简介

examples-auto-run 用于查找、检索和筛选 AI 代理相关技能示例。

  • 适合在 Codex、Claude、Cursor、Gemini CLI 中快速定位可用技能。
  • 通过 npx skills add openai/openai-agents-js --skill "examples-auto-run" 命令安装。
  • 安装前需确认宿主环境兼容性及技能依赖关系。
  • 建议结合来源仓库和 README 核验支持的示例类型和运行条件。

SKILL.md

name
examples-auto-run
description
Run examples:start-all in auto mode with parallel execution, per-script logs, and start/stop helpers.

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)
.codex/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:
.codex/skills/examples-auto-run/scripts/run.sh start --filter basic
.codex/skills/examples-auto-run/scripts/run.sh start --include-server --include-audio

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

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

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

# Tail latest log
.codex/skills/examples-auto-run/scripts/run.sh tail
.codex/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)
.codex/skills/examples-auto-run/scripts/run.sh collect
# Rerun only the entries in .tmp/examples-rerun.txt
.codex/skills/examples-auto-run/scripts/run.sh rerun
# Show the current auto-skip list (env or defaults)
.codex/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
  • 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, agent-patterns:start:routing, customer-service:start, connectors:start, mcp:start:hosted-mcp-on-approval, mcp:start:hosted-mcp-human-in-the-loop.

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.

适合场景

01

用户想查找某类 Agent Skill 时

02

需要根据任务场景推荐可安装能力包时

03

需要对比不同来源的安装命令和来源信息时

04

需要参考平台分布和安装热度时

能力概览

能力 1

按任务关键词查找相关 Skills

能力 2

展示可复制的安装命令

能力 3

保留来源站点、仓库和原始说明,方便继续核验

能力 4

补充不同宿主或平台的使用分布数据

安装后应在对应宿主中按原始 README 的触发条件使用;具体调用方式请以来源页面和 README 为准。

平台分布

Claude Code

28.2%
按下载量换算49

OpenCode

27%
按下载量换算46

windsurf

19.73%
按下载量换算34

Codex

11.68%
按下载量换算20

Antigravity

8.02%
按下载量换算14

Gemini CLI

3.7%
按下载量换算6

安全审计

暂无安全审计结果可展示。

权限和风险

执行命令

安装流程涉及命令执行,可能通过 npx skills add openai/openai-agents-js --skill "examples-auto-run" 联网下载 Skill 或依赖。用户安装前应确认命令来源、仓库内容和执行环境。

安装前确认

本站仅展示第三方公开信息,不托管安装包,不提供自动安装或运行环境。安装前应自行审查源码、依赖和命令行为。当前只有一个来源,正式发布前建议补源仓库或其他目录站核验。

来源信息

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