
examples-auto-run
Run examples:start-all in auto mode with parallel execution, per-script logs, and start/stop helpers.
- Installs
- 106
- Last 24h
- —
- Trending rank
- —
- Security
- Not audited
Install
Works with every agent the skills CLI supports.
npx skills add https://github.com/openai/openai-agents-js --skill examples-auto-run- 01
Install
Run the command in your project. The CLI asks which agents to install for.
- 02
Describe the task
Ask your agent for something this skill covers. It loads examples-auto-run automatically when relevant.
- 03
Review the result
The agent follows the SKILL.md steps, scripts and references bundled with the skill.
SKILL.md
The instructions your agent reads when the skill is triggered.
examples-auto-run
What it does
- Runs
pnpm build && pnpm -r build-checkfirst - Runs
pnpm examples:start-allin 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;
stopis 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=autoAUTO_APPROVE_MCP=1,APPLY_PATCH_AUTO_APPROVE=1,AUTO_APPROVE_HITL=1(set in runner)EXAMPLES_CONCURRENCY=4sandbox:start:memory-generationis 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-agentandcomputer-useuse 10m inside the script.- Includes interactive; excludes server/audio/external by default:
EXAMPLES_INCLUDE_INTERACTIVE=1EXAMPLES_INCLUDE_SERVER=0EXAMPLES_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-audioor the corresponding env flags.
- This means
- Auto-skip list:
EXAMPLES_AUTO_SKIP(comma/space separated) overrides the built-in defaults used by bothrun.shandrun-example-starts.mjs. Defaults includeagent-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
startorrerun, 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
startis invoked. - Rerun list (generated by
collect):.tmp/examples-rerun.txt(onepackage:scriptper 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). rerunruns entries sequentially, continues after failures, and rewrites.tmp/examples-rerun.txtwith 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
startorreruninvocation without waiting for the user to ask. Required steps:- Read the example source to infer intended flow from code/comments (tools invoked, expected outputs, guards, approvals).
- Read the matching log under
.tmp/examples-start-logs/. - Compare intent vs. log: confirm key actions/results happened; flag omissions or divergences.
- Do this for all exit-0 entries, not just samples.
- Summarize findings right after the run completes; when “OK”, note what was checked (e.g., “tools called + final message emitted”).
- 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 latestmain_*.logto reconstruct a table and validations.
FAQ
What does the examples-auto-run skill do?
Run examples:start-all in auto mode with parallel execution, per-script logs, and start/stop helpers.
How do I install examples-auto-run?
Run npx skills add https://github.com/openai/openai-agents-js --skill examples-auto-run in your project. The skills CLI detects the agents you use and copies the skill into the right folder. For Claude Code you can also place the skill folder at ~/.claude/skills/examples-auto-run/ (personal) or .claude/skills/examples-auto-run/ (project).
Which AI agents can use examples-auto-run?
Any agent that supports the open Agent Skills format (a folder with a SKILL.md file), including Claude Code, Codex, Cursor, GitHub Copilot, Gemini CLI, Windsurf, Cline, OpenCode and more.
Is examples-auto-run safe to install?
No partner security audit is available yet. Skills can run commands and scripts, so read the SKILL.md and any bundled files before installing.
Who maintains examples-auto-run?
It is published by openai in openai/openai-agents-js, and it is an official skill from the maker of the technology it covers. It has 106 recorded installs.
More from openai/openai-agents-js
docs-sync
openai/openai-agents-js
Audit or update authored English SDK documentation within a requested topic or diff using implementation evidence.
pnpm-upgrade
openai/openai-agents-js
Open the skill to read its SKILL.md instructions.
code-change-verification
openai/openai-agents-js
Run the required final install, build, type, lint, test, and format checks after eligible SDK changes pass review.
test-coverage-improver
openai/openai-agents-js
Open the skill to read its SKILL.md instructions.
openai-knowledge
openai/openai-agents-js
Retrieve authoritative OpenAI API and platform documentation when an integration or claim needs current external evidence.
pr-draft-summary
openai/openai-agents-js
Prepare a local PR title, description, and branch suggestion when requested or after eligible implementation work.
Popular ai & agents skills
google-agents-cli-publish
google/agents-cli
This skill should be used when the user wants to "publish an agent", "publish my ADK agent", "register an agent with Gemini", "publish to Gemini" (formerly Gemini Enterprise), or needs guidance on the agents-cli publish gemini command. Also use when the user wants to "manage agents in Agent Registry", "list/update/delete registered agents", or "register an MCP server". Covers ADK vs A2A registration modes, programmatic and interactive usage, flag reference, auto-detection from deployment metadata, Agent Registry fleet management, and troubleshooting. Part of the agents-cli skills suite. Do NOT use for deployment (use google-agents-cli-deploy).
google-agents-cli-eval
google/agents-cli
This skill should be used when the user wants to "run an evaluation", "evaluate my agent", "evaluate my ADK agent", "write an eval dataset", "analyze eval failures", "compare eval results", "optimize agent", or needs guidance on the Gemini platform eval methodology and the Quality Flywheel. Covers eval metrics, dataset schema, LLM-as-judge scoring, and common failure causes. Applies to any agents-cli project, whatever framework the agent is written in. Do NOT use for agent API code patterns (ADK: use google-agents-cli-adk-code), deployment (use google-agents-cli-deploy), or project scaffolding (use google-agents-cli-scaffold).
skill-creator
anthropics/skills
Create new skills, modify and improve existing skills, and measure skill performance. Use when users want to create a skill from scratch, edit, or optimize an existing skill, run evals to test a skill, benchmark skill performance with variance analysis, or optimize a skill's description for better triggering accuracy.
codex-pet
prime-skills/runcomfy-agent-skills
Codex Pet generator on RunComfy. Build a Codex-compatible Codex Pet spritesheet.webp + pet.json from a single reference image, drop it into ${CODEXHOME:-$HOME/.codex}/pets/ / and Codex picks it up as a custom Codex Pet next to the 8 built-ins. This skill produces the exact Codex Pet atlas Codex expects (1536x1872 PNG/WebP, 8 cols x 9 rows, 192x208 cells, 9 animation states — idle, running-right, running-left, waving, jumping, failed, waiting, running, review). Calls OpenAI GPT Image 2 edit ONCE via the local RunComfy CLI as runcomfy run openai/gpt-image-2/edit to produce a canonical Codex Pet pose, then assembles all 9 animation rows programmatically with ImageMagick micro-transforms — no Codex Pro, no $imagegen, no OPENAIAPIKEY required, only RUNCOMFYTOKEN. Triggers on "codex pet", "create codex pet", "make codex pet", "hatch codex pet", "/hatch image", "desktop pet codex", "codex pets", "spritesheet.webp", or any explicit ask to build a custom pet for OpenAI Codex.
full-output-enforcement
leonxlnx/taste-skill
Overrides default LLM truncation behavior. Enforces complete code generation, bans placeholder patterns, and handles token-limit splits cleanly. Apply to any task requiring exhaustive, unabridged output.
executing-plans
obra/superpowers
Use when executing an implementation plan in the current session as the implementer yourself — your human partner chose inline execution, or no subagent tool is available