Agent Native

examples-run-analysis

This skill analyzes logs and source files from completed repository example runs to validate whether examples executed correctly.

by OpenAIOfficial publisher

Identity proven by GitHub's verified organisation badge (openai)

Agents
Claude Code, Codex, Cursor, Gemini CLI, GitHub Copilot, OpenCode, claude.ai and API
License
MIT (permissive)
Pin
05241c7pinned Oct 9, 2026
Context cost
about 1,100 tokenswhen the skill loads
GitHub stars
3,899on openai/openai-agents-js
Scripts
None found

What it does

“Analyze logs and source from a completed repository example run. Never execute or control examples.”
The author's description, from SKILL.md

Generated summary from the skill's own text

This skill analyzes logs and source files from completed repository example runs to validate whether examples executed correctly. It performs read-only inspection of evidence, comparing intended behavior in source code and comments against actual log output, without executing or modifying any examples or workflows.

When to use it

  • Verify examples executed as designed after a manual workflow run
  • Classify example outcomes as passed, skipped, or failed with reasons
  • Inspect logs and source to confirm expected tool calls or behavior occurred
  • Validate run scope and determine if evidence is complete and current

When not to

  • Do not use to execute, rerun, or manage example workflows yourself
  • When logs are missing, incomplete, or a workflow is still running
  • To modify source files, create new processes, or alter repository state

Install

These commands install from the publisher's repository and need no account.

skills CLI

npx skills add openai/openai-agents-js --skill examples-run-analysis

Installs from the repository's default branch, which may have changed since the commit we checked.

GitHub CLI 2.90 or later

gh skill install openai/openai-agents-js examples-run-analysis@05241c7aa3d5629acc7407dd8ee1105637fe0369

Installs the commit we checked (05241c7).

Copy by hand

Download the folder at 05241c7 and put it in .claude/skills/examples-run-analysis for Claude Code and in .agents/skills/examples-run-analysis for Codex, Cursor, Gemini CLI, GitHub Copilot and OpenCode.

Skill folder on GitHub at 05241c7

Copy for your agent

A prompt for any coding agent. It installs this skill from GitHub at the pinned commit, copies the files as they are, and runs nothing unless you ask.

Prompt

Install the agent skill "examples-run-analysis" by OpenAI.

Source, pinned to commit 05241c7aa3d5629acc7407dd8ee1105637fe0369:
https://github.com/openai/openai-agents-js/tree/05241c7aa3d5629acc7407dd8ee1105637fe0369/.agents/skills/examples-run-analysis

1. Download that folder at exactly this commit. Do not use the default branch.
2. Copy every file unchanged, keeping the folder structure, into .claude/skills/examples-run-analysis/ for Claude Code and .agents/skills/examples-run-analysis/ for Codex, Cursor, Gemini CLI, GitHub Copilot and OpenCode. Create the folders if they do not exist.
3. Do not edit the files, and do not run any script in the folder unless I ask you to.
4. When you are done, list the files you copied and where you put them.

Listing and checks: https://www.agentnative.dev/skills/openai/examples-run-analysis

SKILL.md at the pin

---
name: examples-run-analysis
description: Analyze logs and source from a completed repository example run. Never execute or control examples.
---

# Examples Run Analysis

Use this skill only to analyze evidence produced by a completed manual example workflow. The repository workflow belongs to the contributor who invoked its pnpm command; this skill never owns execution or cleanup.

## Read-only boundary

- Use only read-only file listing, reading, and searching to inspect repository sources and existing evidence.
- Never invoke pnpm, Node.js, Bash, an example, a build, a test, or another workflow command.
- Never start, rerun, retry, stop, signal, or kill a process. Never create or own a background job.
- Never request elevated execution, broaden filesystem or network authority, source shell startup files, or alter credentials.
- Never create, modify, rename, or delete a log, rerun list, result file, source file, PID file, or other repository path.
- Do not treat this skill as authorization to perform a missing run. Ask the user to run the appropriate pnpm command manually and return after completed evidence exists.

## Evidence to inspect

1. Find the newest completed `.tmp/examples-start-logs/main_*.log`. A completed main log contains the final `Done.` line, validation summary, `All start results:` heading, table header, and one final table row for every discovered entry in that run. Treat a log without that complete footer as incomplete or still running.
2. For every final table row with `passed` and `exit 0`, resolve the full `package:script` name from the earlier start or skip lines when the fixed-width table abbreviated it. Read the matching `.tmp/examples-start-logs/<package>__<script>.log` and the example's `package.json` script target plus its relevant source files.
3. Read the runner sources `scripts/run-examples-workflow.sh` and `scripts/run-example-starts.mjs` when needed to interpret filters, auto-input, concurrency, serialized entries, configured exclusions, auto-skips, optional server/audio/external modes, and timeouts.

## Evidence freshness and completeness

Do not analyze a run as current when any of these conditions applies:

- no main log exists;
- the newest main log lacks its complete footer or indicates cancellation;
- its result table cannot be reconciled with the starts and skips recorded earlier in that same log;
- an exit-zero row has no matching non-empty per-example log or its full identity cannot be resolved;
- source files relevant to the requested validation changed after the run;
- the PID file or log evidence indicates that a workflow is still active;
- the available log predates the run or revision the user asked about.

When evidence is missing, stale, incomplete, or still running, stop the analysis and ask the user to run or finish `pnpm examples:workflow:start` manually. Mention optional flags such as `--filter`, `--include-server`, `--include-audio`, or `--include-external` only when they match the user's requested scope. Do not run the command yourself.

## Required analysis

Analyze every entry, not a sample.

- For every exit-zero example, compare its intended flow in source and comments with its log. Confirm the meaningful actions and results occurred, such as expected tool calls, approvals, handoffs, streamed output, generated artifacts, or final messages. Exit code zero alone is not behavioral validation.
- Classify non-zero entries as a repository failure, an expected example-level failure, an external dependency or credential restriction, a host/environment restriction, or incomplete evidence. Quote the concise untruncated log lines that justify the classification.
- Classify every skip by its recorded reason: interactive, server, audio, external service, default auto-skip, conditional missing environment, or runner exclusion. Distinguish an intentional skip from a failure and from an environment restriction.
- Report configured filters and optional modes so the user can see the exact scope that was and was not exercised.

## Output

Begin with whether the completed run is behaviorally valid for its recorded scope. Then provide one concise line per example with its classification and evidence. Include a separate list of failures, intentional skips, and environment restrictions when any exist. For a valid exit-zero entry, name what was checked rather than saying only `passed`.

Do not omit or ellipsize the log lines that establish a conclusion. Keep excerpts short, but include each relevant line in full.

From openai/openai-agents-js at 05241c7, shown as plain text under its license: MIT (permissive). The license text is in LICENSE.

View SKILL.md on GitHub at 05241c7

Files

2 files, 4.9 KB in total. Each file has a sha256 in the pin's manifest; the first 12 characters are shown.

Skill folder on GitHub at 05241c7
All 50 skills from OpenAI

More from OpenAI

  • code-change-verification

    Runs formatting, linting, type checking, and test verification for SDK code changes after review.

    Contains scripts

    Codex · about 1.3K tokens · pinned 7 days ago

  • docs-sync

    This skill audits English SDK documentation by comparing features and configuration options in the codebase against the current docs, then proposes or…

    Claude Code, Codex, Cursor +4 · about 1.2K tokens · pinned 7 days ago

  • examples-run-analysis

    Analyzes logs and artifacts from manual examples runs to validate example behaviors, identify failures, and classify issues.

    Claude Code, Codex, Cursor +4 · about 1K tokens · pinned 7 days ago

  • final-release-review

    Audits Python SDK release candidates or plans against the previous release, comparing diffs for regressions, API changes, and version compatibility.

    Contains scripts

    Claude Code, Codex, Cursor +3 · about 5.4K tokens · pinned 7 days ago

  • implementation-final-review

    This skill guides agents through a structured review process for completed implementation changes before final verification.

    Contains scripts

    Claude Code, Codex, Cursor +3 · about 1.9K tokens · pinned 7 days ago

  • implementation-kickoff

    This skill manages an isolated implementation workflow using a dedicated git worktree, keeping the user's original checkout unchanged while building a…

    Contains scripts

    Codex · about 2.9K tokens · pinned 7 days ago

All Observability skills
  • debugging-executions

    Debug workflow execution failures by inspecting failed nodes, re-running executions, and comparing expected versus actual values.

    by n8nOfficial publisher

    Claude Code, Codex, Cursor +3 · about 2.5K tokens · pinned 7 days ago

  • instance-awareness

    This skill teaches the agent to resolve ambiguous requests by reading the instance's activity log and workflow history instead of asking the user to clarify.

    by n8nOfficial publisher

    Claude Code, Codex, Cursor +3 · about 1.3K tokens · pinned 7 days ago

  • creating-replay-vision-scanners

    Guides agents through creating Replay Vision scanners, LLM probes that watch session recordings on a schedule and log findings as observations.

    by PostHogOfficial publisher

    Claude Code, Codex, Cursor +4 · about 3.3K tokens · pinned 7 days ago

  • exploring-replay-vision-observations

    This skill guides agents through reading observations from Replay Vision scanners, understanding their findings across session recordings, and taking action…

    by PostHogOfficial publisher

    Claude Code, Codex, Cursor +4 · about 3.3K tokens · pinned 7 days ago

  • exploring-scouts

    Explore and understand PostHog Signals scouts through read-only tools, examining fleet configuration, recent runs, performance metrics, and durable team…

    by PostHogOfficial publisher

    Contains scripts

    Claude Code, Codex, Cursor +3 · about 11K tokens · pinned 7 days ago

  • investigating-replay

    Gathers session recording metadata, user profile, event timeline, and linked error issues in parallel to give a complete investigation when a user provides a…

    by PostHogOfficial publisher

    Claude Code, Codex, Cursor +4 · about 2.3K tokens · pinned 7 days ago

Open roles at OpenAI

5 of 239 open roles on the jobs board

The skills listed here are third-party software, collected from public GitHub repositories as a catalog of recent skills and provided as is. Agent Native does not write or control them and is not responsible for any harm, loss or damage caused by installing or using them. Labels and checks describe what we saw at one commit and are not a guarantee. Read a skill's files before you run it. Terms of use