codex-e2e-test

liaohch3 · ТестванеЕзик на описанието

Run PR-grade real Codex E2E validation through claude-tap, including resume turns, multiple tool calls, optional image input, viewer verification, and screenshot evidence.

Оригинален текст · няма потвърден превод на български

Платформи: Не са посочениНиво: Не е посоченоВ индекса: 22.09.2026 г.Обновен в GitHub: 15.09.2026 г.

Теми: agent-debugging · agent-observability · ai-agents · ai-tools · api-debugging · claude-code · codex · codex-cli · cursor-cli · developer-tools · gemini-cli · hermes-agent · kimi · llm · llm-proxy

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Оригинален SKILL.md

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Лиценз: MIT
Последна проверка на записа: 22.09.2026 г.

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Командата отваря избора на skills от репозитория. Прочетете файла и условията на автора преди изпълнение.

npx skills add liaohch3/claude-tap

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Codex E2E Test Skill

Run real end-to-end validation that starts claude-tap from local source, connects to the real Codex CLI via OAuth, captures OpenAI Responses API traces, and produces viewer screenshots suitable for PR evidence.

Use this skill for every PR that changes capture, proxying, viewer rendering, session/dashboard behavior, client launch logic, trace ordering, content blocks, tools, token usage, or screenshot/demo assets. If a PR cannot run this flow, state why in the PR and cover the same risk with another real client trace.

Prerequisites

codex CLI installed (npm install -g @openai/codex) and authenticated via OAuth
Python dev dependencies: uv sync --extra dev
Playwright installed: uv run playwright install chromium

Verify OAuth works:

codex exec "say hello" --dangerously-bypass-approvals-and-sandbox

If it fails with token errors, re-authenticate:

codex auth login

Key Difference from Claude E2E

Codex uses the OpenAI Responses API (/v1/responses) instead of Anthropic Messages API. With OAuth authentication, the upstream is https://chatgpt.com/backend-api/codex, not https://api.openai.com.

The proxy must be told the correct target with --tap-target.

Run a Real Codex E2E Trace

Prefer the resume + multimodal flow below for PR evidence. The simple commands are only smoke tests for checking local setup.

Simple (single tool call)

claude-tap --tap-client codex \
  --tap-target https://chatgpt.com/backend-api/codex \
  --tap-output-dir /tmp/codex-e2e \
  --tap-no-open \
  -- exec "say hello" \
  --dangerously-bypass-approvals-and-sandbox

Multi-call (triggers multiple API requests)

Use a task that requires shell tool use — this forces the agent to make multiple Responses API calls (models lookup + actual responses):

claude-tap --tap-client codex \
  --tap-target https://chatgpt.com/backend-api/codex \
  --tap-output-dir /tmp/codex-e2e \
  --tap-no-open \
  -- exec "Read pyproject.toml and tell me the project name and version" \
  --dangerously-bypass-approvals-and-sandbox

Expected: 4+ API calls (2x GET /v1/models + 2x POST /v1/responses).

Resume + Multimodal Content-Block Trace

Целият SKILL.md в GitHub