SKILLS LAUNCH PARTY
skills/openai/skills/codex-readiness-integration-test

codex-readiness-integration-test

SKILL.md

LLM Codex Readiness Integration Test

This skill runs a multi-stage integration test to validate agentic execution quality. It always runs in execute mode (no read-only mode).

Outputs

Each run writes to .codex-readiness-integration-test/<timestamp>/ and updates .codex-readiness-integration-test/latest.json.

New outputs per run:

  • agentic_summary.json and logs/agentic.log (agentic loop execution)
  • llm_results.json (automatic LLM evaluation)
  • summary.txt (human-readable summary)

Pre-conditions (Required)

  • Authenticate with the Codex CLI using the repo-local HOME before running the test. Run these in your own terminal (not via the integration test): HOME=$PWD/.codex-home XDG_CACHE_HOME=$PWD/.codex-home/.cache codex login HOME=$PWD/.codex-home XDG_CACHE_HOME=$PWD/.codex-home/.cache codex login status
  • The integration test creates {repo_root}/.codex-home and {repo_root}/.codex-home/.cache/codex as its first step.

Workflow

  1. Ask the user how to source the task.
    • Offer two explicit options: (a) user provides a custom task/prompt, or (b) auto-generate a task.
    • Do not run the entry point until the user chooses one option.
  2. Generate or load {out_dir}/prompt.pending.json.
    • Use the integration test's expected prompt path, not prompt.json at the repo root.
    • With the default out dir, this path is .codex-readiness-integration-test/prompt.pending.json.
    • If --seed-task is provided, it is used as the starting task.
    • If not provided, generate a task with skills/codex-readiness-integration-test/references/generate_prompt.md and save the JSON to {out_dir}/prompt.pending.json.
    • The user must approve the prompt before execution (no auto-approve mode). Make sure to output a summary of the prompt when asking the user to approve.
  3. Execute the agentic loop via Codex CLI (uses AGENTS.md and change_prompt).
  4. Run build/test commands from the prompt plan via skills/codex-readiness-integration-test/scripts/run_plan.py.
  5. Collect evidence (evidence.json), deterministic checks, and run automatic LLM evals via Codex CLI.
  6. Score and write the report + summary output.

Configuration

Optional fields in {out_dir}/prompt.pending.json:

  • agentic_loop: configure Codex CLI invocation for the agentic loop.
  • llm_eval: configure Codex CLI invocation for automatic evals.

If these fields are omitted, defaults are used.

Requirements

  • The LLM evaluator must fail if evidence mentions the phrase Context compaction enabled.
  • Use qualitative context-usage evaluation (no strict thresholds).

What this test covers well

  • Runs Codex CLI against the real repo root, producing real filesystem edits and git diffs.
  • Executes the approved change prompt and then runs the build/test plan in-repo.
  • Captures evidence, deterministic checks, and LLM eval artifacts for review.

What this test does not represent

  • The agentic loop may use non-default flags (e.g., bypass approvals/sandbox), so interactive guardrails differ.
  • Uses a dedicated HOME (.codex-home), which can change auth/config/cache vs normal CLI use.
  • Auto-generated prompts and one-shot execution do not simulate interactive guidance.
  • MCP servers/tools are not exercised unless explicitly configured.

Notes

  • The prompts in skills/codex-readiness-integration-test/references/ expect strict JSON.
  • Use skills/codex-readiness-integration-test/references/json_fix.md to repair invalid JSON output.
  • This skill calls the codex CLI. Ensure it is installed and available on PATH, or override the command in {out_dir}/prompt.pending.json.
  • If the agentic loop detects sandbox-blocked tool access, it now writes requires_escalation: true to {run_dir}/agentic_summary.json and exits with code 3. Re-run the integration test with escalated permissions in that case.
Weekly Installs
71
Repository
openai/skills
First Seen
Jan 23, 2026
Installed on
claude-code57
opencode57
codex55
gemini-cli50
antigravity47
cursor46