name: codex-readiness-integration-test
description: Run the Codex Readiness integration test. Use when you need an end-to-end agentic loop with build/test scoring.
metadata:
short-description: Run Codex Readiness integration test

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).

Entry Point

• python skills/codex-readiness-integration-test/bin/run_integration_test.py

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

• 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

0) 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.
1) Generate or load prompt.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.
- 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.
2) Execute the agentic loop via Codex CLI (uses AGENTS.md and change_prompt).
3) Run build/test commands from the prompt plan via skills/codex-readiness-integration-test/bin/run_plan.py.
4) Collect evidence (evidence.json), deterministic checks, and run automatic LLM evals via Codex CLI.
5) Score and write the report + summary output.

Configuration

Optional fields in prompt.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.
• The LLM evaluator must check that AGENTS.md was referenced.
• 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 prompt.json.