/codex

name: codex
description: "Run benchmark-selected GPT-5.6 work through the Codex CLI."
user-invocable: false
compatibility: "Requires codex CLI on PATH; /do supplies the selected GPT-5.6 model and reasoning effort."
routing:
  force_route: true
  triggers:
    - through codex
    - codex exec
    - dispatch to codex
    - run on codex
    - codex analysis
    - gpt-5.6
  pairs_with:
    - data
    - pr-workflow
  complexity: Medium
  category: meta

Codex — the GPT-5.6 Execution Lane

Run a benchmark-selected GPT-5.6 task through the Codex CLI (`codex exec`) and return the result. This is the OpenAI execution lane — the general-purpose lane for work the model-selection policy sends to GPT-5.6, and the **canonical owner of general `codex exec` mechanics** — when the CLI changes, update here first. GPT selections are reachable only through this CLI; the Agent tool's `model` parameter covers Claude models only.

**Under Claude Code, this skill runs only on explicit invocation or cross-provider escalation, never as the automatic default.** The harness-native model lane under Claude Code is the Anthropic lane (Opus 5.5 by default; `/do` Model choice). This skill is a deliberate cross-provider tool — codex review as a second-opinion, codex exec for a GPT-specific constraint — not a routing default.

Two flows keep their own specialized codex integration — route to them instead of re-implementing here:

| Existing flow | Owns | Where | |---|---|---|

Phase 1: DECIDE — does this task belong on GPT-5.6?

Policy mirror — canonical copy: `skills/meta/do/references/model-selection.md` (edit there first, then here). Rankings, higher = better; cost = avg USD per task, written as a plain number (slash-command templating corrupts dollar-digit sequences in injected skill bodies), what the owner actually pays.

| Task class | Model / effort | DeepSWE Pass@1 / cost / output tokens / steps | |---|---|---| | Low-risk assistance | `gpt-5.6-terra` / `high` | 54 / 1.13 / 22k / 34 | | Standard implementation | `gpt-5.6-sol` / `high` | 69 / 3.47 / 28k / 37 | | High-risk implementation or review | `gpt-5.6-sol` / `xhigh` | 71 / 4.70 / 41k / 44 | | Exceptional explicit escalation | `gpt-5.6-sol` / `max` | 73 / 8.39 / 60k / 61 |

Run deterministic work as scripts, not through Codex. The `/do` model policy selects the lane and passes model plus effort. Legacy GPT-5.5, all Luna choices, and the other non-default GPT-5.6 settings are manual-only; do not substitute them automatically. Luna `max`, for example, saves 0.44 USD versus Sol `high` but consumes 45k more output tokens and 65 more steps for two fewer Pass@1 points. Consult the canonical table in `skills/meta/do/references/model-selection.md`.

These are defaults, not limits. Standing permission to escalate when output misses the bar applies within the policy; `max` still needs an explicit override. For anything that ships, intelligence > taste > cost; cost is a tie-breaker only.

**Gate**: task has a GPT-5.6 policy selection. Otherwise route to scripts or the policy's Claude pick and stop here.

Phase 2: WRAP — how GPT-5.6 runs from this harness

**Wrapper symmetry**: the wrapper is needed for whichever model family is NOT the current harness.

• **Under Claude Code** (current default): GPT-5.6 runs through a wrapper — either the dispatched agent runs `codex exec` via Bash with a self-contained prompt, or a thin Claude wrapper agent (`model: "opus"`) writes the self-contained codex prompt, runs it, and returns the result.
• **Under the Codex harness**: Claude models require the wrapper instead.
• Claude models under Claude Code need no wrapper — just the Agent/Workflow `model` parameter.

Pick the direct-Bash form when the calling agent already holds the task context; pick the thin wrapper agent for fan-out (one wrapper per data source) so the orchestrator stays lean.

**Availability check first**: `command -v codex` — when absent, fall back to the policy's Claude pick (`model: "opus"` for code work) and tell the user in one line which lane ran.

Phase 3: PROMPT — write a self-contained prompt

Codex runs in its own process with no conversation history. The prompt must carry everything:

1. **Context** — one short paragraph: what the repo/data is, what state matters. 2. **Task** — the concrete operation, with file paths relative to the working directory. Let codex read files itself; embedding large content wastes tokens and loses formatting. 3. **Output format** — the exact structure to return (table, JSON, diff), so the wrapper can consume it without a second pass.

**Prompt hygiene (hard rule)**: codex prompts leave the machine. Send only public content — secrets, credentials, and private component names (anything from the installed index in `~/.claude/vexjoy/index/`, overlay skills, or other local-only inventories) stay out. Run the deterministic scan on the prompt text before executing:

printf '%s' "$PROMPT" | rg -n "Bearer|Authorization|token|secret|api[_-]?key|password|PRIVATE KEY" && echo "HYGIENE VIOLATION"

On a hit or a private component name: scrub the flagged content when the task survives without it; otherwise reroute the task to a Claude model. A bare refusal is not an outcome.

Phase 4: RUN

Pass the policy-selected model and effort explicitly. Do not rely on a local default that can silently select a deprecated model.

**Investigation / data analysis (default for anything that only reads):**

Set `CODEX_MODEL` and `CODEX_EFFORT` from the `/do` selection before invoking the CLI; do not substitute a local default.

TMPFILE=$(mktemp)
codex exec -m "$CODEX_MODEL" -c "model_reasoning_effort=\"$CODEX_EFFORT\"" -s read-only --skip-git-repo-check -o "$TMPFILE" "$(cat <<'PROMPT'
[self-contained prompt]
PROMPT
)"
cat "$TMPFILE"

`-s read-only` sandboxes the run to reads — verified working on this host. Use it for every investigation or analysis prompt not covered by an existing codex flow, because a read-only t