codex
Run benchmark-selected GPT-5.6 work through the Codex CLI.
Install
npx skills add https://github.com/notque/vexjoy-agent/tree/main/skills/meta/codex
claude plugin marketplace add https://llmmart.ai/marketplace.json && claude plugin install notque-vexjoy-agent@llmmart
git clone https://github.com/notque/vexjoy-agent.git
The skills CLI installs just this skill, for any of its supported agents. Claude Code installs the whole notque/vexjoy-agent collection as a plugin from our marketplace. Git is the plain clone.
Skill manifest
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). 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: /do SKILL.md, Model Selection (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 /do SKILL.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 execvia Bash with a self-contained prompt, or a thin Claude wrapper agent (model: "sonnet", low effort) 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
modelparameter.
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: "sonnet" for mechanical 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:
- Context — one short paragraph: what the repo/data is, what state matters.
- 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.
- 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 sourced from INDEX.local.json 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 task never needs write access and the sandbox makes that deterministic.
Write tasks (clear-spec implementation, migrations): drop -s read-only; run from the target repo's working directory; review the diff (git status --short, git diff) before committing anything.
Reviews: use codex exec review via the pr-workflow codex-review flow (table above), not a hand-rolled prompt.
Gate: exit code 0 AND output matches the requested format. Non-zero exit: report stderr and stop — codex failures are auth/API/prompt-length issues that a blind retry won't fix. Verify the output against a deterministic check where one exists (counts, file lists, test runs) before passing it upstream — GPT-5.6 output is evidence, not verdict. State the model and effort in the result so the caller can apply the escalation rule.
Error handling
codex: command not found
Cause: Codex CLI not installed on this host.
Solution: fall back to the policy's Claude pick (model: "sonnet" for mechanical work) and report which lane ran; install via the owner's codex setup when authorized.
Sandbox error mentioning bwrap / Failed RTM_NEWADDR
Cause: the bwrap sandbox fails in some containerized/VM environments.
Solution: for read-only work, retry without -s read-only only if the environment already provides external sandboxing (Claude Code does); -s read-only and --dangerously-bypass-approvals-and-sandbox are mutually exclusive — use one.
Output missing or truncated in -o file
Cause: prompt exceeded length limits or codex wrote to stdout only. Solution: shorten the prompt (point codex at files instead of embedding content); capture stdout as fallback.
References
/doSKILL.md, Model Selection — canonical policy table and routing decision rules
Files (vexjoy-agent)
-
SKILL.md 7.6 KB
--- 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). 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: `/do` SKILL.md, Model Selection (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 `/do` SKILL.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: "sonnet"`, low effort) 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: "sonnet"` for mechanical 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 sourced from `INDEX.local.json` or other local-only inventories) stay out. Run the deterministic scan on the prompt text before executing: ```bash 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. ```bash 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 task never needs write access and the sandbox makes that deterministic. **Write tasks (clear-spec implementation, migrations):** drop `-s read-only`; run from the target repo's working directory; review the diff (`git status --short`, `git diff`) before committing anything. **Reviews:** use `codex exec review` via the pr-workflow codex-review flow (table above), not a hand-rolled prompt. **Gate**: exit code 0 AND output matches the requested format. Non-zero exit: report stderr and stop — codex failures are auth/API/prompt-length issues that a blind retry won't fix. Verify the output against a deterministic check where one exists (counts, file lists, test runs) before passing it upstream — GPT-5.6 output is evidence, not verdict. State the model and effort in the result so the caller can apply the escalation rule. ## Error handling ### `codex: command not found` Cause: Codex CLI not installed on this host. Solution: fall back to the policy's Claude pick (`model: "sonnet"` for mechanical work) and report which lane ran; install via the owner's codex setup when authorized. ### Sandbox error mentioning bwrap / `Failed RTM_NEWADDR` Cause: the bwrap sandbox fails in some containerized/VM environments. Solution: for read-only work, retry without `-s read-only` only if the environment already provides external sandboxing (Claude Code does); `-s read-only` and `--dangerously-bypass-approvals-and-sandbox` are mutually exclusive — use one. ### Output missing or truncated in `-o` file Cause: prompt exceeded length limits or codex wrote to stdout only. Solution: shorten the prompt (point codex at files instead of embedding content); capture stdout as fallback. ## References - `/do` SKILL.md, Model Selection — canonical policy table and routing decision rules
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