Getting it into your agent
One page per mod, every tool's command on it. A separate URL per tool would split the same page into five that compete with each other.
npx skills add southlab-ai/Claude-Plugin-Marketplace --skill codex-agentgit clone --depth 1 https://github.com/southlab-ai/Claude-Plugin-MarketplaceWrote this? Show the measurements
A badge with what this costs and how it scanned, read live from this page, so it follows the numbers instead of freezing them. Markdown for a README, HTML for a documentation site or a project page.
[](https://agentmods.dev/skills/southlab-ai/claude-plugin-marketplace/codex-agent)<a href="https://agentmods.dev/skills/southlab-ai/claude-plugin-marketplace/codex-agent"><img src="https://agentmods.dev/badge/skills/southlab-ai/claude-plugin-marketplace/codex-agent/github.svg" alt="Measured on agentmods" height="20"></a>Or the 80×15 button, for a site that already has a row of RSS and ATOM ones. Only the verdict fits; the numbers stay here.
<a href="https://agentmods.dev/skills/southlab-ai/claude-plugin-marketplace/codex-agent"><img src="https://agentmods.dev/badge/skills/southlab-ai/claude-plugin-marketplace/codex-agent.svg" alt="Reviewed on agentmods" width="80" height="20"></a>What it costs to keep this loaded
Counted locally with the o200k_base tokenizer, which is exact for GPT models; Claude uses its own tokenizer and its counts differ. Treat this as one consistent yardstick across the catalogue rather than a bill. Prices are per million input tokens.
| Model | Per session | Once invoked |
|---|---|---|
| Fable 5.1 | $0.00086 | $0.01356 |
| Opus 5 | $0.00043 | $0.00678 |
| Sonnet 5 | $0.00017 | $0.00271 |
| Haiku 4.5 | $0.00009 | $0.00136 |
Grade B, and why
codex-agent scanned grade B with 1 finding against 26 rules in 11 categories — prompt injection, anti-refusal, data exfiltration, privilege escalation, supply chain, agent snooping, system-prompt leakage, SSRF and excessive agency — measured 10d ago.
A static scan of the body, not an audit. Every finding is printed with the line that produced it so you can judge whether it matters here. A mod is markdown that instructs an agent; that is exactly why what it instructs is worth reading.
Reads agent configuration directoriesmediumAgent snooping
.claude/, .codex/, .gemini/ hold keys, settings and other credentials a mod has no legitimate need for.
Spawn non-interactive Codex CLI agents using `codex exec`. Requires the OpenAI Codex CLI installed and authenticated (`codex login`; auth stored in `~/.codex/auth.json`). **Always pin model and reasoning effort explicitl How it starts
The opening of the file, as written. The whole thing — 98 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Codex Agent Spawner
Spawn non-interactive Codex CLI agents using codex exec. Requires the OpenAI Codex CLI installed and authenticated (codex login; auth stored in ~/.codex/auth.json). Always pin model and reasoning effort explicitly — don't rely on ~/.codex/config.toml defaults (they drift).
Model: gpt-5.6-sol by default for a single agent (flagship — a lone second opinion should be the strong one). Use gpt-5.6-terra for routine well-scoped subtasks, gpt-5.6-luna for mechanical extraction/classification. Legacy gpt-5.5 only if the user names it. For fleets, the [[ultracodex]] skill has its own per-role table.
Reasoning effort: medium by default. Raise to high/xhigh only when the user asks (e.g. "xhigh", "a fondo", "máximo esfuerzo") or the subtask is genuinely hard (subtle debugging, architecture, security analysis); max (new in 5.6) for a single hardest problem. Valid values on 5.6: low | medium | high | xhigh | max (minimal is gone).
Base command
codex exec \
-m gpt-5.6-sol \
-c model_reasoning_effort=medium \
-C "<workdir>" \
-s workspace-write \
-o "<rundir>/last-message.md" \
"<PROMPT>"
Run it with the Bash tool and run_in_background: true. The harness notifies you when it exits — do NOT poll or sleep. For long prompts, pipe via stdin (codex exec ... - with a heredoc) instead of an argv string.
Per-run output directory
Before spawning, create a run dir and capture everything there:
RUNDIR="/tmp/codex-agents/<slug>" # slug: short task name, add -2, -3 if it exists
mkdir -p "$RUNDIR"
-o "$RUNDIR/last-message.md"— final answer (this is what you report back to the user).- Append
--json > "$RUNDIR/events.jsonl"only if the user wants a full trace; otherwise plain stdout (captured by the background task) is enough to monitor progress. - The session id appears in the output header (
session id: <uuid>) — note it so the agent can be resumed.
Flag decisions
What this file has done since we first saw it
Hashed on every crawl. A supply-chain change to an agent config is a question of when, not whether, so the history is kept rather than the latest state alone.
- 10d ago First seen · 98 lines · 86 tokens per session scan B 84317c989bab
codex-agent is a skill published in the GitHub repository southlab-ai/Claude-Plugin-Marketplace (2 stars, last pushed 1mo ago), licensed MIT. It adds 86 tokens to every session and 1,356 once invoked, about $0.0004 per session on Opus 5. A static security scan graded it B with 1 finding (reads agent configuration directories). No closer match exists in the catalogue, so it is treated as the original; first seen 2026-08-31.
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