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 agentmods add agents/dimpagk92/cellar/codexgit clone --depth 1 https://github.com/dimpagk92/cellarWhat 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 | $0.00000 | $0.01342 |
| Opus 5 | $0.00000 | $0.00671 |
| Sonnet 5 | $0.00000 | $0.00268 |
| Haiku 4.5 | $0.00000 | $0.00134 |
Grade A, and why
codex scanned grade A with 0 findings 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 yesterday.
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.
Nothing flagged
None of the 26 patterns this scan looks for appear in this file: no shell pipes, no recursive deletes, no credential paths, no hidden text, no instruction-override or anti-refusal phrasing, no agent-config snooping. That is not a guarantee, it is the absence of the things that are checkable.
How it starts
The opening of the file, as written. The whole thing — 131 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Driving CEL from OpenAI Codex CLI
This page shows how to drive CEL from the OpenAI Codex CLI.
Read docs/adapters-cel-agents.md first if you haven't.
Purpose
Codex CLI is OpenAI's terminal-resident agent. It calls tools, loops, and stops on its own, which is exactly the external-agent pattern CEL is designed for. In this setup:
- Codex owns the loop and tool-calling.
- CEL provides
cel_see,cel_act,cel_perceive,cel_thinkvia MCP stdio. - You normally only need
cel_see+cel_act.
Setup
1. Build CEL
cd /path/to/cellar
pnpm install && pnpm -r build
2. Register CEL with Codex
Codex exposes MCP servers via a config file in the user's home directory.
TODO: verify with latest Codex CLI docs at https://platform.openai.com/docs/codex (or the Codex GitHub repo README) — the exact path and key name have changed between Codex releases. As of the most recent public guidance the config lives under ~/.codex/ and MCP servers follow the standard mcpServers schema shared across MCP clients.
The MCP server block itself is stable:
{
"mcpServers": {
"cel": {
"command": "node",
"args": ["/absolute/path/to/cellar/mcp-server/dist/index.js"]
}
}
}
Or via the CLI entry point:
{
"mcpServers": {
"cel": {
"command": "cellar",
"args": ["mcp"]
}
}
}
3. Verify Codex sees CEL
Start Codex and list tools. The exact command varies by version; check codex --help or codex mcp list in your build.
TODO: verify with upstream docs — Codex version in April 2026 should support listing attached MCP servers. If your version does not, run the MCP Inspector against CEL directly to confirm the server is healthy:
npx @modelcontextprotocol/inspector node /path/to/cellar/mcp-server/dist/index.js
4. Grant macOS Accessibility permission
As with every CEL client, the first cel_act call that performs input requires Accessibility permission for the host process. Grant it in System Settings → Privacy & Security → Accessibility and restart Codex.
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.
- yesterday First seen · 131 lines · 0 tokens per session scan A 1d3e334b1a65
codex is an agent published in the GitHub repository dimpagk92/cellar (4 stars, last pushed 21d ago), licensed Apache-2.0. It costs nothing until one of its globs matches a file; then it loads 1,342 tokens. A static security scan graded it A with 0 findings. No closer match exists in the catalogue, so it is treated as the original; first seen 2026-08-31.
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