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## Why Executor skill discovery runs before the remote skills catalog is available. For a remote environment, each `ExecutorFileSystem` operation becomes an exec-server RPC. Previously, every discovered `SKILL.md` independently resolved its plugin namespace by walking its ancestors and probing both supported manifest locations. In the common `plugin/skills/<skill>/SKILL.md` layout, that repeats 8 RPCs per skill even though every skill under the plugin root uses the same namespace. These lookups happen while skills are parsed, so their cost grows linearly with the skill count and adds directly to first-turn latency. A selected capability root can also contain standalone skills, multiple sibling plugins, nested plugins, or symlinked directories. The optimization therefore needs to retain the nearest-ancestor namespace for each skill rather than assuming the selected root represents exactly one plugin. ## What changed - record plugin-root candidates from directory entries already returned during skill discovery - prune candidates that are not ancestors of any discovered `SKILL.md` before reading manifests - resolve each relevant plugin root once, with one fallback lookup per canonical traversal root for symlinked directories - select the nearest cached plugin namespace for each discovered skill - avoid namespace lookup entirely when the root contains no skills No additional directory traversal is required. Namespace work now scales with the number of plugin roots that contain discovered skills, rather than the total number of skills or unrelated sibling plugins. Standalone and nested-plugin names keep their previous behavior. ## Benchmarks I used a temporary counting `ExecutorFileSystem` around the real local filesystem. Each filesystem operation was counted as one remote RPC and given 1 ms of injected latency. Each variant ran three times; times below are medians. ### One plugin with 100 skills | Operation | Before | After | Delta | | --- | ---: | ---: | ---: | | `get_metadata` | 1,002 | 303 | -699 | | `read_file` | 200 | 101 | -99 | | `read_directory` | 102 | 102 | 0 | | **Total filesystem RPCs** | **1,304** | **506** | **-798 (-61.2%)** | | **Median load time** | **2.890 s** | **0.997 s** | **2.90× faster** | The namespace-specific work drops from 800 RPCs to 2 in this layout. ### Multiple plugins under one selected root These runs compare the correct pre-optimization implementation with the final nearest-plugin-root cache. The total plugin skill count stays at 100 while the number of plugin roots changes. | Layout | Before RPCs | After RPCs | Reduction | Before | After | Speedup | | --- | ---: | ---: | ---: | ---: | ---: | ---: | | 2 plugins × 50 skills | 1,312 | 530 | 59.6% | 1,819 ms | 711 ms | 2.56× | | 10 plugins × 10 skills | 1,344 | 578 | 57.0% | 1,850 ms | 778 ms | 2.38× | | 50 plugins × 2 skills | 1,504 | 818 | 45.6% | 2,094 ms | 1,086 ms | 1.93× | | 10 plugins × 10 skills + 10 standalone skills | 1,596 | 630 | 60.5% | 2,209 ms | 860 ms | 2.57× | The remaining cost grows with the number of relevant plugin manifests. Each relevant manifest is read once instead of once per skill, while sibling plugins with no discovered skills are not read. Absolute latency savings depend on the executor's real RPC latency. ## Tests - `just test -p codex-core-skills` (109 passed across the library and integration-test binaries) - one integration test covers standalone, outer-plugin, nested-plugin, and unused sibling-plugin layouts, and asserts the exact set of manifests read
390b73133b
·
2026-06-24 17:14:34 +01:00
7,796 Commits
Codex CLI is a coding agent from OpenAI that runs locally on your computer.
If you want Codex in your code editor (VS Code, Cursor, Windsurf), install in your IDE.
If you want the desktop app experience, run
codex app or visit the Codex App page.
If you are looking for the cloud-based agent from OpenAI, Codex Web, go to chatgpt.com/codex.
Quickstart
Installing and running Codex CLI
Run the following on Mac or Linux to install Codex CLI:
curl -fsSL https://chatgpt.com/codex/install.sh | sh
Run the following on Windows to install Codex CLI:
powershell -ExecutionPolicy ByPass -c "irm https://chatgpt.com/codex/install.ps1 | iex"
Codex CLI can also be installed via the following package managers:
# Install using npm
npm install -g @openai/codex
# Install using Homebrew
brew install --cask codex
Then simply run codex to get started.
You can also go to the latest GitHub Release and download the appropriate binary for your platform.
Each GitHub Release contains many executables, but in practice, you likely want one of these:
- macOS
- Apple Silicon/arm64:
codex-aarch64-apple-darwin.tar.gz - x86_64 (older Mac hardware):
codex-x86_64-apple-darwin.tar.gz
- Apple Silicon/arm64:
- Linux
- x86_64:
codex-x86_64-unknown-linux-musl.tar.gz - arm64:
codex-aarch64-unknown-linux-musl.tar.gz
- x86_64:
Each archive contains a single entry with the platform baked into the name (e.g., codex-x86_64-unknown-linux-musl), so you likely want to rename it to codex after extracting it.
Using Codex with your ChatGPT plan
Run codex and select Sign in with ChatGPT. We recommend signing into your ChatGPT account to use Codex as part of your Plus, Pro, Business, Edu, or Enterprise plan. Learn more about what's included in your ChatGPT plan.
You can also use Codex with an API key, but this requires additional setup.
Docs
This repository is licensed under the Apache-2.0 License.