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703793c22e
## Description This makes Codex Apps tool reads use a shared in-memory snapshot instead of rereading the disk cache every time `list_all_tools()` runs. Disk still seeds the cache on startup and gets updated after successful fetches, but it is no longer the live read path. The core change is that `McpManager` now owns a process-scoped `CodexAppsToolsCache`. Codex threads in the same app-server process now share this Codex Apps in-memory tools snapshot. The snapshot is keyed by the Codex home plus the Codex Apps identity: the active Codex auth user/workspace and the effective Codex Apps MCP source config. There's already code to hard-refresh the cache, so we respect it in this PR. ## Local benchmark I ran a local steady-state microbenchmark of the exact repeated Codex Apps cached-tools read this PR removes, using the same real local cache payload in both trees: `3,678,138` bytes and `381` tools. The cache file was already warm in the OS page cache, so this measures same-process reread/deserialization work rather than cold-disk latency or full turn latency. Each run is 25 iterations (mimicking a turn that makes 25 inference calls). | Version | Run 1 | Run 2 | Avg | |---|---:|---:|---:| | `origin/main` disk read + JSON deserialize + `filter_tools` | `50.755 ms` | `52.894 ms` | `51.825 ms` | | This branch in-memory `current_tools` + `filter_tools` | `0.740 ms` | `0.778 ms` | `0.759 ms` | That removes about `51 ms` from each repeated Codex Apps cached-tools read on this machine, roughly `68x` faster for that subpath. It is useful evidence for the hot path this PR changes, but not a claim that every production turn gets `51 ms` faster; end-to-end impact also depends on the rest of `list_all_tools()` and tool-payload construction. This is on my M2 Max macbook, so with a slower disk this would be much worse (and indeed we did see this really blew up turn runtime with a slow disk).
703793c22e
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2026-06-25 20:54:48 +00:00
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