## Why
This bug is exposed by Guardian/auto-review approvals. With the managed
network proxy enabled, a blocked network request can be reported back
through the network approval service as an approval denial after the
command has already started. Before this change, the shell and unified
exec runtimes registered those network approval calls, but did not have
a way to observe an async proxy denial as a cancellation/failure signal
for the running process.
The result was confusing: Guardian/auto-review could correctly deny
network access, but the command path could keep running or unregister
the approval without surfacing the denial as the command failure.
## What Changed
- `NetworkApprovalService` now attaches a cancellation token to active
and deferred network approvals.
- Proxy-denial outcomes are recorded only for active registrations,
cancel the owning token, and are consumed when the approval is
finalized.
- The shell runtime combines the normal command timeout with the
network-denial cancellation token.
- Unified exec stores the deferred network approval object, terminates
tracked processes when the proxy denial arrives, and returns the denial
as a process failure while polling or completing the process.
- Tool orchestration passes the active network approval cancellation
token into the sandbox attempt and preserves deferred approval errors
instead of silently unregistering them.
- App-server `command/exec` now handles the combined
timeout-or-cancellation expiration variant used by the runtime.
## Verification
- `cargo test -p codex-core network_approval --lib`
- `cargo clippy -p codex-app-server --all-targets -- -D warnings`
- `cargo clippy -p codex-core --all-targets -- -D warnings`
---------
Co-authored-by: Codex <noreply@openai.com>
Summary:
- Add codex-thread-manager-sample, a one-shot binary that starts a
ThreadManager thread, submits a prompt, and prints the final assistant
output.
- Pass ThreadStore into ThreadManager::new and expose
thread_store_from_config for existing callsites.
- Build the sample Config directly with only --model and prompt inputs.
Verification:
- just fmt
- cargo check -p codex-thread-manager-sample -p codex-app-server -p
codex-mcp-server
- git diff --check
Tests: Not run per request.
## Why
Memory startup runs in the background after an eligible turn, but it can
consume Codex backend quota at exactly the wrong time: when the user is
already near a rate-limit boundary. This PR adds a guard so the memory
pipeline backs off when the Codex rate-limit snapshot says the remaining
budget is too low.
## What Changed
- Added `memories.min_rate_limit_remaining_percent` with a default of
`25`, clamped to `0..=100`, and regenerated `core/config.schema.json`.
- Added `codex-rs/memories/write/src/guard.rs`, which fetches Codex
backend rate limits before memory startup and skips phase 1 / phase 2
when the Codex limit is reached or either tracked window is above the
configured usage ceiling.
- Keeps startup best-effort: non-Codex auth or rate-limit fetch/client
failures preserve the existing memory startup behavior.
- Records a `codex.memory.startup` counter with
`status=skipped_rate_limit` when startup is skipped.
- Added config parsing/clamping coverage and guard unit tests.
## Verification
- Added `codex-rs/memories/write/src/guard_tests.rs` for threshold,
primary/secondary window, and reached-limit behavior.
- Added config tests for TOML parsing and clamping.
## Why
Memory startup was tied to thread lifecycle events such as create, load,
and fork. That can run memory work before a thread receives real user
input, and it makes startup cost scale with thread management instead of
actual turns. Moving the trigger to `thread/sendInput` keeps memory
startup aligned with the first real user turn and lets it use the
current thread config at turn time.
The idea is to prevent ghost cost due to pre-warm triggered by the app
Turn-based startup can also make global phase-2 consolidation easier to
request repeatedly, so this adds a success cooldown and tightens the
default startup scan window.
## What Changed
- Start `codex_memories_write::start_memories_startup_task` after a
non-empty `thread/sendInput` turn is submitted, instead of from thread
create/load/fork paths:
d4a6885b78/codex-rs/app-server/src/codex_message_processor.rs (L6477-L6487)
- Expose `CodexThread::config()` so app-server can pass the live config
into memory startup at turn time.
- Add a six-hour successful-run cooldown for global phase-2
consolidation via `SkippedCooldown`:
d4a6885b78/codex-rs/state/src/runtime/memories.rs (L963-L966)
- Reduce memory startup defaults to at most 2 rollouts over 10 days:
d4a6885b78/codex-rs/config/src/types.rs (L31-L34)
## Verification
Updated the memory runtime coverage around phase-2 reclaim behavior,
including `phase2_global_lock_respects_success_cooldown`.
---------
Co-authored-by: Codex <noreply@openai.com>
## Why
Phase 2 still needs to choose the most relevant stage-1 memory outputs
by usage and recency, but exposing that ranking as the rendered
`raw_memories.md` order creates unnecessary large diff. Usage-count or
timestamp changes can reshuffle otherwise unchanged memories, making the
workspace diff noisy and giving the consolidation prompt a misleading
recency signal from file position.
This fix will reduce token consumption
## What Changed
- Keep the existing top-N Phase 2 selection ranking by `usage_count`,
`last_usage`, `source_updated_at`, and `thread_id`.
- Return the selected rows in stable ascending `thread_id` order before
syncing Phase 2 filesystem inputs.
- Update the memory README, raw memories header, and consolidation
prompt so they describe the stable order and tell the prompt to use
metadata and workspace diffs instead of file order as the recency
signal.
- Adjust the memory runtime tests to use deterministic thread IDs and
assert the stable return order separately from the ranked selection
semantics.
## Test Coverage
- Existing memory runtime tests in
`codex-rs/state/src/runtime/memories.rs` now cover the stable returned
ordering for Phase 2 inputs.
---------
Co-authored-by: Codex <noreply@openai.com>
Keep extracting memories out of core and moving the write trigger in the
app-server
This is temporary and it should move at the client level as a follow-up
This makes core fully independant from `codex-memories-write`
---------
Co-authored-by: Codex <noreply@openai.com>
