## 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>
