## Description
This PR is a followup to https://github.com/openai/codex/pull/28355 and
starts assigning `internal_chat_message_metadata_passthrough.turn_id` to
durable Responses API items created during a turn.
The goal is that those items keep the `turn_id` that introduced them
when Codex resends stateless HTTP context, reconstructs history for
resume/fork paths, or reuses websocket response state.
## What changed
- Set `internal_chat_message_metadata_passthrough.turn_id` when missing
as response items enter durable history, initial/replacement history,
inter-agent communication history, and local compaction summaries.
- Preserve existing item turn IDs instead of overwriting them during
persistence, resume reconstruction, compaction, forked history, and
websocket incremental reuse.
- Keep `compaction_trigger` fieldless because it is a request control,
not a durable response item.
- Update focused history/request assertions and fixtures for stateless
requests, websocket incrementals, compaction, thread injection, prompt
debug, and related CI coverage.
## Why
We already have the machinery to support multiple environments on a
single thread, but we only show the model the contents of `AGENTS.md`
files in the primary environment.
We should show the model all of the relevant project instructions when
we know there's more than one environment.
## Known Gaps
As discussed in the RFC, this implementation:
1. doesn't handle environments being added/removed to/from the thread
after its creation
2. it doesn't enforce an aggregate context budget across environments,
and instead applies the configured project maximum independently to each
environment
## Implementation
- Discover project instructions in environment order with an independent
byte budget per environment and preserve source provenance/order.
- Keep the legacy fragment byte-for-byte when exactly one environment
contributes project instructions; use environment-labeled sections when
two or more environments contribute.
- Freeze the complete rendered fragment in `LoadedAgentsMd`, insert it
directly into requests, and recognize both layouts in contextual and
memory filtering.
- Add exact rendering, independent-budget, source-order,
creation-snapshot, and consumer coverage without changing app-server
schemas.
## What
Introduce a `CodexResponsesMetadata` struct that defines all the core
metadata we send to Responses API. Example fields are `thread_id`,
`turn_id`, `window_id`, etc.
Going forward, `client_metadata["x-codex-turn-metadata"]` will be the
canonical way Codex sends metadata to Responses API across both HTTP and
websocket transports.
For now, we continue to emit the existing top-level HTTP headers and
top-level `client_metadata` fields from the same
`CodexResponsesMetadata` struct for compatibility reasons.
Also, app-server clients who specify additional
`responsesapi_client_metadata` via `turn/start` and `turn/steer` will
have those fields merged into
`client_metadata["x-codex-turn-metadata"]`, but cannot override the
reserved fields that core uses (i.e. the fields in
`CodexResponsesMetadata`).
## Why
Responses API request instrumentation is the source of truth for
downstream Codex analytics that join requests by Codex IDs such as
session, thread, turn, and context window. Before this change, those
values were assembled through several request-specific paths: HTTP
request bodies, websocket handshake headers, websocket `response.create`
payloads, compaction requests, and the rich `x-codex-turn-metadata`
envelope all had their own wiring.
That made metadata propagation easy to drift across API-key/direct
Responses API requests, ChatGPT-auth/proxied requests, websocket
requests, and compaction requests. It also made additions like
`window_id` error-prone because a field could be added to one transport
projection but missed in another.
## What changed
- Added `CodexResponsesMetadata` as the core-owned snapshot for Codex
metadata sent to ResponsesAPI.
- Render `client_metadata["x-codex-turn-metadata"]`, flat
`client_metadata` projections, and direct compatibility headers from
that same snapshot.
- Include the known Codex-owned fields in the turn metadata blob,
including installation/session/thread/turn/window IDs, request kind,
lineage, sandbox/workspace metadata, timing, and compaction details.
- Treat app-server `responsesapi_client_metadata` as enrichment for the
Codex turn metadata blob while preventing those extras from overriding
Codex-owned fields.
- Use the same metadata path for normal turns, websocket prewarm, local
compaction, remote v1 compaction, and remote v2 compaction.
- Keep websocket connection-only preconnect metadata separate so
handshakes carry compatibility identity headers without inventing a fake
turn metadata blob.
## Verification
- `cargo check -p codex-core`
- `just fix -p codex-core`
## Why
`/responses/compact` should preserve the request-affinity fields that
apply to the active auth mode. ChatGPT-auth compact requests need the
effective `service_tier`, and compact requests for every auth mode need
the stable `prompt_cache_key`, so compaction does not quietly lose
routing or cache behavior that normal sampling already has.
This follows the request-parity direction from #20719, but keeps the net
change focused on the compact payload fields needed here.
## What changed
- Add `service_tier` and `prompt_cache_key` to the compact endpoint
input payload.
- Build the remote compact payload from the existing responses request
builder output so `Fast` still maps to `priority` when compact sends a
service tier.
- Pass the turn service tier into remote compaction, but only include it
in compact payloads for ChatGPT-backed auth.
- Keep `prompt_cache_key` on compact payloads for all auth modes.
- Add request-body diff snapshot coverage in
`core/tests/suite/compact_remote.rs` for:
- API-key auth reusing `prompt_cache_key` while omitting `service_tier`
even when `Fast` is configured.
- ChatGPT auth reusing both `service_tier` and `prompt_cache_key`.
- Drive the snapshot coverage through five varied turns: plain text,
multi-part text, tool-call continuation, image+text input, local-shell
continuation, and final-turn reasoning output.
## Verification
- Added insta snapshots for compact request-body parity against the last
normal `/responses` request after five varied turns.
- Not run locally per repo guidance; relying on GitHub CI for test
execution.
---------
Co-authored-by: Codex <noreply@openai.com>
## Summary
- reuse a guardian subagent session across approvals so reviews keep a
stable prompt cache key and avoid one-shot startup overhead
- clear the guardian child history before each review so prior guardian
decisions do not leak into later approvals
- include the `smart_approvals` -> `guardian_approval` feature flag
rename in the same PR to minimize release latency on a very tight
timeline
- add regression coverage for prompt-cache-key reuse without
prior-review prompt bleed
## Request
- Bug/enhancement request: internal guardian prompt-cache and latency
improvement request
---------
Co-authored-by: Codex <noreply@openai.com>
Move the general `Apps`, `Skills` and `Plugins` instructions blocks out
of `user_instructions` and into the developer message, with new `Apps ->
Skills -> Plugins` order for better clarity.
Also wrap those sections in stable XML-style instruction tags (like
other sections) and update prompt-layout tests/snapshots. This makes the
tests less brittle in snapshot output (we can parse the sections), and
it consolidates the capability instructions in one place.
#### Tests
Updated snapshots, added tests.
`<AGENTS_MD>` disappearing in snapshots is expected: before this change,
the wrapped user-instructions message was kept alive by `Skills`
content. Now that `Skills` and `Plugins` are in the developer message,
that wrapper only appears when there is real
project-doc/user-instructions content.
---------
Co-authored-by: Charley Cunningham <ccunningham@openai.com>
## Summary
- record a realtime close developer message when a new realtime session
replaces an active one
- assert the replacement marker through the mocked responses request
path
---------
Co-authored-by: Codex <noreply@openai.com>
Co-authored-by: Charles Cunningham <ccunningham@openai.com>
## Summary
- bundle contextual prompt injection into at most one developer message
plus one contextual user message in both:
- per-turn settings updates
- initial context insertion
- preserve `<model_switch>` across compaction by rebuilding it through
canonical initial-context injection, instead of relying on
strip/reattach hacks
- centralize contextual user fragment detection in one shared definition
table and reuse it for parsing/compaction logic
- keep `AGENTS.md` in its natural serialized format:
- `# AGENTS.md instructions for {dirname}`
- `<INSTRUCTIONS>...</INSTRUCTIONS>`
- simplify related tests/helpers and accept the expected snapshot/layout
updates from bundled multi-part messages
## Why
The goal is to converge toward a simpler, more intentional prompt shape
where contextual updates are consistently represented as one developer
envelope plus one contextual user envelope, while keeping parsing and
compaction behavior aligned with that representation.
## Notable details
- the temporary `SettingsUpdateEnvelope` wrapper was removed; these
paths now return `Vec<ResponseItem>` directly
- local/remote compaction no longer rely on model-switch strip/restore
helpers
- contextual user detection is now driven by shared fragment definitions
instead of ad hoc matcher assembly
- AGENTS/user instructions are still the same logical context; only the
synthetic `<user_instructions>` wrapper was replaced by the natural
AGENTS text format
## Testing
- `just fmt`
- `cargo test -p codex-app-server
codex_message_processor::tests::extract_conversation_summary_prefers_plain_user_messages
-- --exact`
- `cargo test -p codex-core
compact::tests::collect_user_messages_filters_session_prefix_entries
--lib -- --exact`
- `cargo test -p codex-core --test all
'suite::compact::snapshot_request_shape_pre_turn_compaction_strips_incoming_model_switch'
-- --exact`
- `cargo test -p codex-core --test all
'suite::compact_remote::snapshot_request_shape_remote_pre_turn_compaction_strips_incoming_model_switch'
-- --exact`
- `cargo test -p codex-core --test all
'suite::client::includes_apps_guidance_as_developer_message_when_enabled'
-- --exact`
- `cargo test -p codex-core --test all
'suite::client::includes_developer_instructions_message_in_request' --
--exact`
- `cargo test -p codex-core --test all
'suite::client::includes_user_instructions_message_in_request' --
--exact`
- `cargo test -p codex-core --test all
'suite::client::resume_includes_initial_messages_and_sends_prior_items'
-- --exact`
- `cargo test -p codex-core --test all
'suite::review::review_input_isolated_from_parent_history' -- --exact`
- `cargo test -p codex-exec --test all
'suite::resume::exec_resume_last_respects_cwd_filter_and_all_flag' --
--exact`
- `cargo test -p core_test_support
context_snapshot::tests::full_text_mode_preserves_unredacted_text --
--exact`
## Notes
- I also ran several targeted `compact`, `compact_remote`,
`prompt_caching`, `model_visible_layout`, and `event_mapping` tests
while iterating on prompt-shape changes.
- I have not claimed a clean full-workspace `cargo test` from this
environment because local sandbox/resource conditions have previously
produced unrelated failures in large workspace runs.
This PR keeps compaction context-layout test coverage separate from
runtime compaction behavior changes, so runtime logic review can stay
focused.
## Included
- Adds reusable context snapshot helpers in
`core/tests/common/context_snapshot.rs` for rendering model-visible
request/history shapes.
- Standardizes helper naming for readability:
- `format_request_input_snapshot`
- `format_response_items_snapshot`
- `format_labeled_requests_snapshot`
- `format_labeled_items_snapshot`
- Expands snapshot coverage for both local and remote compaction flows:
- pre-turn auto-compaction
- pre-turn failure/context-window-exceeded paths
- mid-turn continuation compaction
- manual `/compact` with and without prior user turns
- Captures both sides where relevant:
- compaction request shape
- post-compaction history layout shape
- Adds/uses shared request-inspection helpers so assertions target
structured request content instead of ad-hoc JSON string parsing.
- Aligns snapshots/assertions to current behavior and leaves explicit
`TODO(ccunningham)` notes where behavior is known and intentionally
deferred.
## Not Included
- No runtime compaction logic changes.
- No model-visible context/state behavior changes.
Owen Lin ·
Adam Perry @ OpenAI ·
Ahmed Ibrahim ·
Charley Cunningham ·
sayan-oai ·
jif-oai ·