Remove the redundant inline compaction request trace and clarify that streamed server-side compaction rebuilds replacement history on response.completed from the checkpoint snapshot.
Co-authored-by: Codex <noreply@openai.com>
- reduce the server-side compaction test matrix to the highest-signal cases
- add comments around the deferred checkpoint rewrite and inline/preflight split
Co-authored-by: Codex <noreply@openai.com>
Handle repeated inline compactions on turns that started from empty history by stripping leading compaction items after prefix calculation, and add regression coverage for the fresh-session case.
Co-authored-by: Codex <noreply@openai.com>
Ignore compact_prompt for OpenAI inline auto-compaction, remove the legacy compat downgrade path, and keep /compact on the point-in-time endpoint. Also skip previous-model preflight remote compaction when inline server-side compaction is available.\n\nCo-authored-by: Codex <noreply@openai.com>
Keep current-turn inputs in local inline compaction checkpoints and remember known backend incompatibilities after a compat downgrade so later turns skip the failed inline request path.
Co-authored-by: Codex <noreply@openai.com>
Keep same-turn ghost snapshots when pre-turn inline compaction downgrades to the legacy client-side path so undo state survives compatibility fallback.
Co-authored-by: Codex <noreply@openai.com>
Move normal auto-compaction onto inline Responses API compaction behind a feature flag, keep the legacy path for manual and compatibility cases, and add observability plus integration coverage.
Co-authored-by: Codex <noreply@openai.com>
- include the requested sub-agent model and reasoning effort in the
spawn begin event\n- render that metadata next to the spawned agent name
and role in the TUI transcript
---------
Co-authored-by: Codex <noreply@openai.com>
Summary
- update the code-mode handler, runner, instructions, and error text to
refer to the `exec` tool name everywhere that used to say `code_mode`
- ensure generated documentation strings and tool specs describe `exec`
and rely on the shared `PUBLIC_TOOL_NAME`
- refresh the suite tests so they invoke `exec` instead of the old name
Testing
- Not run (not requested)
## Summary
- update the guardian prompting
- clarify the guardian rejection message so an action may still proceed
if the user explicitly approves it after being informed of the risk
## Testing
- cargo run on selected examples
## Summary
- add `skill_approval` to `RejectConfig` and the app-server v2
`AskForApproval::Reject` payload so skill-script prompts can be
configured independently from sandbox and rule-based prompts
- update Unix shell escalation to reject prompts based on the actual
decision source, keeping prefix rules tied to `rules`, unmatched command
fallbacks tied to `sandbox_approval`, and skill scripts tied to
`skill_approval`
- regenerate the affected protocol/config schemas and expand
unit/integration coverage for the new flag and skill approval behavior
Pass more params to /compact. This should give us parity with the
/responses endpoint to improve caching.
I'm torn about the MCP await. Blocking will give us parity but it seems
like we explicitly don't block on MCPs. Happy either way
Summary
- document how code-mode can import `output_text`/`output_image` and
ensure `add_content` stays compatible
- add a synthetic `@openai/code_mode` module that appends content items
and validates inputs
- cover the new behavior with integration tests for structured text and
image outputs
Testing
- Not run (not requested)
- clarify the `close_agent` tool description so it nudges models to
close agents they no longer need
- keep the change scoped to the tool spec text only
Co-authored-by: Codex <noreply@openai.com>
Summary
- document that `@openai/code_mode` exposes
`set_max_output_tokens_per_exec_call` and that `code_mode` truncates the
final Rust-side output when the budget is exceeded
- enforce the configured budget in the Rust tool runner, reusing
truncation helpers so text-only outputs follow the unified-exec wrapper
and mixed outputs still fit within the limit
- ensure the new behavior is covered by a code-mode integration test and
string spec update
Testing
- Not run (not requested)
Summary
- drop `McpToolOutput` in favor of `CallToolResult`, moving its helpers
to keep MCP tooling focused on the final result shape
- wire the new schema definitions through code mode, context, handlers,
and spec modules so MCP tools serialize the exact output shape expected
by the model
- extend code mode tests to cover multiple MCP call scenarios and ensure
the serialized data matches the new schema
- refresh JS runner helpers and protocol models alongside the schema
changes
Testing
- Not run (not requested)
- add `model` and `reasoning_effort` to the `spawn_agent` schema so the
values pass through
- validate requested models against `model.model` and only check that
the selected model supports the requested reasoning effort
---------
Co-authored-by: Codex <noreply@openai.com>
## Summary
- add ARC monitor support for MCP tool calls by serializing MCP approval
requests into the ARC action shape and sending the relevant
conversation/policy context to the `/api/codex/safety/arc` endpoint
- route ARC outcomes back into MCP approval flow so `ask-user` falls
back to a user prompt and `steer-model` blocks the tool call, with
guardian/ARC tests covering the new request shape
- update the TUI approval copy from “Approve Once” to “Allow” / “Allow
for this session” and refresh the related
snapshots
---------
Co-authored-by: Fouad Matin <fouad@openai.com>
Co-authored-by: Fouad Matin <169186268+fouad-openai@users.noreply.github.com>
Summary
- document output types for the various tool handlers and registry so
the API exposes richer descriptions
- update unified execution helpers and client tests to align with the
new output metadata
- clean up unused helpers across tool dispatch paths
Testing
- Not run (not requested)
There are some bug investigations that currently require us to ask users
for their user ID even though they've already uploaded logs and session
details via `/feedback`. This frustrates users and increases the time
for diagnosis.
This PR includes the ChatGPT user ID in the metadata uploaded for
`/feedback` (both the TUI and app-server).
