Dismiss stale TUI app-server approvals after remote resolution
When an approval, user-input prompt, or elicitation request is resolved
by another client, the TUI now dismisses the matching local UI instead
of leaving stale prompts behind and emitting a misleading local
cancellation.
This change teaches pending app-server request tracking to map
`serverRequest/resolved` notifications back to the concrete request type
and stable request key, then propagates that resolved request into TUI
prompt state. Approval, request-user-input, and MCP elicitation overlays
now drop the resolved current or queued request quietly, advance to the
next queued request when present, and avoid emitting abort/cancel events
for stale UI.
The latest update also retires matching prompts while they are still
deferred behind active streaming and suppresses buffered active-thread
requests whose app-server request id has already been resolved before
drain. `ChatWidget` removes a resolved request from both the deferred
interrupt queue and the materialized bottom-pane stack, while
active-thread request handling verifies the app-server request is still
pending before showing a prompt. Lifecycle events such as exec begin/end
remain queued so approved work can still render normally.
Tests cover resolved-request mapping, overlay dismissal behavior,
deferred prompt pruning for same-turn user input, exec approval IDs,
lifecycle-event retention, and the buffered active-thread ordering
regression.
Validation:
- `just fmt`
- `git diff --check`
- `cargo test -p codex-tui
resolved_buffered_approval_does_not_become_actionable_after_drain`
- `cargo test -p codex-tui
enqueue_primary_thread_session_replays_buffered_approval_after_attach`
- `cargo test -p codex-tui chatwidget::interrupts`
- `just fix -p codex-tui`
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Co-authored-by: Codex <noreply@openai.com>
This updates the `skill-creator` sample skill to explicitly cover
forward-testing as part of the skill authoring workflow. The guidance
now treats subagent-based validation as a first-class step for complex
or fragile skills, with an emphasis on preserving evaluation integrity
and avoiding leaked context.
The sample initialization script is also updated so newly created skills
point authors toward forward-testing after validation. Together, these
changes make the sample more opinionated about how skills should be
iterated on once the initial implementation is complete.
- Add new guidance to `SKILL.md` on protecting validation integrity,
when to use subagents for forward-testing, and how to structure
realistic test prompts without leaking expected answers.
- Expand the skill creation workflow so iteration explicitly includes
forward-testing for complex skills, including approval guidance for
expensive or risky validation runs.
