The startup-timeout integration tests in `chatloop` used a 5ms real-time
budget and relied on wall-clock scheduling to fire the startup guard
timer before the first stream part arrived. On loaded CI runners the
timer sometimes lost the race, producing `attempts == 2` instead of
`attempts == 1` and flaking `TestRun_FirstPartDisarmsStartupTimeout`.
Replace the real `time.Timer` in `startupGuard` with a `quartz.Timer` so
tests can control time deterministically. Production behavior is
unchanged: `RunOptions.Clock` defaults to `quartz.NewReal()` when nil,
and the startup timeout still covers both opening the provider stream
and waiting for the first stream part.
- Add `RunOptions.Clock quartz.Clock` with nil-safe default.
- Tag the startup guard timer as `"startupGuard"` for quartz trap
targeting.
- Rewrite the four startup-timeout integration tests to use
`quartz.NewMock(t)` with trap/advance/release sequences instead of
wall-clock sleeps.
- Add `awaitRunResult` helper so tests fail with a clear message instead
of hanging when `Run` does not complete.
Closes https://github.com/coder/internal/issues/1460
Adds an optional `CreatedAt` timestamp to `tool-call` and `tool-result`
`ChatMessagePart` variants so the frontend can compute tool execution
duration (`result.created_at - call.created_at`).
Timestamps are recorded at the correct moments in the chatloop:
- **Tool-call**: when the model stream emits the tool call
- **Tool-result**: when tool execution completes (or is interrupted)
These are passed through `PersistedStep.PartCreatedAt` so the
persistence layer can apply accurate timestamps to stored parts.
SSE-published parts also carry `CreatedAt` for real-time display.
Old persisted messages without `created_at` deserialize to `nil` — fully
backward compatible.
<details><summary>Implementation notes (Coder Agents
generated)</summary>
### Why not stamp in `PartFromContent`?
`PartFromContent` is called both for SSE publishing (correct timing) and
during persistence (wrong timing — both tool-call and tool-result would
get the same "persistence time" timestamp, yielding ~0 duration).
Instead, timestamps are captured in the chatloop at the right moments
and carried through `PersistedStep.PartCreatedAt` as a
`map[string]time.Time` keyed by `"call:<id>"` / `"result:<id>"`.
### Interrupted tool calls
`persistInterruptedStep` also stamps `CreatedAt` on synthetic error
results for cancelled/interrupted tool calls, so partial duration is
available.
### Files changed
| File | Change |
|------|--------|
| `codersdk/chats.go` | Add `CreatedAt *time.Time` field |
| `codersdk/chats_test.go` | JSON round-trip test |
| `coderd/database/dbtime/dbtime.go` | Add `TimePtr` helper |
| `coderd/x/chatd/chatloop/chatloop.go` | Track timestamps, pass through
`PersistedStep` |
| `coderd/x/chatd/chatd.go` | Apply timestamps during persistence |
| `coderd/x/chatd/chatprompt/chatprompt_test.go` | Verify
`PartFromContent` does NOT stamp |
| `site/src/api/typesGenerated.ts` | Auto-generated |
</details>
---------
Co-authored-by: Ethan <39577870+ethanndickson@users.noreply.github.com>
Adds client-executed dynamic tools to the chat API. Dynamic tools are
declared by the client at chat creation time, presented to the LLM
alongside built-in tools, but executed by the client rather than chatd.
This enables external systems (Slack bots, IDE extensions, Discord bots,
CI/CD integrations) to plug custom tools into the LLM chat loop without
modifying chatd's built-in tool set.
Modeled after OpenAI's Assistants API: the chat pauses with
`requires_action` status when the LLM calls a dynamic tool, the client
POSTs results back via `POST /chats/{id}/tool-results`, and the chat
resumes.
See [this example](https://github.com/coder/coder-slackbot-poc) as a
reference for how this is used. It's highly-configurable, which would
enable creating chats from webhooks, periodically polling, or running as
a Slackbot.
<details>
<summary>Design context</summary>
### Architecture
The chatloop **exits** when it encounters dynamic tools and
**re-enters** when results arrive. No blocking channels, no pubsub for
tool results, no in-memory registry. The DB is the only coordination
mechanism.
```
Phase 1 (chatloop):
LLM response → execute built-in tools only →
Persist(assistant + built-in results) →
status = requires_action → chatloop exits
Phase 2 (POST /tool-results):
Persist(dynamic tool results) →
status = pending → wakeCh → chatloop re-enters
```
### Validation (POST /tool-results)
1. Chat status must be `requires_action` (409 if not)
2. Read chat's `dynamic_tools` → set of dynamic tool names
3. Read last assistant message → extract tool-call parts matching
dynamic tool names
4. Submitted tool_call_ids must match exactly (400 for missing/extra)
5. Persist tool-result message parts, set status to `pending`, signal
wake
### Idempotency
Tool call IDs scoped per LLM step. State machine (`requires_action` →
`pending`) is the guard. First POST wins, subsequent get 409.
### Mixed tool calls
When the LLM calls both built-in and dynamic tools in one step, built-in
tools execute immediately. Their results are persisted in phase 1.
Dynamic tool results arrive via POST in phase 2. The LLM sees all
results when the chatloop resumes.
</details>
> 🤖 Generated by Coder Agents
`isContextLimitKey` had a fallback heuristic that matched any key starting with `"max"` containing `"context"`, causing false positives on keys like `"max_context_version"`. A provider returning such metadata would have the value parsed as a context limit.
Replace substring matching on the separator-stripped key with word-level matching. A new `metadataKeyWords` function tokenizes keys by splitting on separators and camelCase boundaries, then the fallback requires
`"context"` paired with a limit-related word (`"limit"`, `"window"` + qualifier, `"length"` + qualifier, or `"tokens"` + qualifier). Known exact forms like `"context_window"` remain in the fast-path switch.
Closes https://github.com/coder/coder/issues/23332
> **PR Stack**
> 1. #23351 ← `#23282`
> 2. #23282 ← `#23275`
> 3. **#23275** ← `#23349` *(you are here)*
> 4. #23349 ← `main`
---
## Summary
Extracts a structured error classification subsystem for agent chat
(`chatd`) so that retry and error payloads carry machine-readable
metadata — error kind, provider name, HTTP status code, and retryability
— instead of raw error strings.
This is the **backend half** of the error-handling work. The frontend
counterpart is in #23282.
## Changes
### New package: `coderd/chatd/chaterror/`
Canonical error classification — extracts error kind, provider, status
code, and user-facing message from raw provider errors. One source of
truth that drives both retry policy and stream payloads.
- **`kind.go`**: Error kind enum (`rate_limit`, `timeout`, `auth`,
`config`, `overloaded`, `unknown`).
- **`signals.go`**: Signal extraction — parses provider name, HTTP
status code, and retryability from error strings and wrapped types.
- **`classify.go`**: Classification logic — maps extracted signals to an
error kind.
- **`message.go`**: User-facing message templates keyed by kind +
signals.
- **`payload.go`**: Projectors that build `ChatStreamError` and
`ChatStreamRetry` payloads from a classified error.
### Modified
- **`codersdk/chats.go`**: Added `Kind`, `Provider`, `Retryable`,
`StatusCode` fields to `ChatStreamError` and `ChatStreamRetry`.
- **`coderd/chatd/chatretry/`**: Thinned to retry-policy only;
classification logic moved to `chaterror`.
- **`coderd/chatd/chatloop/`**: Added per-attempt first-chunk timeout
(60 s) via `guardedStream` wrapper — produces retryable
`startup_timeout` errors instead of hanging forever.
- **`coderd/chatd/chatd.go`**: Publishes normalized retry/error payloads
via `chaterror` projectors.
OpenAI Responses follow-up turns were replaying full assistant/tool
history even when `store=true`, which breaks after reasoning +
provider-executed `web_search` output.
This change persists the OpenAI response ID on assistant messages, then
in `coderd/x/chatd` switches `store=true` follow-ups to
`previous_response_id` chaining with a system + new-user-only prompt.
`store=false` and missing-ID cases still fall back to manual replay.
It also updates the fake OpenAI server and integration coverage for the
chaining contract, and carries the rebased path move to `coderd/x/chatd`
plus the migration renumber needed after rebasing onto `main`.
- Moves `coderd/chatd/`, `coderd/gitsync/`, `enterprise/coderd/chatd/`
under `x/` parent directories to signal instability
- Adds `Experimental:` glue code comments in `coderd/coderd.go`
> 🤖 This PR was created with the help of Coder Agents, and was
reviewed by my human. 🧑💻
Ethan