Fixes#23897 (docs link only — naming rename is in #23905)
- Fix version stripping logic in both Go (`codersdk/deployment.go`) and
TypeScript (`site/src/utils/docs.ts`) to preserve `-rc.X` suffixes
instead of amputating them along with `-devel`
- Add `v0.0.0` fallback in the TS frontend to match Go backend behavior
for dev builds
- Add tests covering RC, devel, and plain release version strings
> 🤖 Written by a Coder Agent. Will be reviewed by a human.
## Description
Adds support for multiple Copilot provider instances to route requests to different Copilot upstreams (individual, business, enterprise). Each instance has its own name and base URL, enabling per-upstream metrics, logs, circuit breakers, API dump, and routing.
## Changes
* Add Copilot business and enterprise provider names and host constants
* Register three Copilot provider instances in aibridged (default, business, enterprise)
* Update `defaultAIBridgeProvider` in `aibridgeproxy` to route new Copilot hosts to their corresponding providers
## Related
* Depends on: https://github.com/coder/aibridge/pull/240
* Closes: https://github.com/coder/aibridge/issues/152
Note: documentation changes will be added in a follow-up PR.
_Disclaimer: initially produced by Claude Opus 4.6, heavily modified and reviewed by @ssncferreira ._
- Add `chat-access` built-in role granting chat CRUD at User scope
- Exclude `ResourceChat` from member, org member, and org service
account `allPermsExcept` calls
- Allow system, owner, and user-admin to assign the new role
- Migration auto-assigns role to users who have ever created a chat
- Update RBAC test matrix: `memberMe` denied, `chatAccessUser` allowed
**Breaking change**: Members without `chat-access` lose chat creation
ability. Migration covers existing chat creators. Members who have never
created a chat do not get this role automatically applied.
> 🤖 This PR was created by a Coder Agent and reviewed by me.
Adds a nullable JSONB column `last_injected_context` to the `chats`
table that stores the most recently persisted injected context parts
(AGENTS.md context-file and skill message parts). The column is updated
only when `persistInstructionFiles()` runs — on first workspace attach
or when the agent changes — so there are no redundant writes on
subsequent turns.
Internal fields (`ContextFileContent`, `ContextFileOS`,
`ContextFileDirectory`, `SkillDir`) are stripped at write time so the
column only holds small metadata. No stripping needed on the read path.
<details>
<summary>Implementation notes</summary>
- New migration `000456` adds nullable `last_injected_context JSONB`
column.
- New SQL query `UpdateChatLastInjectedContext` writes the column
without touching `updated_at`.
- `persistInstructionFiles()` strips internal fields from parts via
`StripInternal()` before persisting.
- Sentinel path (no AGENTS.md) persists skill-only parts when skills
exist.
- `codersdk.Chat` exposes `LastInjectedContext []ChatMessagePart`
(omitempty).
- `db2sdk.Chat()` passes through the already-clean data.
</details>
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relates to GRU-18
Adds support for agent updates to the Tunneler
## Summary
Skills are now discovered once on the first turn (or when the workspace
agent changes) and persisted as `skill` message parts alongside
`context-file` parts. On subsequent turns, the skill index is
reconstructed from persisted parts instead of re-dialing the workspace
agent.
This makes skills consistent with the AGENTS.md pattern and is
groundwork for a future `/context` endpoint that surfaces loaded
workspace context to the frontend.
## Changes
- Add `skill` `ChatMessagePartType` with `SkillName` and
`SkillDescription` fields
- Extend `persistInstructionFiles` to also discover and persist skills
as parts
- Add `skillsFromParts()` to reconstruct skill index from persisted
parts on subsequent turns
- Update `runChat()` to use `skillsFromParts` instead of re-dialing
workspace for skills
- Frontend: handle new `skill` part type (skip rendering, hide
metadata-only messages)
## Before / After
| | AGENTS.md | Skills |
|---|---|---|
| **Before** | Persist as `context-file` parts, reconstruct from parts |
In-memory `skillsCache` only, re-dial workspace on cache miss |
| **After** | Persist as `context-file` parts, reconstruct from parts |
Persist as `skill` parts, reconstruct from parts |
The in-memory `skillsCache` remains for `read_skill`/`read_skill_file`
tool calls that need full skill bodies on demand.
<details><summary>Design context</summary>
This is the first step toward a unified workspace context
representation. Currently:
- Context files are persisted as message parts (works)
- Skills were only in-memory (inconsistent)
- Workspace MCP servers are cached in-memory (future work)
Persisting skills as parts means a future `/context` endpoint can query
both context files and skills from the same message parts in the DB,
without depending on ephemeral server-side caches.
</details>
Closes#22136
This pull-request implements a `<ClientFilter />` to our `Request Logs`
page for AI Bridge. This will allow the user to select a client which
they wish to filter against. Technically the backend is able to actually
filter against multiple clients at once however the frontend doesn't
currently have a nice way of supporting this (future improvement).
<img width="1447" height="831" alt="image"
src="https://github.com/user-attachments/assets/0be234e2-25f2-4a89-b971-d74817395da1"
/>
---------
Co-authored-by: Jeremy Ruppel <jeremy.ruppel@gmail.com>
Co-authored-by: Claude Sonnet 4.6 <noreply@anthropic.com>
## Summary
Adds read/unread tracking for chats so users can see which agent
conversations have new assistant messages they haven't viewed.
## Backend Changes
- Adds `last_read_message_id` column to the `chats` table (migration
000439).
- Computes `has_unread` as a virtual column in `GetChatsByOwnerID` using
an `EXISTS` subquery checking for assistant messages beyond the read
cursor.
- Exposes `has_unread` on the `codersdk.Chat` struct and auto-generated
TypeScript types.
- Updates `last_read_message_id` on stream connect/disconnect in
`streamChat`, avoiding per-message API calls during active streaming.
- Uses `context.WithoutCancel` for the deferred disconnect write so the
DB update succeeds even after the client disconnects.
## Frontend Changes
- Bold title (`font-semibold`) for unread chats in the sidebar.
- Small blue dot indicator next to the relative timestamp.
- Suppresses unread indicator for the currently active chat via
`isActive` from NavLink.
## Design Decisions
- Only `assistant` messages count as unread — the user's own messages
don't trigger the indicator.
- No foreign key on `last_read_message_id` since messages can be deleted
(via rollback/truncation) and the column is just a high-water mark.
- Zero API calls during streaming: exactly 2 DB writes per stream
session (connect + disconnect).
- Unread state refreshes on chat list load and window focus. The
`watchChats` WebSocket optimistically marks non-active chats as unread
on `status_change` events, but does not carry a server-computed
`has_unread` field. Navigating to a chat optimistically clears its
unread indicator in the cache.
Add a per-MCP-server `model_intent` toggle that wraps tool schemas with
a
`model_intent` field, requiring the LLM to provide a human-readable
description of each tool call's purpose. The intent string is shown as a
status label in the UI instead of opaque tool names, and is
transparently
stripped before the call reaches the remote MCP server.
Built-in tools have rich specialized renderers (terminal blocks, file
diffs,
etc.) and don't need this. MCP tools hit `GenericToolRenderer` which
only
shows raw tool names and JSON — that's where model_intent adds value.
The model learns what to provide via the JSON Schema `description` on
the
`model_intent` property itself — no system prompt changes needed.
<details>
<summary>Implementation details</summary>
### Architecture
Inspired by the `withModelIntent()` pattern from `coder/blink`, adapted
for
Go + React. The wrapping is entirely in the `mcpclient` layer — tool
implementations never see `model_intent`.
**Schema wrapping** (`mcpToolWrapper.Info()`): When enabled, wraps the
original tool parameters under a `properties` key and adds a
`model_intent`
string field with a rich description that teaches the model inline.
**Input unwrapping** (`mcpToolWrapper.Run()`): Strips `model_intent` and
unwraps `properties` before forwarding to the remote MCP server. Handles
three input shapes models may produce:
1. `{ model_intent, properties: {...} }` — correct format
2. `{ model_intent, key: val, ... }` — flat, no wrapper
3. Malformed — falls through gracefully
**Frontend extraction**: `streamState.ts` extracts `model_intent` from
incrementally parsed streaming JSON. `messageParsing.ts` extracts it
from
persisted tool call args.
**UI rendering**: `GenericToolRenderer` shows the capitalized intent
string
as the primary label when available, falling back to the raw tool name.
### Changes
- Database: `model_intent` boolean column on `mcp_server_configs`
- SDK: `ModelIntent` field on config/create/update types
- API: pass-through in create/update handlers + converter
- mcpclient: schema wrapping in `Info()`, input unwrapping in `Run()`
- Frontend: extraction from streaming + persisted args
- UI: intent label in `GenericToolRenderer`, toggle in admin panel
- Tests: 6 new tests (schema wrapping, unwrapping, passthrough,
fallback)
### Decision log
- **Option lives on MCPServerConfig, not model config**: Built-in tools
already have rich renderers; only MCP tools benefit from model_intent.
- **No system prompt changes**: The JSON Schema `description` on the
`model_intent` property teaches the model inline.
- **Pointer bool on update request**: Follows existing pattern (`*bool`)
so PATCH requests don't reset the value when omitted.
</details>
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before submitting.
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Adds the Tunneler state machine and logic for handling build updates.
This is a partial implementation and tests. Further PRs will fill out
the other event types.
Relates to GRU-18
## Summary
Add site-wide banners for AI Governance seat usage thresholds:
1. **90% capacity warning (admin-only):** When actual AI Governance
seats are ≥90% and <100% of the license limit, admins see:
> "You have used 90% of your AI governance add-on seats."
2. **Over-limit banner (admin-only):** When actual seats exceed the
license limit, admins see a prominent warning:
> "Your organization is using {actual} / {limit} AI Governance user
seats ({X}% over the limit). Contact sales@coder.com"
- Uses floor whole percentage (Go int division / `Math.floor`)
- Includes a clickable `mailto:sales@coder.com` link
## Summary
Adds a "Generate new title" action that lets users manually regenerate a
chat's title using richer conversation context than the automatic
first-message title path.
## Changes
### Backend
- **New endpoint:** `POST
/api/experimental/chats/{chatID}/title/regenerate` returns the updated
Chat with a regenerated title
- **Manual title algorithm:** Extracts useful user/assistant text turns
→ selects first user turn + last 3 turns → builds context with gap
markers → renders prompt with anti-recency guidance → calls lightweight
model → normalizes output
- **Helpers:** `extractManualTitleTurns`,
`selectManualTitleTurnIndexes`, `buildManualTitleContext`,
`renderManualTitlePrompt`, `generateManualTitle` — all private, with the
public `Server.RegenerateChatTitle` method
- **SDK:** `ExperimentalClient.RegenerateChatTitle(ctx, chatID) (Chat,
error)`
- Persists title via existing `UpdateChatByID` and broadcasts
`ChatEventKindTitleChange`
### Frontend
- API client method + React Query mutation with cache invalidation
- "Generate new title" menu item (with wand icon) in both TopBar and
Sidebar dropdown menus
- Loading/disabled state while regeneration is in-flight
- Error toast on failure
- Stories updated for both menus
### Tests
- `quickgen_test.go`: Table-driven tests for all 4 helper functions
(turn extraction, index selection, context building, prompt rendering)
- `exp_chats_test.go`: Handler tests (ChatNotFound,
NotFoundForDifferentUser, NoDaemon)
## Design notes
- The existing auto-title path (`maybeGenerateChatTitle`, `titleInput`)
is completely unchanged
- Manual regeneration uses richer context (first user turn + last 3
turns + gap markers) vs the auto path's single first message
- Endpoint is experimental and marked with `@x-apidocgen {"skip": true}`
https://github.com/user-attachments/assets/bd5d12a1-61b3-4b7d-83b6-317bdfb60b3c
## Summary
Adds pinned chats to the agents page sidebar with server-side
persistence and drag-to-reorder. Users can pin/unpin chats via the
context menu, and pinned chats appear in a dedicated "Pinned" section
above the time-grouped list.
## Database
Migration `000453_chat_pin_order`: adds `pin_order integer DEFAULT 0 NOT
NULL` column on `chats` (0 = unpinned, 1+ = pinned in display order).
Three SQL queries handle pin operations server-side using CTEs with
`ROW_NUMBER()`:
- `PinChatByID`: normalizes existing orders and appends to end
- `UnpinChatByID`: sets target to 0 and compacts remaining pins
- `UpdateChatPinOrder`: shifts neighbors, clamps to `[1, pinned_count]`
All queries exclude archived chats. `ArchiveChatByID` clears `pin_order`
on archive. The handler rejects pinning archived chats with 400.
## Backend
Pin/unpin/reorder go through the existing `PATCH
/api/experimental/chats/{chat}` via the `pin_order` field on
`UpdateChatRequest`. The handler routes based on current pin state:
`pin_order == 0` unpins, `> 0` on an already-pinned chat reorders, `> 0`
on an unpinned chat appends to end.
## Frontend
- `pinChat` / `unpinChat` / `reorderPinnedChat` optimistic mutations
using shared `isChatListQuery` predicate
- Sidebar renders Pinned section above time groups, excludes pinned
chats from time groups
- Pin/Unpin context menu items (hidden for child/delegated chats)
- `@dnd-kit/core` + `@dnd-kit/sortable` for drag-to-reorder with
`MouseSensor`, `TouchSensor`, and `KeyboardSensor`
- Local pin-order override prevents flash on drop; click blocker
prevents NavLink navigation after drag
---
*PR generated with Coder Agents*
Coder's chat (chatd) can now discover and use MCP servers configured in
a workspace's `.mcp.json` file. This brings project-specific tooling
(GitHub, databases, docs servers, etc.) into the chat without any manual
configuration.
## How it works
The workspace agent reads `.mcp.json` from the workspace directory (same
format Claude Code uses), connects to the declared MCP servers —
spawning child processes for stdio servers and connecting over the
network for HTTP/SSE — and caches their tool lists. Two new agent HTTP
endpoints expose this:
- `GET /api/v0/mcp/tools` returns the cached tool list (supports
`?refresh=true`)
- `POST /api/v0/mcp/call-tool` proxies calls to the correct server
On each chat turn, chatd calls `ListMCPTools` through the existing
`AgentConn` tailnet connection, wraps each tool as a
`fantasy.AgentTool`, and adds them to the LLM's tool set alongside
built-in and admin-configured MCP tools. Tool names are prefixed with
the server name (`github__create_issue`) to avoid collisions.
Failed server connections are logged and skipped — they never block the
agent or break the chat. Child stdio processes are terminated on agent
shutdown.
*Problem:* `publishChatPubsubEvent` was constructing a partial
`codersdk.Chat` that omitted `LastModelConfigID` and other fields. Go's
zero-value UUID caused the sidebar to show "Default model" for chats
received via SSE.
*Solution:*
- Extracted `convertChat`/`convertChats` from `exp_chats.go` into
`db2sdk.Chat`/`db2sdk.Chats`, alongside existing `ChatMessage`,
`ChatQueuedMessage`, and `ChatDiffStatus` converters.
`publishChatPubsubEvent` now calls `db2sdk.Chat(chat, nil)` instead of
maintaining its own copy of the conversion logic
- Added backend integration test
`TestWatchChats/CreatedEventIncludesAllChatFields`
- Added frontend regression tests for nil-UUID and valid model config ID
cases
> 🤖 Created by Coder Agents, reviewed by this human.
Admins can now control whether the built-in Coder Agents default system
prompt is prepended to their custom instructions, rather than having the
custom prompt silently replace the default.
**Changes:**
- New `include_default_system_prompt` boolean toggle (defaults to `true`
for existing deployments) stored as a site config key — no migration
needed.
- GET `/api/experimental/chats/config/system-prompt` returns the toggle
state, the custom prompt, and a preview of the built-in default.
- PUT persists both the toggle and custom prompt atomically in a single
transaction.
- `resolvedChatSystemPrompt()` composes `[default?, custom?]` joined by
`\n\n`, falling back to the built-in default on DB errors.
- Settings UI adds a Switch toggle with conditional helper text and a
"Preview" button that shows the built-in default prompt via the existing
`TextPreviewDialog`.
- Comprehensive test coverage: 15 subtests covering toggle behavior,
prompt composition matrix, auth boundaries, and integration with chat
creation.
- Adds `GET /api/experimental/chats/by-workspace` endpoint that returns
workspace_id → latest chat_id mapping
- Modifies FE to fetch this alongside the workspace list, gated on
`agents` experiment and render an "Agent" badge similar to the existing
"Task" badge in `WorkspacesTable`
- Badge links to the "latest chat" linked to the given workspace.
Notes:
- Intentionally uses `fetchWithPostFilter` for RBAC to decouple from
workspaces API — will migrate to `workspaces_expanded` view later.
- If users have multiple chats linked to the same workspace, the badge
will link to the most recently updated one.
> 🤖 This PR was created with the help of Coder Agents, and has been
reviewed by my human. 🧑💻
## Summary
Adds an entitlement-gated **AI add-on** column to both the **Users**
table and the **Organization Members** table. When
`ai_governance_user_limit` is entitled, each row shows whether the user
is consuming an AI seat.
## Background
The AI governance add-on tracks which users are consuming AI seats.
Admins need visibility into per-user seat consumption directly from the
user management tables. This change surfaces that information through
both the site-wide Users table and the per-organization Members table,
gated behind the `ai_governance_user_limit` entitlement so the column
only appears when the feature is licensed.
## Implementation
### Backend
- **New SQL query** `GetUserAISeatStates`
(`coderd/database/queries/aiseatstate.sql`) — returns user IDs consuming
an AI seat, derived from:
- Users with entries in `aibridge_interceptions` (AI Bridge usage)
- Users who own workspaces with `has_ai_task = true` builds (AI Tasks
usage)
- **SDK types** — added `has_ai_seat: boolean` to `codersdk.User` and
`codersdk.OrganizationMemberWithUserData`
- **Handler wiring** — both the Users list endpoint (`coderd/users.go`)
and all Members endpoints (`coderd/members.go`) query AI seat state per
page of user IDs and populate the response field
- **dbauthz** — per-user `ActionRead` checks on `ResourceUserObject`
### Frontend
- **Shared `AISeatCell` component**
(`site/src/modules/users/AISeatCell.tsx`) — green `CircleCheck` for
consuming, gray `X` for non-consuming
- **`TableColumnHelpTooltip`** — extended with `ai_addon` variant with
tooltip: *"Users with access to AI features like AI Bridge, Boundary, or
Tasks who are actively consuming a seat."*
- **Column visibility** gated behind
`useFeatureVisibility().ai_governance_user_limit`
## Validation
- Backend: dbauthz full method suite (`TestMethodTestSuite`) passes
including new `GetUserAISeatStates` test
- Backend: `TestGetUsers`, `TestUsersFilter`, CLI golden file tests pass
- Frontend: 7/7 tests pass across `UsersPage.test.tsx` and
`OrganizationMembersPage.test.tsx` (column visibility gating both
directions)
- `go build ./coderd/...` compiles clean
- `pnpm --dir site run lint:types` passes
- `make gen` clean
## Risks
- **Pagination performance**: The AI seat query is scoped to the current
page's user IDs (not a full table scan), keeping it efficient for
paginated views.
- **Semantic scope**: The workspace-side AI seat derivation uses "any
build with `has_ai_task = true`" rather than "latest build only". If the
product intent is latest-build-only, this can be tightened in a
follow-up.
---
_Generated with `mux` • Model: `anthropic:claude-opus-4-6` • Thinking:
`xhigh` • Cost: `$27.25`_
<!-- mux-attribution: model=anthropic:claude-opus-4-6 thinking=xhigh
costs=27.25 -->
## Summary
This change removes the steady-state "resolve the latest workspace
agent" query from chat execution.
Instead of asking the database for the latest build's agent on every
turn, a chat now persists the workspace/build/agent binding it actually
uses and reuses that binding across subsequent turns. The common path
becomes "load the bound agent by ID and dial it", with fallback paths to
repair the binding when it is missing, stale, or intentionally changed.
## What changes
- add `workspace_id`, `build_id`, and `agent_id` binding fields to
`chats`
- expose those fields through the chat API / SDK so the execution
context is explicit
- load the persisted binding first in chatd, instead of always resolving
the latest build's agent
- persist a refreshed binding when chatd has to re-resolve the workspace
agent
- keep child / subagent chats on the same bound workspace context by
inheriting the parent binding
- leave `build_id` / `agent_id` unset for flows like `create_workspace`,
then bind them lazily on the next agent-backed turn
## Runtime behavior
The binding is treated as an optimistic cache of the agent a chat should
use:
- if the bound agent still exists and dials successfully, we use it
without a latest-build lookup
- if the bound agent is missing or no longer reachable, chatd
re-resolves against the latest build and persists the new binding
- if a workspace mutation changes the chat's target workspace, the
binding is updated as part of that mutation
To avoid reintroducing a hot-path query, dialing uses lazy validation:
- start dialing the cached agent immediately
- only validate against the latest build if the dial is still pending
after a short delay
- if validation finds a different agent, cancel the stale dial, switch
to the current agent, and persist the repaired binding
## Result
The hot path stops issuing
`GetWorkspaceAgentsInLatestBuildByWorkspaceID` for every user message,
which is the source of the DB pressure this PR is addressing. At the
same time, chats still converge to the correct workspace agent when the
binding becomes stale due to rebuilds or explicit workspace changes.
## Summary
Adds a general-purpose `map[string]string` label system to chats, stored
as jsonb with a GIN index for efficient containment queries.
This is a standalone foundational feature that will be used by the
upcoming Automations feature for session identity (matching webhook
events to existing chats), replacing the need for bespoke session-key
tables.
## Changes
### Database
- **Migration 000451**: Adds `labels jsonb NOT NULL DEFAULT '{}'` column
to `chats` table with a GIN index (`idx_chats_labels`)
- **`InsertChat`**: Accepts labels on creation via `COALESCE(@labels,
'{}')`
- **`UpdateChatByID`**: Supports partial update —
`COALESCE(sqlc.narg('labels'), labels)` preserves existing labels when
NULL is passed
- **`GetChats`**: New `has_labels` filter using PostgreSQL `@>`
containment operator
- **`GetAuthorizedChats`**: Synced with generated `GetChats` (new column
scan + query param)
### API
- **Create chat** (`POST /chats`): Accepts optional `labels` field,
validated before creation
- **Update chat** (`PATCH /chats/{chat}`): Supports `labels` field for
atomic label replacement
- **List chats** (`GET /chats`): Supports `?label=key:value` query
parameters (multiple are AND-ed)
### SDK
- `Chat`, `CreateChatRequest`, `UpdateChatRequest`, `ListChatsOptions`
all gain `Labels` fields
- `UpdateChatRequest.Labels` is a pointer (`*map[string]string`) so
`nil` means "don't change" vs empty map means "clear all"
### Validation (`coderd/httpapi/labels.go`)
- Max 50 labels per chat
- Key: 1–64 chars, must match `[a-zA-Z0-9][a-zA-Z0-9._/-]*` (supports
namespaced keys like `github.repo`, `automation/pr-number`)
- Value: 1–256 chars
- 13 test cases covering all edge cases
### Chat runtime
- `chatd.CreateOptions` gains `Labels` field, threaded through to
`InsertChat`
- Existing `UpdateChatByID` callers (e.g., quickgen title updates) are
unaffected — NULL labels preserve existing values via COALESCE
We had a bug where computer use base64-encoded screenshots would not be
interpreted as screenshots anymore once saved to the db, loaded back
into memory, and sent to Anthropic. Instead, they would be interpreted
as regular text. Once a computer use agent made enough screenshots and
stopped, and you tried sending it another message, you'd get an out of
context error:
<img width="808" height="367" alt="Screenshot 2026-03-23 at 12 02 54"
src="https://github.com/user-attachments/assets/f0bf6be2-4863-47ca-a7a9-9e6d9dfceeed"
/>
This PR fixes that.
## Summary
Introduces a new `context-file` ChatMessagePart type for persisting
workspace instruction files (AGENTS.md) as durable, frontend-visible
message parts. This is the foundation for showing loaded context files
in the chat input's context indicator tooltip.
### Problem
Previously, instruction files were resolved transiently on every turn
via `resolveInstructions()` → `InsertSystem()` and injected into the
in-memory prompt without persistence. The frontend had no knowledge that
instruction files were loaded into context, and there was no way to
surface this information to users.
### Solution
Instruction files are now read **once** when a workspace is first
attached to a chat (matching how [openai/codex handles
it](https://developers.openai.com/codex/guides/agents-md)) and persisted
as `user`-role, `both`-visibility message parts with a new
`context-file` type. This ensures:
- **Durability**: survives page refresh (data is in the DB, returned by
`getChatMessages`)
- **Cache-friendly**: `user`-role avoids the system-message hoisting
that providers do, keeping the instruction content in a stable position
for prompt caching
- **Frontend-visible**: the frontend receives paths and truncation
status for future context indicator rendering
- **Extensible**: the same pattern works for Skills (future)
### Key changes
| Layer | Change |
|---|---|
| **SDK** (`codersdk/chats.go`) | Add `ChatMessagePartTypeContextFile`
with `context_file_path`, `context_file_content` (internal, stripped
from API), `context_file_truncated` fields |
| **Prompt expansion** (`chatprompt`) | Expand `context-file` parts to
`<workspace-context>` text blocks in `partsToMessageParts()` |
| **Chat engine** (`chatd.go`) | Add `persistInstructionFiles()`, called
on first turn with a workspace. Remove per-turn `resolveInstructions()`
+ `InsertSystem()` from `processChat()` and `ReloadMessages` |
| **Frontend** | Ignore `context-file` parts in `messageParsing.ts` and
`streamState.ts` (no rendering yet — follow-up will add tooltip display)
|
### How it works
1. On each turn, `processChat` checks if any loaded message contains
`context-file` parts
2. If not (first turn with a workspace), reads AGENTS.md files via the
workspace agent connection and persists them
3. For this first turn, also injects the instruction text into the
prompt (since messages were loaded before persistence)
4. On all subsequent turns, `ConvertMessagesWithFiles()` encounters the
persisted `context-file` parts and expands them into text automatically
— no extra resolution needed
- Stores a deployment-wide agents template allowlist in `site_configs`
(`agents_template_allowlist`)
- Adds `GET/PUT /api/experimental/chats/config/template-allowlist`
endpoints
- Filters `list_templates`, `read_template`, and `create_workspace` chat
tools by allowlist, if defined (empty=all allowed)
- Add "Templates" admin settings tab in Agents UI ([what it looks
like](https://624de63c6aacee003aa84340-sitjilsyrr.chromatic.com/?path=/story/pages-agentspage-agentsettingspageview--template-allowlist))
> 🤖 This PR was created with the help of Coder Agents, and has been
reviewed by my human. 🧑💻
> **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.
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_Disclaimer:_ _initially_ _produced_ _by_ _Claude_ _Opus_ _4\.6,_ _heavily_ _modified_ _and_ _reviewed_ _by_ _me._
Closes https://github.com/coder/internal/issues/1360
Adds a new `/api/v2/aibridge/sessions` API which returns "sessions".
Sessions, as defined in the [RFC](https://www.notion.so/coderhq/AI-Bridge-Sessions-Threads-2ccd579be59280f28021d3baf7472fbe?source=copy_link), are a set of interceptions logically grouped by a session key issued by the client.
The API design for this endpoint was done in [this doc](https://github.com/coder/internal/issues/1360).
If the client has not provided a session ID, we will revert to the thread root ID, and if that's not present we use the interception's own ID (i.e. a session of a single interception - which is effectively what we show currently in our `/api/v2/aibridge/interceptions` API).
The SQL query looks gnarly but it's relatively simple, and seems to perform well (~200ms) even when I import dogfood's `aibridge_*` tables into my workspace. If we need to improve performance on this later we can investigate materialized views, perhaps, but for now I don't think it's warranted.
---
_The PR looks large but it's got a lot of generated code; the actual changes aren't huge._
## What
Adds per-user per-model auto-compaction threshold overrides. Users can
now customize the percentage of context window usage that triggers chat
compaction, independently for each enabled model.
## Why
The compaction threshold was previously only configurable at the
deployment level (`chat_model_configs.compression_threshold`). Different
users have different preferences — some want aggressive compaction to
keep costs low, others prefer higher thresholds to retain more context.
This gives users control without requiring admin intervention.
## Architecture
**Storage:** Reuses the existing `user_configs` table (no migration
needed). Overrides are stored as key/value pairs with keys shaped
`chat_compaction_threshold:<modelConfigID>` and integer percent values.
**API:** Three new experimental endpoints under
`/api/experimental/chats/config/`:
- `GET /user-compaction-thresholds` — list all overrides for the current
user
- `PUT /user-compaction-thresholds/{modelConfig}` — upsert an override
(validates model exists and is enabled, validates 0–100 range)
- `DELETE /user-compaction-thresholds/{modelConfig}` — clear an override
(idempotent)
**Runtime resolution:** In `coderd/chatd/chatd.go`, a new
`resolveUserCompactionThreshold()` helper runs at the start of each chat
turn (inside `runChat()`), after the model config is resolved but before
`CompactionOptions` is built. If a valid override exists, it replaces
`modelConfig.CompressionThreshold`. The threshold source
(`user_override` vs `model_default`) is logged with each compaction
event.
**Precedence:** `effectiveThreshold = userOverride ??
modelConfig.CompressionThreshold`
**UI:** New "Context Compaction" subsection in the Agents → Settings →
Behavior tab, placed after Personal Instructions. Shows one row per
enabled model with the system default, a number input for the override,
and Save/Reset controls.
## Testing
- 9 API subtests covering CRUD, validation (boundary values 0/100,
out-of-range rejection), upsert behavior, idempotent delete, user
isolation, and non-existent model config
- 4 dbauthz tests (16 scenarios) verifying `ActionReadPersonal` /
`ActionUpdatePersonal` on all query methods
- 4 Storybook stories with play functions (Default, WithOverrides,
Loading, Error)
<details>
<summary>Implementation plan</summary>
### Phase 1 — Tests
- Backend API tests in `coderd/chats_test.go` (9 subtests)
- Database auth wrapper tests in
`coderd/database/dbauthz/dbauthz_test.go` (4 methods)
- Frontend stories in `UserCompactionThresholdSettings.stories.tsx` (4
stories)
### Phase 2 — Backend preference surface
- 4 SQL queries in `coderd/database/queries/users.sql` (list, get,
upsert, delete)
- `make gen` to propagate into generated artifacts
- Auth/metrics wrappers in dbauthz and dbmetrics
- SDK types and client methods in `codersdk/chats.go`
- HTTP handlers and routes in `coderd/chats.go` and `coderd/coderd.go`
- Key prefix constant shared between handlers and runtime
### Phase 3 — Runtime override
- `resolveUserCompactionThreshold()` helper in `coderd/chatd/chatd.go`
- Override injection in `runChat()` before building `CompactionOptions`
- `threshold_source` field added to compaction log
### Phase 4 — Settings UI
- API client methods and React Query hooks in `site/src/api/`
- `UserCompactionThresholdSettings` component extracted from
`SettingsPageContent`
- Per-model mutation tracking (only the active row disables during save)
- 100% warning, "System default" label, helpful empty state copy
### Phase 5 — Refactor and review fixes
- Consolidated key prefix constant in `codersdk`
- Explicit PUT range validation (not just struct tags)
- GET handler gracefully skips malformed rows instead of 500
- Boundary value, upsert, and non-existent model config tests
- UX improvements: per-model mutation state, aria-live on errors
</details>
- Changes all 41 chat method receivers in `codersdk/chats.go` from
`*Client` to `*ExperimentalClient` to ensure that callers are aware that
these reference potentially unstable `/api/experimental` endpoints.
> 🤖 This PR was created with the help of Coder Agents, and has been
reviewed by my human. 🧑💻
This PR changes agents desktop resolution from 1366x768 to 1920x1080.
Anthropic requires the that the resolution of desktop screenshots fits
in 1,150,000 total pixels, so we downscale screenshots to 1280x720
before sending them to the LLM provider.
Resolution scaling was already implemented, but our code didn't exercise
it. The resolution bump showed that there were some bugs in the scaling
logic - this PR fixes these bugs too.
Continuation of https://github.com/coder/coder/pull/23067
Add filtering to the paginated org member endpoint (pretty much the same
as what I did in the previous PR with group members, except there I also
had to add pagination since it was missing).
Partially addresses #21813 (still need to make changes to the "add user"
button to be complete)
Since there are a lot of user tests already, I moved them into
`coderdtest` to be shared.
- Add `agents_workspace_ttl` site config (default: whatever the template
says a.k.a. `0s`)
- Expose via GET/PUT `/api/experimental/chats/config/workspace-ttl`
- Chat tool reads setting and passes `TTLMillis` on workspace creation
- Existing autostop infrastructure handles the rest (zero changes to
LifecycleExecutor, CalculateAutostop, or activity bumping)
- ⚠️ Template-level `UserAutostopEnabled=false` overrides this global
default. Not touching this.
- Frontend: "Workspace Lifetime" control in /agents/settings Behavior
tab (admin-only)
> This PR was created with the help of Coder Agents, and has been
reviewed by several humans and robots. 🤖🤝🧑💻
Replace the 200ms polling loop in chatd's execute and
process_output tools with server-side blocking via sync.Cond
on HeadTailBuffer.
The agent's GET /{id}/output endpoint accepts ?wait=true to
block until the process exits or a 5-minute server cap expires.
The process_output tool blocks by default for 10s (overridable
via wait_timeout), and falls back to a non-blocking snapshot on
timeout. The execute tool's foreground path makes a single
blocking call instead of polling.
Related #23316
## Description
Blocks `CONNECT` tunnels to private and reserved IP ranges in
aibridgeproxyd, preventing the proxy from being used to reach internal
networks.
The Coder access URL is always exempt (hostname+port match) so the proxy
can reach its own deployment. It is possible to exempt additional ranges
via `CODER_AIBRIDGE_PROXY_ALLOWED_PRIVATE_CIDRS`.
DNS rebinding is handled differently per path:
* Direct (no upstream proxy): validate the resolved IP right before the
TCP dial, no window between check and connect.
* Upstream proxy: Resolves and checks before forwarding to the upstream
dialer. A small rebinding window exists since the upstream proxy
re-resolves independently.
## Changes
* Add blocked IP denylist covering private, reserved, and
special-purpose ranges
* Add `AllowedPrivateCIDRs` option with CLI flag and env var
* Wire IP checks into `proxy.ConnectDial` for both upstream and direct
paths
* Add tests for blocked/allowed cases across direct dial, upstream
proxy, CIDR exemptions, and CoderAccessURL exemption
Notes: documentation will be handled in a follow-up PR.
Closes: https://github.com/coder/security/issues/124
## Summary
Adds the database schema, API endpoints, SDK types, and encryption
wrappers for admin-managed MCP (Model Context Protocol) server
configurations that chatd can consume. This is the backend foundation
for allowing external MCP tools (Sentry, Linear, GitHub, etc.) to be
used during AI chat sessions.
## Database
Two new tables:
- **`mcp_server_configs`**: Admin-managed server definitions with URL,
transport (Streamable HTTP / SSE), auth config (none / OAuth2 / API key
/ custom headers), tool allow/deny lists, and an availability policy
(`force_on` / `default_on` / `default_off`). Includes CHECK constraints
on transport, auth_type, and availability values.
- **`mcp_server_user_tokens`**: Per-user OAuth2 tokens for servers
requiring individual authentication. Cascades on user/config deletion.
New column on `chats` table:
- **`mcp_server_ids UUID[]`**: Per-chat MCP server selection, following
the same pattern as `model_config_id` — passed at chat creation,
changeable per-message with nil-means-no-change semantics.
## API Endpoints
All routes are under `/api/experimental/mcp/servers/` and gated behind
the `agents` experiment.
**Admin endpoints** (`ResourceDeploymentConfig` auth):
- `POST /` — Create MCP server config
- `PATCH /{id}` — Update MCP server config (full-replace)
- `DELETE /{id}` — Delete MCP server config
**Authenticated endpoints** (all users, enabled servers only for
non-admins):
- `GET /` — List configs (admins see all, members see enabled-only with
admin fields redacted)
- `GET /{id}` — Get config by ID (with `auth_connected` populated
per-user)
**OAuth2 per-user auth flow:**
- `GET /{id}/oauth2/connect` — Initiate OAuth2 flow (state cookie CSRF
protection)
- `GET /{id}/oauth2/callback` — Handle OAuth2 callback, store tokens
- `DELETE /{id}/oauth2/disconnect` — Remove stored OAuth2 tokens
## Security
- **Secrets never returned**: `OAuth2ClientSecret`, `APIKeyValue`, and
`CustomHeaders` are never in API responses — only boolean indicators
(`has_oauth2_secret`, `has_api_key`, `has_custom_headers`).
- **Field redaction for non-admins**: `convertMCPServerConfigRedacted`
strips `OAuth2ClientID`, auth URLs, scopes, and `APIKeyHeader` from
non-admin responses.
- **dbcrypt encryption at rest**: All 5 secret fields use `dbcrypt_keys`
encryption with full encrypt-on-write / decrypt-on-read wrappers (11
dbcrypt method overrides + 2 helpers), following the same pattern as
`chat_providers.api_key`.
- **OAuth2 CSRF protection**: State parameter stored in `HttpOnly`
cookie with `HTTPCookies.Apply()` for correct `Secure`/`SameSite` behind
TLS-terminating proxies.
- **dbauthz authorization**: All 18 querier methods have authorization
wrappers. Read operations use `ActionRead`, write operations use
`ActionUpdate` on `ResourceDeploymentConfig`.
## Governance Model
| Control | Implementation |
|---------|---------------|
| **Global kill switch** | `enabled` defaults to `false` |
| **Availability policy** | `force_on` (always injected), `default_on`
(pre-selected), `default_off` (opt-in) |
| **Per-chat selection** | `mcp_server_ids` on `CreateChatRequest` /
`CreateChatMessageRequest` |
| **Auth gate** | OAuth2 servers require per-user auth before tools are
injected |
| **Tool-level allow/deny** | Arrays on `mcp_server_configs` for
granular tool filtering |
| **Secrets encrypted at rest** | Uses `dbcrypt_keys` (same pattern as
`chat_providers.api_key`) |
## Tests
8 test functions covering:
- Full CRUD lifecycle (create, list, update, delete)
- Non-admin visibility filtering (enabled-only, field redaction)
- `auth_connected` population for OAuth2 vs non-OAuth2 servers
- Availability policy validation (valid values + invalid rejection)
- Unique slug enforcement (409 Conflict)
- OAuth2 disconnect idempotency
- Chat creation with `mcp_server_ids` persistence
## Known Limitations (Deferred)
These are documented and intentional for an experimental feature:
- **Audit logging** not yet wired — will add when feature stabilizes
- **Cross-field validation** (e.g., OAuth2 fields required when
`auth_type=oauth2`) — admin-only endpoint, will add when stabilizing
- **`force_on` auto-injection** — query exists but not yet wired into
chatd tool injection (follow-up)
- **Additional test coverage** — 403 auth tests, GET-by-ID tests,
callback CSRF tests planned for follow-up
## What's NOT in this PR
- Frontend UI (admin panel + chat picker)
- Actual MCP client connections (`chatd/chatmcp/` manager)
- Tool injection into `chatloop/`
Updates the `charm.land/fantasy` replace to the rebased `cj/go1.25`
branch on `kylecarbs/fantasy`, which now includes:
- **chore: downgrade to Go 1.25**
- **feat: anthropic computer use**
- **chore: use kylecarbs/openai-go fork for coder/coder compat**
Switches the `openai-go/v3` replace from `SasSwart/openai-go` →
`kylecarbs/openai-go`, which is the same SasSwart perf fork plus a fix
for `WithJSONSet` being clobbered by deferred body serialization.
Without the fix, `NewStreaming` silently drops `stream: true` from
requests. See https://github.com/kylecarbs/openai-go/pull/2 for details.
- Adds a new API endpoint `GET /api/v2/users/oidc-claims` that returns
only the **merged claims** (not the separate id_token/userinfo
breakdown). Scoped exclusively to the authenticated user's own identity
— no user parameter, so users cannot view each other's claims.
- Adds a new CLI command:** `coder users oidc-claims` that hits the
above endpoint.
- The existing owner-only debug endpoint is preserved unchanged for
admins who need the full claim breakdown.
> 🤖 This PR was created with the help of Coder Agents, and will be
reviewed by my human. 🧑💻
ChatMessagePart uses a flat struct with omitempty on all fields,
but some fields are required in their TypeScript variant (no ?
suffix in the variants struct tag). When Go omits a zero-valued
required field, the frontend receives undefined where it expects
a concrete value.
Remove omitempty from fields that are required in at least one
variant: Text, URL, MediaType, FileName, StartLine, EndLine,
Content. Fields where all variants use ? keep omitempty.
Add a sub-test to TestChatMessagePartVariantTags that enforces
this invariant via reflection so future additions cannot
reintroduce the mismatch.
Supersedes #23249
Go serializes ChatMessagePart.Text with omitempty, so empty
reasoning text (from reasoning_start with no delta) is omitted
from JSON. The frontend receives {type: "reasoning"} with text
as undefined, crashing on .trim() calls.
Mark Text as optional in the reasoning variant via the variants
struct tag. This generates ChatReasoningPart with text?: string
and the frontend falls back to "" via nullish coalescing.
Closes#23245
## What
Adds a new admin-only **PR Insights** page for the `/agents` analytics
view — a dashboard for engineering leaders to understand code shipped by
AI agents.
### Backend
- `GET /api/v2/chats/insights/pull-requests` — admin-only endpoint
- 4 SQL queries in `chatinsights.sql` aggregating `chat_diff_statuses`
joined with chat cost data (via root chat tree rollup)
- Runs 5 parallel DB queries: current summary, previous summary (for
trends), time series, per-model breakdown, recent PRs
- SDK types auto-generate to TypeScript
### Frontend (`PRInsightsView`)
- **Stat cards**: PRs created, Merged, Merge rate, Lines shipped,
Cost/merged PR — with trend badges comparing to previous period
- **Activity chart**: Stacked area chart (created/merged/closed) using
git color tokens (`git-added-bright`, `git-merged-bright`,
`git-deleted-bright`)
- **Model performance table**: Per-model PR counts, inline merge rate
bars, diff stats, cost breakdown
- **Recent PRs table**: Status badges, review state icons, author info,
external links
- **Time range filter**: 7d/14d/30d/90d button group
- **4 Storybook stories**: Default, HighPerformance, LowVolume, NoPRs
### Data source
All PR data comes from the existing `chat_diff_statuses` table
(populated by the `gitsync.Worker` background job that polls GitHub
every 120s). No new data collection required.
### Screenshot
View in Storybook: `pages/AgentsPage/PRInsightsView`
## Summary
- add a hidden deployment config option for chat acquire batch size
(`CODER_CHAT_ACQUIRE_BATCH_SIZE` / `chat.acquireBatchSize`)
- thread the configured value into chatd startup while preserving the
existing default of `10`
- clamp the deployment value to the `int32` range before passing it into
chatd
- regenerate the API/docs/types/testdata artifacts for the new config
field
## Why
`chatd` currently acquires pending chats in batches of `10` via a
compile-time default. This change makes that batch size
operator-configurable from deployment config, so we can tune acquisition
behavior without another code change.
Both message parsers accepted untyped input and relied on scattered
asRecord/asString calls to extract fields at runtime. With the
discriminated ChatMessagePart union, both accept typed input directly
and narrow via switch (part.type).
parseMessageContent narrows from (content: unknown) to
(content: readonly ChatMessagePart[] | undefined), removing legacy
input shape handling the Go backend normalizes away.
applyMessagePartToStreamState narrows from Record<string, unknown>
to ChatMessagePart.
The SSE type guards had a & Record<string, unknown> intersection
that widened everything untyped downstream. Since the data comes
from our own API, the intersection was removed and all handlers in
ChatContext now use generated types directly.
Fixes tool_call_id and tool_name variant tags in codersdk/chats.go:
marked optional to match reality (Go guards against empty values,
omitempty omits them at the wire level).
Refs #23168, #23175
## Summary
- add shared MCP annotation metadata to toolsdk tools
- emit MCP tool annotations from both coderd and CLI MCP servers
- cover annotation serialization in toolsdk, coderd MCP e2e, and CLI MCP
tests
## Why
- Coder already exposed MCP tools, but it did not populate MCP tool
annotation hints (`readOnlyHint`, `destructiveHint`, `idempotentHint`,
`openWorldHint`).
- Hosts such as Claude Desktop use those hints to classify and group
tools, so without them Coder tools can get lumped together.
- This change adds a shared annotation source in `toolsdk` and has both
MCP servers emit those hints through `mcp.Tool.Annotations`, avoiding
drift between local and remote MCP implementations.
## Testing
- Tested locally on Cladue Desktop and the tools are categorized
correctly.
<table>
<tr>
<td> Before
<td> After
<tr>
<td> <img width="613" height="183" alt="image"
src="https://github.com/user-attachments/assets/29d2e3fb-53bc-4ea7-bdb3-f10df4ef996b"
/>
<td> <img width="600" height="457" alt="image"
src="https://github.com/user-attachments/assets/cc384036-c9a7-4db9-9400-43ad51920ff5"
/>
</table>
Note: Done using Coder Agents, reviewed and tested by human locally
The flat ChatMessagePart interface had 20+ optional fields, preventing
TypeScript from narrowing types on switch(part.type). Each consumer
needed runtime validation, type assertions, or defensive ?. chains.
Add `variants` struct tags to ChatMessagePart fields declaring which
union variants include each field. A codegen mutation in apitypings
reads these tags via reflect and generates per-variant sub-interfaces
(ChatTextPart, ChatReasoningPart, etc.) plus a union type alias.
A test validates every field has a variants tag or is explicitly
excluded, and every part type is covered.
Remove dead frontend code: normalizeBlockType, alias case branches
("thinking", "toolcall", "toolresult"), legacy field fallbacks
(line_number, typedBlock.name/id/input/output), and result_delta
handling. Add test coverage for args_delta streaming, provider_executed
skip logic, and source part parsing.
Cian Johnston