* fix: compaction config for small context windows (≤32K)
Raise COMPACTION_SMALL_CONTEXT_WINDOW from 16K to 32K so models like
Haiku 4.5 (30K context) use proportional 50% reserve instead of the
fixed 20K reserve. Also scale fixedOverhead for small contexts (capped
at 40% of context window) to prevent the doom loop where overhead alone
triggers compaction on every step.
Co-Authored-By: Claude Opus 4.6 <noreply@anthropic.com>
* docs: add compaction tuning guidance to limits constants
Explain the relationship between SMALL_CONTEXT_WINDOW and
FIXED_OVERHEAD so devs know the 24K minimum constraint when
tweaking these values.
Co-Authored-By: Claude Opus 4.6 <noreply@anthropic.com>
---------
Co-authored-by: Claude Opus 4.6 <noreply@anthropic.com>
* feat: add 2-stage pruning to compaction pipeline before LLM summarization
Add two new lightweight stages to the compaction prepareStep pipeline that
recover context tokens cheaply before falling back to expensive LLM
summarization:
- Stage 2: Use AI SDK's pruneMessages to remove old tool call/result
pairs beyond the last 6 messages entirely
- Stage 3: Replace remaining tool output values with short placeholders
("[Cleared — N chars]") while preserving tool call structure and IDs
Both stages re-estimate tokens from message content (not stale step
usage) after modifying messages. The existing LLM summarization and
sliding window fallback remain as Stage 4.
Also adds estimateTokensForThreshold() helper, clearToolOutputs()
function, and COMPACTION_PRUNE_KEEP_RECENT_MESSAGES /
COMPACTION_CLEAR_OUTPUT_MIN_CHARS constants.
Co-Authored-By: Claude Opus 4.6 <noreply@anthropic.com>
* fix: reorder compaction pipeline — truncate before clear, protect recent tools
- Stage 0: Check threshold, return untouched when under (no data loss)
- Stage 1: Prune old tool call/result pairs beyond last 6 messages
- Stage 2: Truncate large tool outputs to 15K chars (keeps partial content)
- Stage 3: Clear old tool outputs with placeholders, protect last 2
- Stage 4: LLM-based compaction with sliding window fallback
clearToolOutputs now accepts keepRecentCount parameter (default 2) to
skip the N most recent tool messages from clearing.
Co-Authored-By: Claude Opus 4.6 <noreply@anthropic.com>
* fix: limits fixes
* fix: address review — preserve toKeep context, derive test values from constants
- When Stage 3 (clearToolOutputs) doesn't resolve overflow, pass
truncated (not cleared) messages to Stage 4 so toKeep retains
meaningful tool outputs for the agent's immediate context
- Add comment explaining intentional conservatism in post-prune
token estimation (step usage is stale, must re-estimate safely)
- Refactor computeConfig tests to derive expected values from
AGENT_LIMITS constants instead of hardcoding magic numbers
Co-Authored-By: Claude Opus 4.6 <noreply@anthropic.com>
---------
Co-authored-by: Claude Opus 4.6 <noreply@anthropic.com>
* feat: new tools for breadcrumbs
* feat: setup scheduled task card
* feat: added dismiss cooldown
* chore: update prompt
* fix: support api key tool
* fix: prompt text to limit nudges
* fix: scheduled tasks card
* fix: update nudges prompt
* feat: skip nudges when user dismisses nudge
* fix: ensure nudges only show if they are not dismissed
* Revert "fix: ensure nudges only show if they are not dismissed"
This reverts commit d825254698829b8e9941aae7873bd440027d0c74.
* Revert "feat: skip nudges when user dismisses nudge"
This reverts commit 12b552b454d10ec4209b88668fc48681423ff6fc.
* Revert "fix: update nudges prompt"
This reverts commit 80b7520b953b4d3cbed2ed477b9e508e39938dca.
* feat: update agent with mcp when new mcp connection is added
* feat: created connect apps option as a blocking card system
* feat: schedule tasks passive without dismiss
* fix: nudges and prompt texts
* fix: biome lint errors
* fix: review comments
* fix: resolve comments
* fix: review comments
* fix: review comments
* fix: auto resolve state
* fix: eliminate the race where the async delete could resolve after the
new session
* feat: track ignored apps list
* fix: empty response text object on message reply
* feat: sync previously connected mcps
* feat: sync integrations with klavis
* feat: account for unauthenticated connections
* fix: analytics events
* fix: typescript issues
* fix: klavis client issue
* fix: invalid mcps causing entire responses from failing
* fix: prompt with card for integrations when the integration fails
* fix: prompt structure to support declined apps
* fix: refresh session on mcp changes
* feat: add agent skills system with catalog, loader, and UI
Co-Authored-By: Claude Opus 4.6 <noreply@anthropic.com>
* fix: return 500 for server errors in PUT/DELETE skill routes
Previously both handlers returned 404 for all errors, masking filesystem
failures (disk full, permission denied) as "not found". Now only
"not found" errors return 404; everything else returns 500.
* fix: align SKILL.md format with agentskills.io spec
- Move `enabled` and `version` into `metadata` field (spec only allows
name, description, license, compatibility, metadata, allowed-tools)
- Frontmatter `name` now matches directory name (lowercase kebab-case)
- Human-readable name stored in `metadata.display-name`
- Add index signature to SkillMetadata for arbitrary string keys
- Validate frontmatter with type guard in getSkill (remove unsafe cast)
- updateSkill now preserves existing frontmatter fields (license, etc.)
- Tighten buildSkillMd param from Record<string, unknown> to SkillFrontmatter
---------
Co-authored-by: Claude Opus 4.6 <noreply@anthropic.com>
- truncateToolOutputs: handle all output.type variants (text, json,
content) by checking output.value directly instead of branching on
type. The old code missed type 'content' (array of content parts),
causing 1M+ char tool results to pass through untouched.
- estimateTokens: change chars/4 to chars/3 — HTML/Markdown content
tokenizes at ~3.14 chars/token empirically, not 4.
- COMPACTION_FIXED_OVERHEAD: 5K → 12K to account for system prompt
(~2.5K tokens) + tool definitions as JSON Schema (~8-9K tokens).
- Apply truncateToolOutputs in prepareStep (Stage 0) before token
estimation, not just during summarization.
## Summary
- Add `VITE_PUBLIC_KIMI_LAUNCH` feature flag controlling Kimi partnership branding
- BrowserOS provider card shows "Powered by Kimi K2.5 from Moonshot AI" badge and "Extended usage limits for the next 2 weeks!" when flag is on
- Moonshot/Kimi highlighted as "Recommended" in provider templates
- LLM Hub defaults to Kimi, ChatGPT, Claude, Gemini (with legacy defaults migration)
- Kimi hub row shows "Powered by Moonshot AI" flare
- Model selector locked to kimi-k2.5
- "How to get a Kimi API key" link in provider dialog
- Moonshot provider fully integrated across frontend and backend
* feat: generalized compaction prompts with split turn handling
Replace browser-specific XML prompts with domain-agnostic markdown format.
Add split turn detection and parallel summarization for large single-turn
conversations. Switch compaction from generateText to streamText for
Fireworks API compatibility. Add comprehensive unit and E2E tests (84 total).
* fix: address code review issues for compaction (PR #391)
Enforce COMPACTION_MAX_SUMMARIZATION_INPUT cap, extract shared
callSummarizer helper, add runtime type guard for experimental_context,
move magic constants to AGENT_LIMITS, and remove dead constants.
* fix: cap truncatedTurnPrefix input to maxSummarizationInput
Apply the same sliding window cap to turn prefix messages that was
already applied to toSummarize, preventing unbounded LLM input for
long single-turn conversations with many tool calls.
* fix: reduce browseros-auto default context window to 200K
The 400K setting caused compaction to trigger at ~383K, but the actual
model limit is 262K. Conversations hit the hard limit before compaction
could kick in.
Automatically detect whether custom MCP servers use Streamable HTTP or
SSE transport by probing with a POST request before creating the config.
- Add detectMcpTransport() utility that probes the server endpoint
- If POST returns 200 with JSON/event-stream, use Streamable HTTP
- If POST returns 404/405 or fails, fall back to SSE transport
- Cache detection results per URL with 1-hour TTL
- Skip caching for transient errors (5xx, network failures)
Known servers (browseros-mcp, klavis-strata) skip detection and use
Streamable HTTP directly.
* fix: tempDir is executionDir and create per session execution dir
* fix: move create() in gemini-agent to top
* fix: log(debug) directories
* fix: chat routes bug
* feat: support userSessionDir in /chat request schema
* fix: clean-up un-used types
* fix: lint errors
* fix: controller-ext is built separately
* fix: remove un-used scripts in agent/
* fix: rename to assistant
* fix: add build scripts
* feat: new start:dev to start both
* fix: update gitignore
* feat: --new-ports support for dev:start
* feat: update start-all to support port and new data dir
* fix: add help insturctions for start:dev
* feat: agent-sdk outline
* feat: unit tests for agent-sdk
* feat: implement /sdk routes
* feat: integration test for agent-sdk with server
* feat: ENV to disble headless mode for testing
* feat: act() integration test working
* chore: refactor package/shared to have constants/ and /types separately
* feat: verify() and extract() sdk APIs
* feat: extract() use remote endpoint for extraction
* feat: verify() implemented - lazy parsing to avoid strong schema checks
* fix: remove generateStructuredOutput as not models support it
* fix: clean-up LLM types and use zod schema
* fix: typecheck vitetest error
* fix: remove directly calling GeminiAgent in sdk act()
* fix: lefthook for refactor warning
* fix: refactor routes/sdk to move business logic out
* chore: fix monorepo setup
1) use single .env.development file at the root
2) update package.json to contain commands to start server and agent
3) rename "Assistant" package name to "agent"
4) rename HTTP_MCP_PORT to SERVER_PORT
* chore: update README
* chore: update .env.example
