Introduce `/project-wiki` bundled skill that orchestrates a multi-stage pipeline to
analyze a codebase and generate a complete technical documentation wiki. Adds four
specialized sub-agents:
- WikiProjectAnalyze: deep repository analysis and classification
- WikiCatalogueDesign: dynamic document structure design based on project traits
- WikiDocumentGenerate: code-driven technical document authoring
- WikiIndexGeneration: structured index and navigation creation
Also updates .gitignore to exclude `.costrict`, `.claude`, and `/costrict` directories.
Rename CLI binary from `ccb` to `csc`, update .gitignore for additional
AI tool directories and exe files, and fix unresponsive keyboard input
in interactive dialogs by stopping the early input listener before Ink
takes over stdin.
* feat: Add DeepSeek thinking mode support for OpenAI compatibility layer
- Add DeepSeek reasoning models support (deepseek-reasoner and DeepSeek-V3.2)
- Automatic thinking mode detection based on model name
- Inject thinking parameters in request body (both official API and vLLM formats)
- Preserve reasoning_content in message conversion for tool call iterations
- Extract buildOpenAIRequestBody() for testability
- Treat multimodal inputs (e.g. images) as new turn boundaries
- Fix env var cleanup in tests to prevent state leak
Signed-off-by: guunergooner <tongchao0923@gmail.com>
* docs: update contributors
---------
Signed-off-by: guunergooner <tongchao0923@gmail.com>
Co-authored-by: guunergooner <18660867+guunergooner@users.noreply.github.com>
Fixes#168
OpenAI requires that an assistant message with tool_calls be immediately
followed by tool messages. Previously, convertInternalUserMessage
output user content before tool results, causing 400 errors.
Now tool messages are pushed first.
Reverse-engineer the missing daemon + remoteControlServer implementation
by tracing the call chain from existing code:
- src/daemon/main.ts: restore from stub to full supervisor (spawn/monitor
workers, exponential backoff restart, graceful shutdown)
- src/daemon/workerRegistry.ts: restore from stub to worker dispatcher
(remoteControl kind → runBridgeHeadless())
- src/commands/remoteControlServer/: new slash command /remote-control-server
(alias /rcs) for managing the daemon from REPL
- build.ts + scripts/dev.ts: enable DAEMON feature flag
Both official CLI 2.1.92 and our codebase had the command registered in
commands.ts but the directory and daemon implementation were missing.
The bottom layer (runBridgeHeadless in bridgeMain.ts) was already complete.
Co-authored-by: unraid <local@unraid.local>
The earlyInput capture's escape sequence detection was too simplistic — it
only checked if the byte after ESC fell in 0x40-0x7E range, treating it as
a terminator. This caused DCS sequences (e.g. XTVERSION `\x1bP>|iTerm2
3.6.4\x1b\\`) and CSI parameter sequences (e.g. DA1 `\x1b[?64;...c`) to
partially leak into the input buffer as `>|iTerm2 3.6.4?64;1;2;4;6;17;18;21;22c`.
Fix by handling each escape sequence type per ECMA-48:
- CSI (`ESC [`): skip parameter + intermediate bytes, then final byte
- DCS/OSC/SOS/PM (`ESC P/]/X/^`): scan to BEL or ST terminator
- Other: keep single-byte skip
Closes#171
Co-authored-by: Claude Opus 4.6 <noreply@anthropic.com>
Add xAI Grok as a new API provider. Reuses OpenAI-compatible message/tool
converters and stream adapter with Grok-specific client and model mapping.
Default model mapping:
opus → grok-4.20-reasoning
sonnet → grok-3-mini-fast
haiku → grok-3-mini-fast
Users can customize mapping via:
- GROK_MODEL env var (override all)
- GROK_MODEL_MAP env var (JSON family map, e.g. {"opus":"grok-4"})
- GROK_DEFAULT_{FAMILY}_MODEL env vars
Activation: CLAUDE_CODE_USE_GROK=1 or modelType: "grok" in settings.json
Also integrates with /provider command for runtime switching.
Two fixes for OpenAI-compatible provider compatibility:
1. Sanitize JSON Schema `const` → `enum` in tool parameters.
Many OpenAI-compatible endpoints (Ollama, DeepSeek, vLLM, etc.)
do not support the `const` keyword in JSON Schema. Recursively
convert `const: value` to `enum: [value]` which is semantically
equivalent.
2. Force stop_reason to `tool_use` when tool_calls are present.
Some backends incorrectly return finish_reason "stop" even when
the response contains tool_calls. Without this fix, the query
loop treats the response as a normal end_turn and never executes
the requested tools.
Remove macOS-only guards so Computer Use works cross-platform:
- main.tsx: allow CHICAGO_MCP on any known platform (not just macos)
- swiftLoader.ts: remove darwin-only throw, let the backend handle it
- computer-use-input: dispatch to darwin/win32/linux backends
- computer-use-swift: rename loadDarwin→loadBackend, dispatch all platforms
Co-authored-by: yi7503 <yi7503@gmail.com>
Co-authored-by: Claude Opus 4.6 (1M context) <noreply@anthropic.com>
Two root causes fixed:
1. swiftLoader.ts: require('@ant/computer-use-swift') returns a module
with { ComputerUseAPI } class, not an instance. macOS native .node
exports a plain object. Fixed by detecting class export and calling
new ComputerUseAPI().
2. executor.ts resolvePrepareCapture: toolCalls.ts expects result to have
{ hidden: string[], displayId: number } fields. Our ComputerUseAPI
returns { base64, width, height } only. Fixed by backfilling missing
fields with defaults.
Verified: request_access → screenshot → left_click all work on Windows.
Co-Authored-By: Claude Opus 4.6 (1M context) <noreply@anthropic.com>
New Windows-native capabilities:
- windowCapture.ts: PrintWindow API for per-window screenshot (works on
occluded/background windows)
- windowEnum.ts: EnumWindows for precise window enumeration with HWND
- uiAutomation.ts: IUIAutomation for UI tree reading, element clicking,
text input, and coordinate-based element identification
- ocr.ts: Windows.Media.Ocr for screen text recognition (en-US + zh-CN)
Updated win32.ts backend to use EnumWindows for listRunning() and added
captureWindowTarget() for window-specific screenshots.
Co-Authored-By: Claude Opus 4.6 (1M context) <noreply@anthropic.com>
