### Setup Wizard: Guided Mode Source: https://docs.work-buddy.ai/handbook/status_setup-wizard-directions Initiate the 'guided' mode for first-time setup. This mode walks the user through bootstrap, feature selection, requirements, and health checks. ```python mcp__work-buddy__wb_run("setup_wizard", {"mode": "guided"}) ``` -------------------------------- ### Run Setup Wizard Source: https://docs.work-buddy.ai/handbook/status_setup-wizard-directions Use this command to initiate the setup wizard. Specify the desired mode and any necessary arguments. ```python mcp__work-buddy__wb_run("setup_wizard", {"mode": "", ...}) ``` -------------------------------- ### Setup Wizard: Status Mode Source: https://docs.work-buddy.ai/handbook/status_setup-wizard-directions Run the setup wizard in 'status' mode for a quick overview of bootstrap requirements and component health. This is the default mode if none is specified. ```python mcp__work-buddy__wb_run("setup_wizard", {"mode": "status"}) ``` -------------------------------- ### Install LM Studio CLI on Windows Source: https://docs.work-buddy.ai/handbook/features_lmstudio-offload-setup Installs LM Studio using winget and instructs on how to enable the CLI for terminal use. ```powershell winget install LMStudio.LMStudio # Open LM Studio once → System tab → "Install CLI" so `lms` is on PATH. ``` -------------------------------- ### Setup Wizard: Diagnose Mode Source: https://docs.work-buddy.ai/handbook/status_setup-wizard-directions Run the setup wizard in 'diagnose' mode for targeted troubleshooting of a specific component. This mode combines requirements, health checks, and diagnostic sequences. ```python wb_run("setup_wizard", {"mode": "diagnose", "component": "hindsight"}) ``` -------------------------------- ### Start LM Studio Local Server Source: https://docs.work-buddy.ai/handbook/features_lmstudio-offload-setup Start the LM Studio local server. The default port is 1234. Use `curl` to verify that the server is running and listing models. ```bash lms server start # default port 1234 curl http://127.0.0.1:1234/v1/models ``` -------------------------------- ### Setup Wizard: View Preferences Source: https://docs.work-buddy.ai/handbook/status_setup-wizard-directions View current feature preferences using the 'preferences' mode without any 'updates'. This displays the current configuration of components. ```python wb_run("setup_wizard", {"mode": "preferences"}) ``` -------------------------------- ### Install LM Studio CLI on macOS Source: https://docs.work-buddy.ai/handbook/features_lmstudio-offload-setup Installs LM Studio using Homebrew and guides on enabling the CLI for terminal operations. ```bash brew install --cask lm-studio # Open LM Studio once → System tab → "Install CLI" so `lms` is on PATH. ``` -------------------------------- ### Day Planner Entry Format Example Source: https://docs.work-buddy.ai/handbook/obsidian_day-planner Example of how to format entries in the Day Planner section of a note. Timestamps are in 24-hour HH:mm format, and tasks snap to 10-minute intervals. ```markdown - [ ] 09:00 - 10:30 Deep work: ECG-FM paper writing - [ ] 10:30 - 10:45 Break - [ ] 10:45 - 11:30 [Cal] Lab meeting ``` -------------------------------- ### Setup Wizard: Save Preferences Source: https://docs.work-buddy.ai/handbook/status_setup-wizard-directions Save user preferences for features using the 'preferences' mode with the 'updates' argument. This allows enabling or disabling specific components. ```python wb_run("setup_wizard", {"mode": "preferences", "updates": {"hindsight": {"wanted": false}}}) ``` -------------------------------- ### Configure LLM Tiers in YAML Source: https://docs.work-buddy.ai/handbook/architecture_llm-runner Example configuration for binding LLM tiers to specific backends and models in `config.yaml`. This setup determines which concrete LLM endpoint the runner will use based on the requested tier. ```yaml llm: tiers: frontier_balanced: backend: anthropic model: claude-sonnet-4-6 defaults: {max_tokens: 4096} local_tool_calling: backend: lmstudio_native profile: local_agent defaults: {max_tokens: 4096} ``` -------------------------------- ### Format Focused Tasks Source: https://docs.work-buddy.ai/handbook/morning_morning-routine Example structure for focused tasks, including optional duration and a specific start time. Tasks can use 'description' or 'text' for their label. ```json [{"description": "MIT 1: Ship LLM-judge eval", "duration": 90}, {"description": "MIT 2: Draft paper contract", "duration": 30, "time_start": "14:00"}] ``` -------------------------------- ### Setup Wizard: Update Preferences Source: https://docs.work-buddy.ai/handbook/status_setup-wizard-directions Update feature preferences using the 'preferences' mode with the 'updates' argument. This allows modifying settings like 'wanted' status and 'reason' for components. ```python wb_run("setup_wizard", {"mode": "preferences", "updates": {"telegram": {"wanted": false, "reason": "..."}, "hindsight": {"wanted": true}}}) ``` -------------------------------- ### Start Development Orientation Workflow Source: https://docs.work-buddy.ai/handbook/dev_dev-mode Initiates the development orientation process. This is a mandatory first step before making any code modifications to ensure proper understanding of the existing architecture and code. ```python `mcp__work-buddy__wb_run("dev-orient")` ``` -------------------------------- ### Running Python Commands in Work Buddy Source: https://docs.work-buddy.ai/handbook/dev_plugin-integration Example command to activate the 'work-buddy' conda environment and execute a command within the project directory. ```powershell powershell.exe -Command "cd \repos\work-buddy; conda activate work-buddy; " ``` -------------------------------- ### Return Complete Routing Record Source: https://docs.work-buddy.ai/handbook/routing_route-information Example of the final JSON output summarizing all routing actions taken, categorized by 'routed', 'deleted', 'split', and 'skipped' items, including relevant details for each. ```json { "routed": [{"id": "t_7b2e09", "action": "route", "destination": "tasks/master-task-list.md"}], "deleted": [{"id": "t_c44d1a", "reason": "Already completed"}], "split": [{"id": "t_d44f12", "splits": [...]}], "skipped": [{"id": "t_x9y8z7", "reason": "User wants to think about it"}] } ``` -------------------------------- ### Example User Interaction for Cluster Review Source: https://docs.work-buddy.ai/handbook/routing_route-information Illustrates how items are presented to the user for confirmation, correction, or skipping. Includes item ID, raw text, agent interpretation, proposed action, and confidence level. ```markdown ## Admin items (3 items) **[t_d44f12]** "Admin - VPN/taxes/new laptop stuff" → Proposed: task (inbox) — "Set up VPN, handle tax prep, research laptops" → Confidence: low — this bundles 3 things, and taxes may be done What is this? Confirm / correct / skip? **[t_c44d1a]** "Taxes - Varsha" → Proposed: task (inbox) — "Tax-related task involving Varsha" → Confidence: low — don't know who Varsha is or what the task is What is this? Confirm / correct / skip? **[t_7b2e09]** "Varsha - T4 / T4A" → Proposed: linked to t_c44d1a? — "Tax form from Varsha" → Confidence: low What is this? Confirm / correct / skip? ``` -------------------------------- ### Download GGUF Model using Hugging Face CLI Source: https://docs.work-buddy.ai/handbook/features_lmstudio-offload-setup Downloads a GGUF model to a temporary cache directory using `huggingface-cli` as a fallback if `lms get` fails, requiring manual import afterward. ```bash pip install huggingface_hub # if not already installed huggingface-cli download yixuan-chia/snowflake-arctic-embed-m-v1.5-Q8_0-GGUF \ --local-dir /tmp/gguf-cache ``` -------------------------------- ### Format Calendar Events (Flat) Source: https://docs.work-buddy.ai/handbook/morning_morning-routine Example of a flat structure for calendar events, suitable for manual construction. 'start' and 'end' can be 'HH:MM' or ISO datetime. 'summary', 'description', or 'text' can be used for the event label. ```json [{"start": "13:00", "end": "13:30", "summary": "Team sync"}] ``` -------------------------------- ### Verify LM Studio CLI Installation Source: https://docs.work-buddy.ai/handbook/features_lmstudio-offload-setup Checks if the LM Studio CLI (`lms`) is installed and accessible by verifying its version. ```bash lms --version # should print a version string, no errors ``` -------------------------------- ### Spawn Help Session Source: https://docs.work-buddy.ai/handbook/architecture_control-graph Initiates a help session for a specific node in the control graph. ```APIDOC ## POST /api/control/help/ ### Description Spawns a help session for the specified node ID. This typically involves creating a structured brief for a support agent. ### Method POST ### Endpoint `/api/control/help/` ### Parameters #### Path Parameters - **node_id** (string) - Required - The ID of the node for which to spawn a help session. ``` -------------------------------- ### Datacore Get Page Source: https://docs.work-buddy.ai/handbook/context_datacore_get_page Get a single vault page by path with Datacore metadata: frontmatter, sections, tags, links, timestamps. ```APIDOC ## GET /datacore/get_page ### Description Retrieves a single vault page by its path, including Datacore metadata such as frontmatter, sections, tags, links, and timestamps. ### Method GET ### Endpoint /datacore/get_page ### Parameters #### Query Parameters - **path** (str) - Required - Vault-relative path (e.g. 'journal/2026-04-09.md') - **fields** (str) - Optional - Comma-separated fields to retrieve. Defaults to all fields. ### Response #### Success Response (200) - **frontmatter** (object) - The frontmatter of the page. - **sections** (array) - An array of sections within the page. - **tags** (array) - An array of tags associated with the page. - **links** (array) - An array of links found in the page. - **timestamps** (object) - Timestamps related to the page (e.g., created, modified). ### Requirements - obsidian - datacore ``` -------------------------------- ### Run Morning Routine Source: https://docs.work-buddy.ai/handbook/morning_directions Initiates the morning routine workflow. Load morning configuration before proceeding with individual steps. ```python from work_buddy.morning import get_morning_config, is_phase_enabled, resolve_phases cfg = get_morning_config() # For each step, check is_phase_enabled(step_id, cfg). If disabled, advance immediately with {skipped: true}. ``` -------------------------------- ### Task Creation Parameters Source: https://docs.work-buddy.ai/handbook/tasks_task-new Illustrates how to construct parameters for the task_create function using the final plan. It dynamically includes optional fields from the plan. ```python final_plan = params = {"task_text": final_plan["task_text"]} for k in ("urgency", "project", "due_date", "contract", "summary", "tags"): if final_plan.get(k) is not None: params[k] = final_plan[k] result = `mcp__work-buddy__wb_run("task_create", params)` ``` -------------------------------- ### Create Task with Handoff Prompt Source: https://docs.work-buddy.ai/handbook/tasks_handoff-directions Use this command to create a task with a concise summary and a full handoff prompt. The summary parameter triggers the creation of a note file. ```shell mcp__work-buddy__wb_run("task_create", {"task_text": "", "summary": ""}) ``` -------------------------------- ### Python Start Messaging Bridge Source: https://docs.work-buddy.ai/handbook/architecture_event-bus Starts a daemon process that polls a messaging service for events and republishes them onto the in-process event bus. This bridges communication between different processes. ```python dashboard.messaging_bridge.start_messaging_bridge(...) ``` -------------------------------- ### Stage Precisely with Git Source: https://docs.work-buddy.ai/handbook/dev_dev-commit Avoid using `git add -A` or `git add .`. Use `git add ` when you own the entire file's diff. For files with mixed hunks, use `git add -p ` and selectively accept your changes. ```bash git add ``` ```bash git add -p ``` -------------------------------- ### Get Thread Source: https://docs.work-buddy.ai/handbook/messaging_get_thread Retrieves all messages in a specified conversation thread. ```APIDOC ## Get Thread ### Description Get all messages in a conversation thread. ### Method GET ### Endpoint /messaging/threads/{thread_id} ### Parameters #### Path Parameters - **thread_id** (str) - Required - The unique identifier for the thread. ``` -------------------------------- ### Background Registry Warm-Start Source: https://docs.work-buddy.ai/handbook/architecture_mcp-import-discipline The `main_http()` function initiates a daemon thread to pre-fetch the registry upon server bind. This improves initial request latency by ensuring the registry is ready. ```python main_http() ``` -------------------------------- ### Get Project Source: https://docs.work-buddy.ai/handbook/projects_project_get Retrieves a single project by its unique slug, along with its recent observations. ```APIDOC ## Project Get ### Description Get a single project with its recent observations (identity + state + trajectory). ### Method GET ### Endpoint /projects/{slug} ### Parameters #### Path Parameters - **slug** (str) - Required - Project slug (e.g. 'my-project') ### Response #### Success Response (200) - **id** (str) - The unique identifier of the project. - **name** (str) - The name of the project. - **slug** (str) - The slug of the project. - **observations** (list) - A list of recent observations for the project. - **id** (str) - The unique identifier of the observation. - **state** (str) - The state of the observation. - **trajectory** (str) - The trajectory of the observation. ``` -------------------------------- ### Get Task Briefing Source: https://docs.work-buddy.ai/handbook/morning_morning-routine Retrieves the current task status. This is a direct call to the 'task_briefing' function. ```python `mcp__work-buddy__wb_run("task_briefing")` ``` -------------------------------- ### Define a SourceDescriptor Source: https://docs.work-buddy.ai/handbook/triage_source-descriptors Example of a SourceDescriptor for a journal thread, specifying its name, TTL, quarantine triggers, and configuration. ```python SourceDescriptor( name="journal_thread", ttl_days=5, quarantine_triggers=[ "source_removed", "source_edited_beyond_match", ], config={ "edit_match_threshold": 0.85, }, ) ``` -------------------------------- ### Set Step Visibility to Summary with Included Keys Source: https://docs.work-buddy.ai/handbook/architecture_workflows Configure a step to return a summary of results inline, including only specified keys. Full results are still available on demand. ```json "visibility": {"mode": "summary", "include_keys": ["total", "items"]} ``` -------------------------------- ### Get Activity Timeline Source: https://docs.work-buddy.ai/handbook/journal_activity_timeline Retrieves a structured timeline of recent activity. You can specify a time range and optionally include deeper signals. ```APIDOC ## Get Activity Timeline ### Description Infer recent activity from journal entries and optionally deeper signals. Returns a structured timeline with events, gaps, and relative timestamps. Use for understanding what happened during a time window. ### MCP Name `activity_timeline` ### Category `journal` ### Parameters #### Query Parameters - **deep** (bool) - Optional - Also collect git/chat/vault signals (default: false) - **since** (str) - Required - ISO datetime or relative shorthand (e.g. '2h', '1d', '30m') - **target_date** (str) - Optional - Journal date YYYY-MM-DD (default: inferred from since) - **until** (str) - Optional - ISO datetime. Default: now. ### Requirements - obsidian ``` -------------------------------- ### Python EventBus Start Heartbeat Source: https://docs.work-buddy.ai/handbook/architecture_event-bus Initiates a background task to periodically publish heartbeat events. This is useful for monitoring the bus's liveness. ```python events.start_heartbeat(interval, bus) ``` -------------------------------- ### Run Full Blindspot Detection Workflow Source: https://docs.work-buddy.ai/handbook/metacognition_blindspot-directions Executes the complete workflow for detecting blindspots, encompassing context gathering and pattern analysis. ```shell `mcp__work-buddy__wb_run("detect-blindspots")` ``` -------------------------------- ### Execute Datacore Query with Raw Syntax Source: https://docs.work-buddy.ai/handbook/obsidian_datacore-query-directions Direct method for querying Datacore using raw Datacore syntax. Use this for simpler queries or when a structured plan is not necessary. ```python mcp__work-buddy__wb_run("datacore_query", "@page/project-alpha-notes < childof tag/project/alpha") ``` -------------------------------- ### Initialize MCP Gateway Session Source: https://docs.work-buddy.ai/handbook/operations_mcp-gateway This is the mandatory first call for every agent session. It registers your session with the MCP server for activity tracking. If `wb_init` is not in your tool list, use `wb_run` to call it. ```bash `mcp__work-buddy__wb_init(session_id="")` ``` ```bash `mcp__work-buddy__wb_run(capability="wb_init", params={"session_id": ""})` ``` -------------------------------- ### Get Rate Limit Observations Source: https://docs.work-buddy.ai/handbook/services_dashboard_costs Retrieves the most recent per-model rate-limit observations, including RPM, ITPM, and OTPM headroom, for display in the toolbar chip. ```APIDOC ## GET /api/costs/rate-limits ### Description Fetches the most recent per-model rate-limit observations (RPM, ITPM, OTPM headroom) for the toolbar chip. ### Method GET ### Endpoint /api/costs/rate-limits ``` -------------------------------- ### Direct Lookup in System Docs Source: https://docs.work-buddy.ai/handbook/operations_mcp-gateway Use `agent_docs` with a `path` and `depth` to retrieve full documentation for a specific item. ```javascript `mcp__work-buddy__wb_run("agent_docs", {"path": "morning/directions", "depth": "full"})` ``` -------------------------------- ### Run Python Command in Work Buddy Source: https://docs.work-buddy.ai/handbook/dev_dev-mode Execute Python commands within the Work Buddy environment. This example is specific to Windows with conda activation. ```powershell powershell.exe -Command "cd \repos\work-buddy; conda activate work-buddy; " ``` -------------------------------- ### Declarative Open Action Configuration Source: https://docs.work-buddy.ai/handbook/triage_card-actions Defines a per-source 'open in app' affordance within the SourceDescriptor.config. This includes the button label, the MCP capability to dispatch, a mapping of item properties to capability arguments, and optional error kinds for auto-quarantine. ```json { "open_action": { "label": "Open in Thunderbird", "capability": "email_display", "param_map": { "provider_message_id": "metadata.provider_message_id", "folder_path": "metadata.folder_path", }, "quarantine_on_error_kinds": ["email_message_not_found"], } } ```