deepwork

name	deepwork
description	Start or continue DeepWork workflows using MCP tools

DeepWork Workflow Manager

Execute multi-step workflows with quality gate checkpoints.

Terminology

A job is a collection of related workflows. For example, a "code_review" job might contain workflows like "review_pr" and "review_diff". Users may use the terms "job" and "workflow" somewhat interchangeably when describing the work they want done — use context and the available workflows from get_workflows to determine the best match.

IMPORTANT: Use the DeepWork MCP server tools. All workflow operations are performed through MCP tool calls and following the instructions they return, not by reading instructions from files.

How to Use

1. Call get_workflows to discover available workflows
2. Call start_workflow with goal, job_name, and workflow_name
3. Follow the step instructions returned; use the session_id from begin_step for all subsequent calls
4. Call finished_step with your outputs when done
5. Handle the response: needs_work, next_step, or workflow_complete

Creating New Jobs

You MUST create new DeepWork jobs by starting the `new_job` workflow via the DeepWork MCP tools. Follow the guidance from the DeepWork MCP server as you go through the workflow — it will walk you through each step.

To create a new job, use the MCP tools:

1. Call get_workflows to confirm the deepwork_jobs job is available
2. Call start_workflow with:
   • job_name: "deepwork_jobs"
   • workflow_name: "new_job"
   • goal: a description of what the new job should accomplish
3. Follow the instructions returned by the MCP tools as you progress through the workflow

Quality Gates

Steps may have quality criteria. When you call finished_step:

• Outputs are evaluated against review criteria
• If any fail, you get needs_work with feedback — fix issues and call finished_step again
• After passing, you get the next step or completion

Nested Workflows and Navigation

• Starting a workflow while one is active pushes onto a stack. Check the stack field in responses.
• Use abort_workflow with an explanation if a workflow cannot be completed.
• Use go_to_step to revisit an earlier step — clears progress from that step onward.

Tips

• Create all expected outputs before calling finished_step — check step_expected_outputs for what's required
• Provide clear, specific goals when starting — they're used for context throughout the workflow
• Read quality gate feedback carefully before retrying — it tells you exactly what to fix
• Don't leave workflows in a broken state — use abort_workflow if you can't complete

Intent Parsing

When the user invokes /deepwork, parse their intent:

1. ALWAYS: Call get_workflows to discover available workflows
2. Based on the available flows and what the user said in their request, proceed:
   • Explicit workflow: /deepwork <a workflow name> → start the <a workflow name> workflow
   • General request: /deepwork <a request> → infer best match from available workflows
   • No context: /deepwork alone → ask user to choose from available workflows

Special case: /deepwork learn after /deepwork:record

If the user invokes /deepwork learn and /deepwork:record was used earlier in this conversation, the session captured a new workflow from scratch — there is no existing job to learn from. Instead of starting the learn workflow, start the new_job workflow (job_name: "deepwork_jobs", workflow_name: "new_job") with a goal summarizing the workflow the user recorded. Use the conversation history as the primary input for defining the job's steps, inputs, and outputs.