add_platform.verify

Step 4/4 in integrate workflow

Full workflow to integrate a new AI platform into DeepWork

Adds a new AI platform to DeepWork with adapter, templates, and tests. Use when integrating Cursor, Windsurf, or other AI coding tools.

Prerequisites (Verify First)

Before proceeding, confirm these steps are complete:

• /add_platform.implement

Instructions

Goal: Sets up platform directories and verifies deepwork install works correctly. Use after implementation to confirm integration.

Verify Installation

Objective

Ensure the new platform integration works correctly by setting up necessary directories and running the full installation process.

Task

Perform end-to-end verification that the new platform can be installed and that DeepWork's standard jobs work correctly with it.

Prerequisites

Ensure the implementation step is complete:

• Adapter class exists in src/deepwork/adapters.py
• Templates exist in src/deepwork/templates/<platform_name>/
• Tests pass with 100% coverage
• README.md is updated

Process

1. Set up platform directories in the DeepWork repo

   The DeepWork repository itself should have the platform's command directory structure for testing:

   bashCopy

   mkdir -p <platform_command_directory>
   

   For example:

   • Claude: .claude/commands/
   • Cursor: .cursor/commands/ (or wherever Cursor stores commands)

2. Run deepwork install for the new platform

   bashCopy

   deepwork install --platform <platform_name>
   

   Verify:

   • Command completes without errors
   • No Python exceptions or tracebacks
   • Output indicates successful installation

3. Check that command files were created

   List the generated command files:

   bashCopy

   ls -la <platform_command_directory>/
   

   Verify:

   • deepwork_jobs.define.md exists (or equivalent for the platform)
   • deepwork_jobs.implement.md exists
   • deepwork_jobs.refine.md exists
   • deepwork_rules.define.md exists
   • All expected step commands exist

4. Validate command file content

   Read each generated command file and verify:

   • Content matches the expected format for the platform
   • Job metadata is correctly included
   • Step instructions are properly rendered
   • Any platform-specific features (hooks, frontmatter) are present

5. Test alongside existing platforms

   If other platforms are already installed, verify they still work:

   bashCopy

   deepwork install --platform claude
   ls -la .claude/commands/
   

   Ensure:

   • New platform doesn't break existing installations
   • Each platform's commands are independent
   • No file conflicts or overwrites

Quality Criteria

• Platform-specific directories are set up in the DeepWork repo
• deepwork install --platform <platform_name> completes without errors
• All expected command files are created:
  • deepwork_jobs.define, implement, refine
  • deepwork_rules.define
  • Any other standard job commands
• Command file content is correct:
  • Matches platform's expected format
  • Job/step information is properly rendered
  • No template errors or missing content
• Existing platforms still work (if applicable)
• No conflicts between platforms
• When all criteria are met, include <promise>✓ Quality Criteria Met</promise> in your response

Context

This is the final validation step before the platform is considered complete. A thorough verification ensures:

• The platform actually works, not just compiles
• Standard DeepWork jobs install correctly
• The platform integrates properly with the existing system
• Users can confidently use the new platform

Take time to verify each aspect - finding issues now is much better than having users discover them later.

Common Issues to Check

• Template syntax errors: May only appear when rendering specific content
• Path issues: Platform might expect different directory structure
• Encoding issues: Special characters in templates or content
• Missing hooks: Platform adapter might not handle all hook types
• Permission issues: Directory creation might fail in some cases

Job Context

A workflow for adding support for a new AI platform (like Cursor, Windsurf, etc.) to DeepWork.

The integrate workflow guides you through four phases:

1. Research: Capture the platform's CLI configuration and hooks system documentation
2. Add Capabilities: Update the job schema and adapters with any new hook events
3. Implement: Create the platform adapter, templates, tests (100% coverage), and README updates
4. Verify: Ensure installation works correctly and produces expected files

The workflow ensures consistency across all supported platforms and maintains comprehensive test coverage for new functionality.

Important Notes:

• Only hooks available on slash command definitions should be captured
• Each existing adapter must be updated when new hooks are added (typically with null values)
• Tests must achieve 100% coverage for any new functionality
• Installation verification confirms the platform integrates correctly with existing jobs

Required Inputs

Files from Previous Steps - Read these first:

• templates/ (from implement)

Work Branch

Use branch format: deepwork/add_platform-[instance]-YYYYMMDD

• If on a matching work branch: continue using it
• If on main/master: create new branch with git checkout -b deepwork/add_platform-[instance]-$(date +%Y%m%d)

Outputs

Required outputs:

• verification_checklist.md

Guardrails

• Do NOT skip prerequisite verification if this step has dependencies
• Do NOT produce partial outputs; complete all required outputs before finishing
• Do NOT proceed without required inputs; ask the user if any are missing
• Do NOT modify files outside the scope of this step's defined outputs

On Completion

1. Verify outputs are created
2. Inform user: "integrate step 4/4 complete, outputs: verification_checklist.md"
3. integrate workflow complete: All steps finished. Consider creating a PR to merge the work branch.

Reference files: .deepwork/jobs/add_platform/job.yml, .deepwork/jobs/add_platform/steps/verify.md