Add Platform.add Capabilities

add_platform.add_capabilities

Step 2/4 in add_platform workflow

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.research

Instructions

Goal: Updates job schema and adapters with any new hook events the platform supports. Use after research to extend DeepWork's hook system.

Add Hook Capabilities

Objective

Update the DeepWork job schema and platform adapters to support any new hook events that the new platform provides for slash command definitions.

Task

Analyze the hooks documentation from the research step and update the codebase to support any new hook capabilities, ensuring consistency across all existing adapters.

Prerequisites

Read the hooks documentation created in the previous step:

• doc/platforms/<platform_name>/hooks_system.md

Also review the existing schema and adapters:

• src/deepwork/schemas/job_schema.py
• src/deepwork/adapters.py

Process

1. Analyze the new platform's hooks

   • Read doc/platforms/<platform_name>/hooks_system.md
   • List all hooks available for slash command definitions
   • Compare with hooks already in job_schema.py
   • Identify any NEW hooks not currently supported

2. Determine if schema changes are needed

   • If the platform has hooks that DeepWork doesn't currently support, add them
   • If all hooks are already supported, document this finding
   • Remember: Only add hooks that are available on slash command definitions

3. Update job_schema.py (if needed)

   • Add new hook fields to the step schema
   • Follow existing patterns for hook definitions
   • Add appropriate type hints and documentation
   • Example addition:

     # New hook from <platform>
     new_hook_name: Optional[List[HookConfig]] = None
     

4. Update all existing adapters

   • Open src/deepwork/adapters.py
   • For EACH existing adapter class:
     • Add the new hook field (set to None if not supported)
     • This maintains consistency across all adapters
   • Document why each adapter does or doesn't support the hook

5. Validate the changes

   • Run Python syntax check: python -m py_compile src/deepwork/schemas/job_schema.py
   • Run Python syntax check: python -m py_compile src/deepwork/adapters.py
   • Ensure no import errors

6. Document the decision

   • If no new hooks were added, add a comment explaining why
   • If new hooks were added, ensure they're documented in the schema

Output Format

job_schema.py

Location: src/deepwork/schemas/job_schema.py

If new hooks are added:

@dataclass
class StepDefinition:
    # ... existing fields ...

    # New hook from <platform_name> - [description of what it does]
    new_hook_name: Optional[List[HookConfig]] = None

adapters.py

Location: src/deepwork/adapters.py

For each existing adapter, add the new hook field:

class ExistingPlatformAdapter(PlatformAdapter):
    # ... existing code ...

    def get_hook_support(self) -> dict:
        return {
            # ... existing hooks ...
            "new_hook_name": None,  # Not supported by this platform
        }

Or if no changes are needed, add a documentation comment:

# NOTE: <platform_name> hooks reviewed on YYYY-MM-DD
# No new hooks to add - all <platform_name> command hooks are already
# supported by the existing schema (stop_hooks covers their validation pattern)

Quality Criteria

• Hooks documentation from research step has been reviewed
• If new hooks exist:
  • Added to src/deepwork/schemas/job_schema.py with proper typing
  • ALL existing adapters updated in src/deepwork/adapters.py
  • Each adapter indicates support level (implemented, None, or partial)
• If no new hooks needed:
  • Decision documented with a comment explaining the analysis
• Only hooks available on slash command definitions are considered
• job_schema.py has no syntax errors (verified with py_compile)
• adapters.py has no syntax errors (verified with py_compile)
• All adapters have consistent hook fields (same fields across all adapters)
• When all criteria are met, include <promise>✓ Quality Criteria Met</promise> in your response

Context

DeepWork supports multiple AI platforms, and each platform may have different capabilities for hooks within command definitions. The schema defines what hooks CAN exist, while adapters define what each platform actually SUPPORTS.

This separation allows:

• Job definitions to use any hook (the schema is the superset)
• Platform-specific generation to only use supported hooks (adapters filter)
• Future platforms to add new hooks without breaking existing ones

Maintaining consistency is critical - all adapters must have the same hook fields, even if they don't support them (use None for unsupported).

Common Hook Types

For reference, here are common hook patterns across platforms:

When you find a new hook type, consider whether it maps to an existing pattern or is genuinely new functionality.

Job Context

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

This job 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:

• hooks_system.md (from research)

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:

• job_schema.py
• adapters.py

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

Quality Validation

Stop hooks will automatically validate your work. The loop continues until all criteria pass.

To complete: Include <promise>✓ Quality Criteria Met</promise> in your final response only after verifying ALL criteria are satisfied.

On Completion

1. Verify outputs are created
2. Inform user: "Step 2/4 complete, outputs: job_schema.py, adapters.py"
3. Continue workflow: Use Skill tool to invoke /add_platform.implement

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