add_platform.verify
Sets up platform directories and verifies deepwork install works correctly. Use after implementation to confirm integration.
Best use case
add_platform.verify is best used when you need a repeatable AI agent workflow instead of a one-off prompt.
Sets up platform directories and verifies deepwork install works correctly. Use after implementation to confirm integration.
Teams using add_platform.verify should expect a more consistent output, faster repeated execution, less prompt rewriting.
When to use this skill
- You want a reusable workflow that can be run more than once with consistent structure.
When not to use this skill
- You only need a quick one-off answer and do not need a reusable workflow.
- You cannot install or maintain the underlying files, dependencies, or repository context.
Installation
Claude Code / Cursor / Codex
Manual Installation
- Download SKILL.md from GitHub
- Place it in
.claude/skills/add_platform.verify/SKILL.mdinside your project - Restart your AI agent — it will auto-discover the skill
How add_platform.verify Compares
| Feature / Agent | add_platform.verify | Standard Approach |
|---|---|---|
| Platform Support | Not specified | Limited / Varies |
| Context Awareness | High | Baseline |
| Installation Complexity | Unknown | N/A |
Frequently Asked Questions
What does this skill do?
Sets up platform directories and verifies deepwork install works correctly. Use after implementation to confirm integration.
Where can I find the source code?
You can find the source code on GitHub using the link provided at the top of the page.
SKILL.md Source
# 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: ```bash 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** ```bash 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: ```bash 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: ```bash 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`
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