Prompts Overview
Copilot Collections includes 22 ready-to-use prompts — slash commands that trigger specific workflow actions across the full product lifecycle. They are stored in .github/prompts/ as .prompt.md files and become available as /command shortcuts in VS Code chat.
How Prompts Work
Each prompt file defines:
- Agent binding — Which agent executes the command.
- Model — The AI model to use (e.g., Claude Opus 4.6).
- Description — Shown in VS Code's command palette.
- Instructions — Detailed workflow steps, required skills, and output format.
When you type /tsh-research, /tsh-plan, etc. in the VS Code chat, the corresponding prompt file is loaded and executed by the bound agent.
Available Prompts
📋 Product Ideation Commands
| Command | Agent | Description |
|---|---|---|
| /tsh-analyze-materials | Business Analyst | Process workshop materials into Jira-ready epics and stories |
| /tsh-clean-transcript | Business Analyst | Clean a raw workshop transcript |
| /tsh-create-jira-tasks | Business Analyst | Format extracted tasks for Jira and push |
🛠 Development Commands
| Command | Agent | Description |
|---|---|---|
| /tsh-research | Context Engineer | Gather context and requirements for a task |
| /tsh-plan | Architect | Create a structured implementation plan |
| /tsh-implement | Software Engineer | Execute the implementation plan |
| /tsh-implement-ui | Software Engineer | Implement UI with iterative Figma verification |
✅ Quality Commands
| Command | Agent | Description |
|---|---|---|
| /tsh-review | Code Reviewer | Review implementation against plan and standards |
| /tsh-review-ui | UI Reviewer | Single-pass Figma vs implementation comparison |
| /tsh-review-codebase | Architect | Comprehensive code quality analysis |
| /tsh-implement-e2e | E2E Engineer | Create end-to-end tests with Playwright |
⚙️ Copilot Customization Commands
| Command | Agent | Description |
|---|---|---|
| /tsh-create-custom-agent | Copilot Orchestrator | Create a new custom agent |
| /tsh-create-custom-skill | Copilot Orchestrator | Create a new custom skill |
| /tsh-create-custom-prompt | Copilot Orchestrator | Create a new custom prompt |
| /tsh-create-custom-instructions | Copilot Orchestrator | Create custom instruction files |
🏗 Infrastructure & DevOps Commands
| Command | Agent | Description |
|---|---|---|
| /tsh-deploy-kubernetes | DevOps Engineer | Create Kubernetes deployments, Helm charts, and workload resources |
| /tsh-implement-terraform | DevOps Engineer | Create Terraform modules and provision cloud infrastructure safely |
| /tsh-implement-pipeline | DevOps Engineer | Create or modify CI/CD pipelines with deployment stages |
| /tsh-implement-observability | DevOps Engineer | Implement observability solutions including metrics, logs, traces, and alerting |
| /tsh-audit-infrastructure | DevOps Engineer | Audit infrastructure for security gaps, cost waste, and best practices |
| /tsh-analyze-aws-costs | DevOps Engineer | AWS cost optimization and tagging compliance audit |
| /tsh-analyze-gcp-costs | DevOps Engineer | GCP cost optimization and labeling compliance audit |
Input Format
All prompts accept either:
- A Jira ticket ID:
/tsh-research PROJ-123 - A task description:
/tsh-research Add pagination to the user list API
The agent adapts its behavior based on the input type — pulling context from Jira/Confluence for ticket IDs, or working from the description and codebase for free-form text.