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Analyze existing prompt and suggest improvements using the Seven Levels framework

Audit a codebase for agentic layer coverage and identify investment opportunities

Generate a comprehensive bug fix plan with root cause analysis from a bug description using meta-prompt template engineering.

Generate a comprehensive chore plan from a one-line description using meta-prompt template engineering.

Classify a GitHub issue into a problem class (chore, bug, or feature) for ADW routing.

Create a Git commit with agent attribution for ADW workflows.

Load task-specific context dynamically based on task type (bug, feature, review, chore, research)

Show current context window state and consumption analysis

Scaffold a new custom agent configuration.

Generate a new prompt at specified level.

Generate custom tool boilerplate with @tool decorator.

Generate configuration for a team of specialized agents

Generate concise markdown documentation from implemented changes.

Generate a comprehensive feature implementation plan with user story, implementation phases, and testing strategy from a feature description.

Generate a semantic Git branch name from issue context for ADW workflows.

Execute a generated plan file - a Higher-Order Prompt (HOP) that accepts another prompt (the plan) as input.

Set up an isolated Git worktree environment for parallel agent execution.

List available tools for custom agent configuration

Show the seven levels of agentic prompts with quick reference

Reload previous session context from a context bundle file

Run orchestration workflow for a complex task using multi-agent patterns

Create a minimal, surgical patch plan to address a specific issue.

Prime agent with codebase understanding. Runs git ls-files, reads README, and summarizes project structure.

Create a GitHub pull request with full context linking back to the original issue.

Analyze a failed E2E test, fix the underlying issue, and verify the fix

Analyze a failed test, fix the underlying issue, and verify the fix

Compare implementation against specification to verify alignment

Create minimum viable agentic layer structure for a project

Execute the scout-then-build pattern for a feature implementation

Validate state and merge branch to main for production deployment

Execute end-to-end test specification and report results

Run project test suite and report results in structured JSON format

List all available Claude Code tools with their parameters and capabilities.

Calculate and update agentic coding KPIs to measure ZTE progression

Upgrade an existing prompt to a higher level.