Align on the shape of a change through an interview, then implement it. Escalates open product decisions and settles the implementation shape in conversation. Use when the user asks to \"discuss this change\", \"align on this change first\", \"ask me questions first\", \"interview me then implement\", \"agree on the approach before coding\", or wants the shape of a single change settled before any code is written.
npx skills add https://github.com/tobihagemann/turbo --skill discuss-change
Escalate open decisions, agree on the implementation shape, then implement.
Use TaskCreate to create a task for each step:
/implement skillAbsorb the request without interrupting. Take the task from the user's request, or from conversation context when the task was already established. Restate the goal in one or two sentences and confirm.
Identify product or design decisions the request did not resolve. Escalate these via AskUserQuestion before any code is written. Read the code the change would touch before judging whether a bullet matches. Skip when no bullet below matches the change.
Escalate when:
Do not escalate technical decisions the agent can make autonomously: which data structure, which existing pattern to follow, internal implementation approach. The boundary is product intent.
Confirm external constraints before escalating. When an option depends on a third-party API, service, or platform behaving a particular way, query documentation MCP tools (or WebSearch as a fallback) and drop the option unless current documentation confirms that behavior.
Present each decision as a concise trade-off with options. Mark the strongest option "(Recommended)" and place it first.
Interview the user about the implementation shape until you reach shared understanding. Use AskUserQuestion, one question at a time. Cover whichever of these matter for the task. Do not present a rigid checklist. Skip when the request and the resolved decisions already name the files to touch, the existing code to build on, and the tests to write.
| Area | What to explore |
|---|---|
| Reuse vs new | Which existing code should the change build on? Which patterns should it deliberately not follow, and why? |
| File placement | Where do new files live? Which existing files are modified? |
| Data flow | How does data move through the change? Any new boundaries or contracts? |
| Edge cases | Partial failure, empty states, backward compatibility, concurrency |
| Tests | Which existing test patterns apply? Where do new tests live? |
| Scope cut | Anything to explicitly defer? |
Output the agreed shape as text, short enough to read at a glance: what the change does, where it lands, the decisions resolved in Steps 2 and 3, how to tell it worked, and anything deliberately deferred. This text is the change description Step 5 implements, so keep it concrete enough to act on.
Then use AskUserQuestion to offer two paths:
/implement SkillRun the /implement skill. The shape confirmed in Step 4 is the change it applies.
Then use the TaskList tool and proceed to any remaining task.
/turboplan for plan mode.Comprehensive GitHub project management with swarm-coordinated issue tracking, project board automation, and sprint planning
Comprehensive technology-agnostic prompt for analyzing and documenting project folder structures. Auto-detects project types (.NET, Java, React, Angular, Python, Node.js, Flutter), generates detailed blueprints with visualization options, naming conventions, file placement patterns, and extension templates for maintaining consistent code organization across diverse technology stacks.
Use when complex problems require systematic step-by-step reasoning with ability to revise thoughts, branch into alternative approaches, or dynamically adjust scope. Ideal for multi-stage analysis, design planning, problem decomposition, or tasks with initially unclear scope.
Multi-agent workflow examples to work together on the OpenServ Platform. Covers agent discovery, multi-agent workspaces, task dependencies, and workflow orchestration using the Platform Client. Read reference.md for the full API reference. Read openserv-agent-sdk and openserv-client for building and running agents.
> Compress natural language memory files (CLAUDE.md, todos, preferences) into caveman format to save input tokens. Preserves all technical substance, code, URLs, and structure. Compressed version overwrites the original file. Human-readable backup saved as FILE.original.md.
API design principles and decision-making. REST vs GraphQL vs tRPC selection, response formats, versioning, pagination.
Patterns for automating GitHub workflows with AI assistance, inspired by [Gemini CLI](https://github.com/google-gemini/gemini-cli) and modern DevOps practices.
Groups existing components into logical business domains to plan service-based architecture. Use when asking "which components belong together?", "group these into services", "organize by domain", "component-to-domain mapping", or planning service extraction from an existing codebase. Do NOT use for identifying new domains from scratch (use domain-analysis) or analyzing coupling (use coupling-analysis).
Take tobihagemann/discuss-change from the repository into ~/.claude/skills for personal
use, or into .claude/skills inside a project.
The agent identifies a skill by the name field in its header. Two skills with the
same name cannot sit side by side — one of them will be ignored.