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tGD
tGD enthält 37 gesammelte Skills von openclawyhwang-hub, mit Repository-Berufsabdeckung und Skill-Detailseiten auf SkillsMP.
Skills in diesem Repository
Throwaway HTML mockups: 2-3 design variants to compare.
Breaks work into ordered tasks. Use when you have a spec or clear requirements and need to break work into implementable tasks. Use when a task feels too large to start, when you need to estimate scope, or when parallel work is possible.
Execute implementation plans by dispatching fresh subagents per task with two-stage review. Use when executing a multi-task implementation plan, when context is getting too long for quality output, or when you want maximum isolation between tasks.
Core tGD rules that MUST be followed at all times — the Verification Iron Law, per-phase tone, the Command Closing Report, and human sign-off. Load this at the start of every tGD session (the session-start meta-skill tgd-router points here) and whenever a command references it. Do not skip, do not rationalize exceptions.
Discovers and invokes agent skills. Use when starting a session or when you need to discover which skill applies to the current task. This is the meta-skill that governs how all other skills are discovered and invoked.
Creates specs before coding. Use when starting a new project, feature, or significant change and no specification exists yet. Use when requirements are unclear, ambiguous, or only exist as a vague idea.
Conducts multi-axis code review. Use before merging any change. Use when reviewing code written by yourself, another agent, or a human. Use when you need to assess code quality across multiple dimensions before it enters the main branch.
Guides systematic root-cause debugging. Use when tests fail, builds break, behavior doesn't match expectations, or you encounter any unexpected error. Use when you need a systematic approach to finding and fixing the root cause rather than guessing.
Structures git workflow practices. Use when making any code change. Use when committing, branching, resolving conflicts, or when you need to organize work across multiple parallel streams.
Compiles CodeGraph + Understand-Anything outputs into a self-contained single-file HTML wiki (wiki.html) plus a plain-Markdown docs tree. Every scanned repo gets the same fixed DeepWiki-style structure — home, overview, architecture, modules, flows, onboarding, source browser, search — only the data varies per project. Zero runtime dependencies beyond Python 3 stdlib; no node, npm, or build step. Standalone / manual skill — NOT part of the /tgd-map pipeline. Use when you explicitly want to generate or regenerate a project wiki from an existing knowledge graph under $TGD_DIR/.scans/.
Optimizes agent context setup. Use when starting a new session, when agent output quality degrades, when switching between tasks, or when you need to configure rules files and context for a project.
Automates CI/CD pipeline setup. Use when setting up or modifying build and deployment pipelines. Use when you need to automate quality gates, configure test runners in CI, or establish deployment strategies.
Records decisions and documentation. Use when making architectural decisions, changing public APIs, shipping features, or when you need to record context that future engineers and agents will need to understand the codebase.
Prepares production launches. Use when preparing to deploy to production. Use when you need a pre-launch checklist, when setting up monitoring, when planning a staged rollout, or when you need a rollback strategy.
Enforces evidence-based verification before claiming any work is complete. Use when about to claim work is complete, fixed, or passing — requires running verification commands and confirming output before making any success claims. Evidence before assertions, always.
Delivers changes incrementally. Use when implementing any feature or change that touches more than one file. Use when you're about to write a large amount of code at once, or when a task feels too big to land in one step.
Parse TASKS.md and auto-create Jira Data Center issues in a single Sprint. Use as conditional skill in /tgd-plan phase after TASKS.md is generated.
Refines raw ideas into sharp, actionable concepts through structured divergent and convergent thinking. Use when an idea is still vague, when you need to stress-test assumptions before committing to a plan, or when you want to expand options before converging on one. Triggers on "ideate", "refine this idea", or "stress-test my plan".
Extracts what the user actually wants instead of what they think they should want. Achieves this through one-question-at-a-time interview until ~95% confidence about the underlying intent. Use when an ask is underspecified ("build me X" without "for whom" or "why now"), when the user explicitly invokes ("interview me", "grill me", "are we sure?", "stress-test my thinking"), or when you catch yourself silently filling in ambiguous requirements before any plan, spec, or code exists.
Drives development with tests. Use when implementing any logic, fixing any bug, or changing any behavior. Use when you need to prove that code works, when a bug report arrives, or when you're about to modify existing functionality.
THE primary tool for all browser verification, testing, and automation. Use for ANY browser task: navigating pages, filling forms, clicking buttons, taking screenshots, extracting data, testing web apps, or exploring DOM. Replaces Webwright and DevTools.
Guides stable API and interface design. Use when designing APIs, module boundaries, or any public interface. Use when creating REST or GraphQL endpoints, defining type contracts between modules, or establishing boundaries between frontend and backend.
Simplifies code for clarity. Use when refactoring code for clarity without changing behavior. Use when code works but is harder to read, maintain, or extend than it should be. Use when reviewing code that has accumulated unnecessary complexity.
Manages deprecation and migration. Use when removing old systems, APIs, or features. Use when migrating users from one implementation to another. Use when deciding whether to maintain or sunset existing code.
Subjects every non-trivial decision to a fresh-context adversarial review before it stands. Use when correctness matters more than speed, when working in unfamiliar code, when stakes are high (production, security-sensitive logic, irreversible operations), or any time a confident output would be cheaper to verify now than to debug later.
Builds production-quality UIs. Use when building or modifying user-facing interfaces. Use when creating components, implementing layouts, managing state, or when the output needs to look and feel production-quality rather than AI-generated.
Optimizes application performance. Use when performance requirements exist, when you suspect performance regressions, or when Core Web Vitals or load times need improvement. Use when profiling reveals bottlenecks that need fixing.
Hardens code against vulnerabilities. Use when handling user input, authentication, data storage, or external integrations. Use when building any feature that accepts untrusted data, manages user sessions, or interacts with third-party services.
Grounds every implementation decision in official documentation. Use when you want authoritative, source-cited code free from outdated patterns. Use when building with any framework or library where correctness matters.
Extract business domain knowledge from a codebase and generate an interactive domain flow graph. Works standalone (lightweight scan) or derives from an existing /understand knowledge graph.
Analyze a Karpathy-pattern LLM wiki knowledge base and generate an interactive knowledge graph with entity extraction, implicit relationships, and topic clustering.
Analyze a codebase to produce an interactive knowledge graph for understanding architecture, components, and relationships
Launch the interactive web dashboard to visualize a codebase's knowledge graph
Use when you need to ask questions about a codebase or understand code using a knowledge graph
Use when you need to analyze git diffs or pull requests to understand what changed, affected components, and risks
Use when you need a deep-dive explanation of a specific file, function, or module in the codebase
Use when you need to generate an onboarding guide for new team members joining a project