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Found 48 Skills
Conduct targeted code exploration on a repository, and document the process of "Asking Questions → Reading Code → Reaching Conclusions" as searchable evidence for direct reuse when similar questions arise next time. There are three types: question (investigate code around a specific problem and provide conclusions), module-overview (organize the structure, boundaries, entry points, and dependencies of a module), spike (conduct lightweight technical exploration of multiple possible directions without making final decisions). Trigger scenarios: When users say "Let's explore first", "How is X implemented in this repository", "Quickly get familiar with this module", "Archive the exploration results". For the distinction from learning / tricks / decisions, refer to the root skill `easysdd`.
Maintain organized project documentation with metadata headers. Update existing docs before creating new ones. Use when writing or editing any project documentation.
Organize reusable programming patterns, library usages, and technical techniques that address "This is the correct way to do such tasks" into a prescriptive reference library, which can be retrieved and reused on demand during feature-design and issue-analyze phases. There are three types: pattern (design patterns, programming idioms), library (usage and pitfalls of a specific library/framework), technique (specific operation skills / command recipes). Trigger scenarios: when users say "Record a trick", "This usage is worth noting", "tricks", "Record library usage", or when valuable techniques worth documenting and archiving are discovered during feature-design / issue-analyze phases and actively pushed. For how to distinguish it from learning / decisions / explore, refer to the root skill of `easysdd`.
Manage the Grounded Docs MCP Server documentation index. Covers scraping and indexing documentation from URLs or local files, refreshing existing indexes with changed content, and removing libraries from the index. Use when you need to add, update, or delete indexed documentation.
Use when revising existing wiki pages because knowledge has changed, a new piece of information updates or contradicts existing content, or the user wants to directly edit wiki content with LLM assistance.
Set a tracking document as the source of truth for the current feature or task. Use when starting work on a feature, bug fix, or multi-step task that benefits from a persistent record of decisions, discoveries, and progress. Keeps the document updated as work proceeds.
Use this skill when > Design review session that stress-tests plans against the existing domain model, sharpens terminology, and updates documentation (CONTEXT.md, ADRs) inline as decisions crystallize. Use when validating architecture or plans against a project's language and documented decisions.
Initialize a .spec-driven/ directory in a project. Creates config.yaml and specs/ scaffold, then guides the user to fill in project context.
When the user wants to create or update their Unreal Engine project context document. Use when the user says 'project context,' 'set up context,' 'UE context,' 'configure project,' or wants to avoid repeating their project setup across UE development tasks. Creates `.agents/ue-project-context.md` that all other UE skills reference. See related skills footer for skills that depend on this context.
Documentation and commit specialist. Runs after ralph subagents complete a Priority group. Reviews RALPH_DONE signals, updates progress.md and PRD task checkboxes, and makes one atomic git commit per completed user story. Also writes an implementation summary when the full PRD is done. Use after ralph subagents finish implementing — never during active development.
Create a new Architecture Decision Record with sequential numbering and AgentDB registration
Generate and critically evaluate grounded improvement ideas for the current project. Use when asking what to improve, requesting idea generation, exploring surprising improvements, or wanting the AI to proactively suggest strong project directions before brainstorming one in depth. Triggers on phrases like 'what should I improve', 'give me ideas', 'ideate on this project', 'surprise me with improvements', 'what would you change', or any request for AI-generated project improvement suggestions rather than refining the user's own idea.