maplibre-layers
Use when adding map layers, managing GeoJSON sources, styling markers, or handling layer interactions. Load for layer registration patterns, markRaw usage, MglGeoJsonSource components, data-driven styling, and...
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Use when adding map layers, managing GeoJSON sources, styling markers, or handling layer interactions. Load for layer registration patterns, markRaw usage, MglGeoJsonSource components, data-driven styling, and...
Use when you notice a pattern that should be in the config. Analyzes current setup, researches best practices, and proposes specific config changes. Also use when asked to improve agent behavior or workflows.
Use when adding features, changing behavior, or modifying architecture. Creates change proposal with specs and tasks. ALWAYS ask for approval before proceeding to implementation. Do NOT use for bug fixes or tri...
Use when request is vague, complex, or needs design exploration BEFORE implementation. Ask questions one at a time. Do NOT use for clear, mechanical tasks. Output: design ready for OpenSpec proposal.
Use when working through any task checklist (not just OpenSpec). Complete one task, verify, mark done, then next. No skipping, no adding, no reordering.
Test game via browser with Chrome DevTools. Navigate UI, play through game flow, observe behavior and report issues.
Use for ANY bug, test failure, or unexpected behavior. Use BEFORE proposing fixes. Four phases: investigate, analyze, hypothesize, implement. Ensures understanding before attempting solutions.
Context and reference for building UI with shadcn-vue components. Load when adding, modifying, or debugging UI components.
Run tests before and after changes. Only add tests for complex logic, not boilerplate. Database tests matter most.
Test game mechanics via SQL. Use game_* tools for gameplay flow.
Use when working with candidate scoring, confidence calculation, softmax aggregation, or guess decision logic. Load for understanding how candidates are ranked, when the system decides to guess, and how semanti...
Use when working with geographic queries, geometry filtering, ST_* functions, or region-based candidate filtering. Load for PostGIS spatial operations, polygon intersections, distance calculations, or geographi...
Use when creating reusable composables, managing reactive state, or implementing the Composition API. Load for useX patterns, Pinia store patterns, withLoadingState helper, lifecycle management, and type-safe s...
Use when working with trait extraction, place enrichment, or the learning loop. Load for understanding how the system learns from gameplay, how traits are extracted from Nominatim + player sessions, async queue...
Use after completing a refactor, implementing a major feature, or when skills may be outdated. Analyzes code changes, identifies affected skills, and proposes updates to keep team knowledge current. Also use wh...
Use for quick self-review of small changes. For comprehensive review or cross-domain changes, dispatch @code-reviewer agent instead.
Use when orchestrating subagents for implementation. Covers when to dispatch vs recall, how to scope tasks, session management, and handoff patterns. Load this before working with any subagent.
REQUIRED before implementing any game feature, scoring logic, state transition, or decision-making. ALL business logic lives in PostgreSQL - frontend is presentation only. Load this to understand where code bel...
Load at session start or when unsure which skill applies. Explains available skills and when to use each. Check this to understand the skill system.
Use BEFORE any implementation to check if specs exist for the capability. Run this first when starting any feature work. Reports: spec exists, no spec, or active change in progress.
Find and consolidate duplicate service implementations in Leavn app - analyze variants, choose winner, update call sites, delete duplicates
Use the gitbug mcp and learn about how code should look
Create clean, descriptive git commits for Leavn app following emoji prefix convention with comprehensive change summaries
Review code and suggest improvements, refactors, and clarifications
默认按已收录数据中的 GitHub 仓库 Stars 排序。Stars 属于来源仓库,同一仓库的多个技能可能共享相同数值;它反映仓库关注度,不代表单个技能的安装量或质量评分。