搜索文档、Skill 和 MCP
「编码与调试」分类共 449 个 Skill，按仓库 star 排序。分类自动生成，仅供参考。
vibeeval/vibecosystem532Framework for measuring and tracking agent response quality over time. Detects regressions before they reach production. Use when evaluating agent changes, auditing quality, or establishing performance baselines.
vibeeval/vibecosystem532Agent ve skill dosyalarinin yapisal dogrulamasi. Frontmatter kontrol, naming convention, zorunlu bolum kontrolu, tutarlilik denetimi. Yeni agent/skill eklendiginde veya mevcut dosyalar duzenlediginde otomatik calistirilir.
vibeeval/vibecosystem532AST-based code search and refactoring via ast-grep MCP
vibeeval/vibecosystem532Backend architecture patterns, API design, database optimization, and server-side best practices for Node.js, Express, and Next.js API routes.
ancoleman/ai-design-components525Strategic guidance for designing modern data platforms, covering storage paradigms (data lake, warehouse, lakehouse), modeling approaches (dimensional, normalized, data vault, wide tables), data mesh principles, and medallion architecture patterns. Use when architecting data platforms, choosing between centralized vs decentralized patterns, selecting table formats (Iceberg, Delta Lake), or designing data governance frameworks.
ancoleman/ai-design-components525Debugging workflows for Python (pdb, debugpy), Go (delve), Rust (lldb), and Node.js, including container debugging (kubectl debug, ephemeral containers) and production-safe debugging techniques with distributed tracing and correlation IDs. Use when setting breakpoints, debugging containers/pods, remote debugging, or production debugging.
ancoleman/ai-design-components525When designing distributed systems for scalability, reliability, and consistency. Covers CAP/PACELC theorems, consistency models (strong, eventual, causal), replication patterns (leader-follower, multi-leader, leaderless), partitioning strategies (hash, range, geographic), transaction patterns (saga, event sourcing, CQRS), resilience patterns (circuit breaker, bulkhead), service discovery, and caching strategies for building fault-tolerant distributed architectures.
ancoleman/ai-design-components525API design and implementation across REST, GraphQL, gRPC, and tRPC patterns. Use when building backend services, public APIs, or service-to-service communication. Covers REST frameworks (FastAPI, Axum, Gin, Hono), GraphQL libraries (Strawberry, async-graphql, gqlgen, Pothos), gRPC (Tonic, Connect-Go), tRPC for TypeScript, pagination strategies (cursor-based, offset-based), rate limiting, caching, versioning, and OpenAPI documentation generation. Includes frontend integration patterns for forms, tables, dashboards, and ai-chat skills.
ancoleman/ai-design-components525Implement and maintain compliance with SOC 2, HIPAA, PCI-DSS, and GDPR using unified control mapping, policy-as-code enforcement, and automated evidence collection. Use when building systems requiring regulatory compliance, implementing security controls across multiple frameworks, or automating audit preparation.
VILA-Lab/FigMirror521Archive a completed change in the experimental workflow. Use when the user wants to finalize and archive a change after implementation is complete.
skydoves/compose-performance-skills514Use this skill to run an end-to-end Jetpack Compose performance audit when the symptom is broad ("the app feels sluggish", "scroll is rough everywhere", "we're starting a perf sprint", "what should we fix first?"). Orchestrates the four-phase Measure → Diagnose → Fix → Verify loop by sequencing the 25 focused skills (release-mode setup, R8, Baseline Profiles, Compose Compiler reports, stability inference, Layout Inspector, `@TraceRecomposition`, stabilization, strong skipping, phase-deferral, derivedStateOf, lazy layouts, lazy prefetch, Modifier.Node, modifier ordering, flow collection, effects, CI gates, hot-reload) and produces a written audit report with Before/After Macrobenchmark numbers. Use when the developer wants a perf sprint kickoff, a pre-release perf gate, onboarding to a perf-troubled codebase, or a written deliverable. Use when the user mentions "audit", "perf review", "perf sprint", "where do I start", or has no specific symptom yet.
skydoves/compose-performance-skills514Use this skill to find which Jetpack Compose composables are recomposing and why, using Android Studio Layout Inspector recomposition counts and skip counts, the per-parameter Argument Change Reasons (Changed / Unchanged / Uncertain / Static / Unknown) introduced in Android Studio Hedgehog and later, and runtime `@TraceRecomposition` from `compose-stability-analyzer` for production-like measurement. Walks through enabling counts, mapping each Argument Change Reason to a fix, and confirming the result in a release build. Use when the developer says "this should be skipping but isn't", "I want to see recomposition counts", asks what "Uncertain" or "Unknown" means in the inspector, or needs to confirm a stability or strong-skipping fix actually worked end-to-end.
JetBrains/thinkrail514Use when asked to create the initial spec graph for an existing codebase that has source code but no specs. Normally reached via setting-up-a-project.
skydoves/compose-performance-skills514Use this skill to fix scroll jank, lost item state, and broken animateItem() animations in LazyColumn, LazyRow, LazyVerticalGrid, and LazyHorizontalGrid. Covers stable item keys, contentType for mixed-type feeds, Modifier.animateItem() requirements, hoisting modifier chains and painters out of the items lambda, and validating item composable stability. Use when the developer mentions LazyColumn jank, dropped frames while scrolling, items losing scroll state on insert/remove/reorder, mixed feeds of cards/headers/ads feeling sluggish, animateItem() not animating, RecyclerView view-type analog, key parameter, or contentType parameter. The prefetch-window tuning lives in a sibling skill.
coco-research/coco511Use when designing a new REST or GraphQL API, reviewing an API spec before implementation, setting team API standards, or migrating REST to GraphQL. Covers resources, HTTP semantics, pagination, error handling, and pitfalls.
coco-research/coco511Use when implementing, reviewing, or debugging Apple Liquid Glass: iOS 26+ adoption, Regular vs Clear variants, tinting, scroll edge effects, or an iOS-native redesign review.
tt-a1i/simplify-codebase505Simplification audit or authorized codebase simplification whose stated objective is to remove accidental complexity. Use for evidence-backed deletion or consolidation of dead code, duplicate state, redundant APIs or layers, ownerless abstractions, obsolete compatibility or design records, and over-engineering in any language; also use for 代码简化 or 熵回收. Do not use for general code review, onboarding, style-only refactoring, or performance tuning.