“complete”的搜索结果

Use when a task requires exhaustive unabridged output, complete files, or strict prevention of placeholders and skipped code.

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Generate two complementary onboarding documents that together give any engineer — from newcomer to principal — a complete understanding of a codebase. Use when user asks for onboarding docs or getting-started guides, user runs /deep-wiki, or user wants to help new team members understand a codebase.

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Scanpy is a scalable Python toolkit for analyzing single-cell RNA-seq data, built on AnnData. Apply this skill for complete single-cell workflows including quality control, normalization, dimensionality reduction, clustering, marker gene identification, visualization, and trajectory analysis.

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Complete toolkit for senior architect with modern tools and best practices.

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Generate complete solutions for specific Dataverse SDK use cases with architecture recommendations

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Ensure OpenAPI specs define consistent request/response schemas, error model, auth, pagination, and backward compatibility.

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Verifies bug fixes are correct and complete by tracing callers, checking imports/exports, validating path resolution, and confirming no regressions. Does the code work? Use when reviewing code changes for functional correctness.

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Complete Flutter SDK installation, IDE configuration, and troubleshooting guide for Linux, macOS, and Windows. Use for installing Flutter SDK from scratch, configuring PATH environment variables across platforms, setting up VS Code/Android Studio/IntelliJ IDEA with Flutter plugins, resolving 'flutter command not found' errors, fixing flutter doctor warnings and errors, troubleshooting Android SDK/NDK installation issues, configuring Xcode and CocoaPods on macOS, installing Visual Studio C++ build tools on Windows, resolving PATH conflicts and SDK path issues, fixing network/proxy setup problems, debugging IDE plugin activation, configuring emulators and simulators, handling platform-specific build errors, resolving dependency conflicts, fixing certificate and signing issues, troubleshooting hot reload failures, and verifying successful installation with flutter doctor diagnostics.

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Break a user interface under real-world conditions across responsiveness, hostile content, interaction states, accessibility, network failure, interruption, and complete user journeys, reporting observable user harm with evidence rather than aesthetic opinion. Use whenever the user wants to stress-test a UI, verify responsive and edge-case behaviour, inspect loading/error/empty/recovery states, review a flow for friction, or find where an interface fails under reality. Part of the audit suite; inherits the shared constitution while its own job is proving observable user harm.

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Use this skill whenever the user asks to inspect, audit, review, assess, or evaluate a codebase/project for maintainability, extensibility, architecture, reliability, security, testing, engineering quality, or AI-agent/prompt/tooling risks. Also use this when invoked by `/inspect`. It performs a read-only, evidence-backed, multi-agent project inspection with complete file coverage, per-dimension scoring, blunt technical findings, and explicit degraded-mode disclosure.

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Use when creating decision-complete plans through grounding, capped clarification, subagent delegation, and critic iteration.

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Create professional, visually excellent presentation slides in Marp Markdown format. Use this skill when the user asks to: - Create a presentation, slides, deck, slideshow, or プレゼン / スライド - Write or generate slides about a specific topic - Make a Marp .md file for presenting Produces complete, ready-to-render .md files with embedded custom CSS theme, narrative structure, and polished visual design. Supports Japanese and English content.

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Complete App Store Optimization (ASO) toolkit for researching, optimizing, and tracking mobile app performance on Apple App Store and Google Play Store

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Classify target IA shard for BE extraction, load stack skills, and produce a complete referenced-material inventory

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Author FE spec files, update indexes/tracker, run deepening and ambiguity gates, and enforce navigation completeness before plan-phase handoff

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Orchestrate backend spec production from completed IA shards through classify and write passes with mandatory ambiguity gates

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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 claims, always.

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Execute code-quality gates for a completed phase including tests, coverage, lint, types, build, CI/CD, staging, migrations, and spec coverage

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Compile architecture draft into dated architecture design and engineering standards with rubric-complete quality gates

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Validate ideation completeness through constraints, exhaustion, rubric checks, and output compilation

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Complete WhatsApp management for OpenClaw agents: per-conversation memory (groups + DMs), unanswered message tracking, loop prevention, and multi-PA coordination. Use when: tracking conversation context, recalling past decisions, finding unanswered messages, or preventing echo/duplicate message loops.

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Orchestrator for the full academic research pipeline: research -> write -> integrity check -> review -> revise -> re-review -> re-revise -> final integrity check -> finalize. Coordinates deep-research, academic-paper, and academic-paper-reviewer into a seamless 10-stage workflow with mandatory, coverage-bounded integrity checks, two-stage peer review, and auditable quality-assurance artifacts. Triggers on: academic pipeline, research to paper, full paper workflow, paper pipeline, end-to-end paper, research-to-publication, complete paper workflow, 연구부터 논문까지, 연구 주제 설정부터 논문 완성까지, 논문 전체 워크플로.

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Guides MongoDB users through implementing and optimizing Atlas Search (full-text), Vector Search (semantic), and Hybrid Search solutions. Use this skill when users need to build search functionality for text-based queries (autocomplete, fuzzy matching, faceted search), semantic similarity (embeddings, RAG applications), or combined approaches. Also use when users need text containment, substring matching ('contains', 'includes', 'appears in'), case-insensitive or multi-field text search, or filtering across many fields with variable combinations. Provides workflows for selecting the right search type, creating indexes, constructing queries, and optimizing performance using the MongoDB MCP server.

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Generate read-only MongoDB queries (find) or aggregation pipelines using natural language, with collection schema context and sample documents. Use this skill whenever the user asks to write, create, or generate MongoDB queries, wants to filter/query/aggregate data in MongoDB, asks "how do I query...", needs help with query syntax, or discusses finding/filtering/grouping MongoDB documents. Also use for translating SQL-like requests to MongoDB syntax. Does NOT handle Atlas Search ($search operator), vector/semantic search ($vectorSearch operator), fuzzy matching, autocomplete indexes, or relevance scoring - use search-and-ai for those. Does NOT analyze or optimize existing queries - use mongodb-query-optimizer for that. Does NOT handle aggregation pipelines that involve write operations. Requires MongoDB MCP server.

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