用于【AI科幻】题材下搜索起点中文网等目标平台的同题材 TopN 候选池,先锁定榜单与样本池,再从中收束 3–5 本主样本做四层深拆式竞对分析。作为题材包装层与路由层,负责保留AI科幻标准入口名,补充技术视角、技术针脚、数据链/系统逻辑链、长线系统谜团等题材维度,并明确要求优先强制加载并使用 `通用-分析竞对作品`。关键词:AI科幻竞对分析、AI科幻竞品分析、起点AI科幻榜单、标杆作品拆解、技术悬疑标杆报告。
npx skills add https://github.com/lornshrimp/Lorn.NovelWriteSkills --skill AI科幻-分析竞对作品
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这是题材包装层、兼容入口与路由层。
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通用-分析竞对作品通用-分析竞对作品 另写一套平行共性规则。AI科幻-小说项目初始化(当竞对分析在项目初始化语境下调用时,本 Skill 应与初始化联动执行,产出竞对差距清单写入初始化蓝皮书)通用-分析竞对作品。写作研究/、题材 Prompt、题材 Skill 所沉淀的关注点,转译成本轮竞对维度,而不是只套一层抽象通用壳。通用-分析竞对作品。references/AI科幻竞对分析补充维度.md/init 调用本 Skill 时自动进入初始化模式,产出竞对差距清单写入初始化蓝皮书)AI科幻/竞对分析/作品名-竞对分析报告-YYYY-MM-DD.md通用-分析竞对作品。references/AI科幻竞对分析补充维度.md,再确定本轮AI科幻专项分析点。3–5 本主样本按“市场数据层 → 内容创作层 → 运营策略层 → 受众反馈层”深拆;只有用户明确要求时,才对 Top10 全量逐本重拆。通用-分析竞对作品 的术语口径:榜单位次、均订 / 首订 / 收订比代理信号、本章说 / 书友圈活跃度、老白读者接受度等;本题材层只补AI科幻专项裁判。AI科幻题材的竞对分析中,套路配置的焦点与女频不同——核心在"情节推进类"套路而非"人物关系类":
通用-分析竞对作品 为准。Top10 候选池 → 3–5 本主样本 → 四层深拆 的默认执行口径,以及起点术语口径,也以 通用-分析竞对作品 为准。通用-分析竞对作品,不要长期滞留在题材层。Integration with protocols.io API for managing scientific protocols. This skill should be used when working with protocols.io to search, create, update, or publish protocols; manage protocol steps and materials; handle discussions and comments; organize workspaces; upload and manage files; or integrate protocols.io functionality into workflows. Applicable for protocol discovery, collaborative protocol development, experiment tracking, lab protocol management, and scientific documentation.
Analyzes job descriptions and generates tailored resumes that highlight relevant experience, skills, and achievements to maximize interview chances
Generate Excalidraw diagrams from natural language descriptions. Use when asked to "create a diagram", "make a flowchart", "visualize a process", "draw a system architecture", "create a mind map", or "generate an Excalidraw file". Supports flowcharts, relationship diagrams, mind maps, and system architecture diagrams. Outputs .excalidraw JSON files that can be opened directly in Excalidraw.
Build and distribute Expo development clients locally or via TestFlight
Use when you have a written implementation plan to execute in a separate session with review checkpoints
Data structure for annotated matrices in single-cell analysis. Use when working with .h5ad files or integrating with the scverse ecosystem. This is the data format skill—for analysis workflows use scanpy; for probabilistic models use scvi-tools; for population-scale queries use cellxgene-census.
Benchling R&D platform integration. Access registry (DNA, proteins), inventory, ELN entries, workflows via API, build Benchling Apps, query Data Warehouse, for lab data management automation.
Comprehensive molecular biology toolkit. Use for sequence manipulation, file parsing (FASTA/GenBank/PDB), phylogenetics, and programmatic NCBI/PubMed access (Bio.Entrez). Best for batch processing, custom bioinformatics pipelines, BLAST automation. For quick lookups use gget; for multi-service integration use bioservices.
Take lornshrimp/ai科幻-分析竞对作品 from the repository into ~/.claude/skills for personal
use, or into .claude/skills inside a project.
The agent identifies a skill by the name field in its header. Two skills with the
same name cannot sit side by side — one of them will be ignored.