リサーチ・学習のスキル

Produce a periodic review of a second-brain vault: what was added, which topics are growing, what contradicts what, which questions are still open, and what is worth reading next. Use this skill whenever the user asks for a weekly or monthly review, asks what changed in their vault, what they have been learning about lately, or what they should look at next, and when a scheduled review task fires. Do NOT use for structural linting, for ingesting sources, or for answering a specific factual question.

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Use when writing, rewriting, or improving technical docs (quickstarts, how-tos, tutorials, concept pages, or API references).

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Best practices for systematic research, source evaluation, and evidence gathering

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Guidelines for writing well-structured, cited research reports

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Review a business plan from the perspective of the solo founder who has to actually execute it. Asks the brutal operational questions: Can I build this with my time budget? Can I keep it running? Will my cashflow survive? Outputs a verdict — SHIPPABLE NOW / SHIPPABLE WITH DESCOPE / NEEDS HIRE / WRONG STACK. Use when a plan looks great on paper and you want to know whether a solo operator can actually execute it. Triggered by: 'operator review', 'can I actually do this solo', 'execution reality check', '操盘视角', '我能不能干得动'.

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Manage project learnings — small, atomic, validated patterns that the agent should remember across all skills and sessions. Different from /money-save (which captures full session state); learnings are individual insights that get auto-loaded into every other money-* skill's context. Use when the user has just discovered something worth remembering — a customer pattern, a pricing insight, a channel that works, a failure mode. Triggered by: 'remember this', 'log a learning', 'this is a pattern', 'show learnings', 'what have we learned', '记住这个', '存入经验', '查看经验库'.

日本語の概要は準備中です。原文の説明を表示しています。

Capture or triage small Neva repository and engineering-harness frictions without derailing feature work.

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Deep research and discovery before building something new. Explores local projects for reusable code, researches competitors, reads forums and reviews, analyses plugin ecosystems, investigates technical options, and produces a comprehensive research brief. Three depths: focused (30 min), wide (1-2 hours), deep (3-6 hours). Triggers: 'research this', 'discovery', 'explore the space', 'what should I build', 'competitive analysis', 'before I start building', 'research before coding'. Not for cited fact-checking research reports (a separate harness does those); this is pre-build product discovery.

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After solving a non-trivial problem, detect generalizable learnings and propose skill updates. Always active — applies to every interaction.

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Plan the smallest set of diagnostic, comparison, paper, and appendix figures or tables needed to support verified mathematical-modeling decisions and claims.

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Draft submission-ready mathematical-modeling paper sections from the approved solution package, frozen numbers, human decision ledger, and verified figures without searching scattered exploratory outputs or inventing interpretation.

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Polish mathematical modeling paper drafts for grammar, clarity, formula consistency, hedging calibration, overclaim detection, and contest formatting compliance. Use after paper-section-writer has drafted sections.

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Build and maintain one global mathematical symbol and unit table from the problem frame and active method cards, resolving cross-subquestion conflicts before code or paper work.

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Collect and analyze relevant papers, reports, and reference methods to inform method selection without fabricating references or copying models blindly.

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Manage and verify references for mathematical modeling contest papers, generating BibTeX entries, checking citation completeness, and ensuring all references are traceable to actual sources.

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Format reference for Power BI Enhanced Report (PBIR) JSON schemas and patterns. Automatically invoke when the user asks about PBIR JSON structure, visual.json properties, PBIR expressions, objects vs visualContainerObjects, theme inheritance, conditional formatting patterns, extension measures, bookmarks, field references, filter formatting, query roles, PBIR page structure, report wallpaper, or any PBIR metadata format question.

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Transforms workflow to use Manus-style persistent markdown files for planning, progress tracking, and knowledge storage. Use when starting complex tasks, multi-step projects, research tasks, or when the user mentions planning, organizing work, tracking progress, or wants structured output.

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When the user wants to find information sources for content ideation, competitor monitoring, or industry tracking. Also use when the user mentions "research sources," "information sources," "content ideation," "industry monitoring," "competitor monitoring," "market intelligence," "content research," or "topic research." For keywords, use keyword-research.

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When the user wants to improve E-E-A-T, add trust signals, or optimize for expertise and authority. Also use when the user mentions "E-E-A-T," "E-E-A-T signals," "experience expertise authority trust," "author bio," "YMYL," "trust signals," "expertise signals," "authority signals," "citations," "references," or "credibility." For headings, use heading-structure.

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When the user wants to analyze competitors for SEO, content, backlinks, or positioning. Also use when the user mentions "competitor analysis," "competitor research," "competitor keywords," "competitor backlinks," "link gap," "content gap," "competitor content," "competitive analysis," or "competitor comparison." For content roadmap, use content-strategy.

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When the user wants to plan, implement, or optimize student and education discount programs. Also use when the user mentions "student discount," "education discount," "student plan," "for students," ".edu discount," "academic pricing," "student verification," "SheerID," "UNiDAYS," or "education program." For startup pricing page, use startups-page-generator.

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Plan a user research questionnaire, or turn collected responses into evidence-linked input for a PRD, with the AI Product Development Toolkit's research prompts.

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社会情感学习（SEL）专家系统——基于CASEL框架的完整知识体系与实践指南。 涵盖五大核心能力（自我意识/自我管理/社会意识/人际关系/负责任决策）、 课程设计、教学策略、评估工具及全球本土化实践。 触发词：「SEL」「社会情感学习」「情绪教育」「CASEL」「社交技能训练」 适用场景：教育工作者、家长、学校管理者、教育研究者

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ClawTeam导演智囊团——基于ClawTeam多智能体框架的世界著名导演协同创作系统。 整合31位全球顶级导演的风格思想，通过多智能体协作机制（顺序链、辩论投票、主席团模式） 辅助剧本创作、影像风格设计和叙事决策。 触发词：「导演智囊团」「ClawTeam」「多导演协作」「剧本创作」「影像风格」 适用场景：编剧、导演、创意策划、影视教育、AI影像创作

日本語の概要は準備中です。原文の説明を表示しています。