Results for “knowledge base”

Build a detailed buyer persona or customer profile. Use when the user says "write a persona", "build a buyer persona", "customer persona for [product]", "who is our target customer", "ICP document", "ideal customer profile", "define our buyer", "who are we building this for", "customer profile", "audience profile", or wants to create a documented, research-backed profile of who buys the product and why. For sourcing the real research behind a persona, see customer-research. For segment and firmographic definition, see icp-research. For writing it into the knowledge base, see brand-context.

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Turn raw customer material into evidence-backed personas and verbatim voice-of-customer language. Two modes - analyse sources the user already has (call transcripts, support tickets, survey responses, sales notes, reviews), or source new material from public places customers actually talk. Produces quoted pains, objections, and switch triggers that other skills consume, never invented ones. Use when the user says "customer research", "voice of customer", "what do our customers actually say", "we need real quotes", "analyse these call transcripts", "read our support tickets", "build a persona from data", "find what customers complain about", or when a persona is marked provisional. For structuring the finished persona into the knowledge base, see brand-context. For the JTBD persona template itself, see customer-persona.

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Turn a verified Salesforce research packet into a concise, role-aware learning brief with clear objectives, concept sequencing, worked examples, release caveats, checks for understanding, and citations mapped to claims. Trigger keywords: teach me Salesforce, explain Salesforce concept, create learning brief, Salesforce study guide, role-based lesson. NOT for open-ended source discovery or freshness verification — use architect/salesforce-learning-research first. NOT for generating production metadata or changing an org.

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ออกแบบ Notion workspace — schema database, relation, automation, PARA method สำหรับ knowledge worker

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Answer an explicitly vault-scoped question from an Obsidian wiki without changing it. Use when the user selects the vault as the evidence source: query the wiki, query quick, query deep, explain from the wiki, summarize the vault, find in wiki, search the wiki, or based on the wiki. Do not route ordinary general-knowledge questions here.

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FLOW framework integration: evidence-led SEO using the Find → Leverage → Optimize → Win loop. Surfaces stage-specific AI prompts from the FLOW knowledge base (41 prompts, CC BY 4.0). Use when user says "FLOW", "FLOW framework", "seo flow", "evidence-led SEO", "find leverage optimize win", or wants stage-specific SEO prompts.

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FLOW framework integration for bloggers. Evidence-led content workflow using the Find, Optimize, Win loop with stage-specific AI prompts from the FLOW knowledge base (30 blog-applicable prompts, adapted from FLOW under CC BY 4.0). Use when user says "FLOW framework", "blog flow", "/blog flow", "evidence-led blogging", or "find optimize win", or asks for stage-specific blog prompts. Not for generic prompt writing.

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Extract tacit knowledge through non-obvious microquestions — things only the user knows that can't be found in code, docs, or research. Use when you're about to guess at intent, context, or constraints during SAFEWORD's understanding flow. Also use when user says 'ask me', 'what do you need to know', or when another skill (bdd, brainstorm, debug) needs user context before proceeding. Do NOT use for questions answerable by reading the codebase or searching the web.

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Add a short, project-specific rule, convention, or override to .unikit/RULES.md — the quick-capture inbox for this project's rules (common rules always load; topic files in .unikit/rules/ load when the work matches), automatically loaded by /unikit-implement (later promotable via /unikit-memory migrate-rules). Works only with a rule typed as a prompt — it does NOT read files, folders, URLs, or PDFs. Cross-checks against the knowledge base (RULES_INDEX.md) to avoid duplicating core/stack entries. Use for fast, one-line conventions and corrections: "add a rule", "remember this", "convention", "always do X", "never use Y", "from now on do Z", or when the user corrects agent behavior and wants it remembered; also "split the rules into topics" (optimise), "clean up the rules" (prune), "shorten RULES.md" (compact). If the user points to a source (file, folder, URL, PDF, article, book) or wants to research/document framework usage, use /unikit-memory; for architecture decisions use ARCHITECTURE.md.

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Learn project rules from accumulated fix patches in .unikit/code/patches/. Analyzes past mistakes, extracts prevention points, classifies each as a coding rule (→ RULES.md) or a per-skill workflow rule (→ skill-context), and proposes them for approval. Use when the user wants to turn past fixes into rules — "evolve", "evolve the rules", "learn from past mistakes", "learn from the fixes", "analyze the patches", "what rules should we add from recent fixes". Best run after several /unikit-fix sessions have left patches behind. This derives rules from accumulated patch history — to add a single rule by hand use /unikit-rules, and to promote mature RULES.md entries into the knowledge base use /unikit-memory migrate-rules.

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(builtin) Initialize hierarchical AGENTS.md knowledge base

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Personal knowledge base for capturing and retrieving information about people, places, restaurants, games, tech, events, media, ideas, and organizations. Use when: user mentions a person, place, restaurant, landmark, game, device, event, book/show, idea, or company. Trigger phrases: "remember", "note that", "met this person", "visited", "played", "what do I know about", etc. Brain entries take precedence over daily logs for named entities.

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Manages intent — features, enhancements, bugs and the reasoning behind them — recorded as prose in the knowledge base with a lifecycle. Use when capturing new work, moving work through backlog, refinement or implementation, releasing or cancelling work, or asking what is pending, in flight, or no longer valid.

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Elite AI context engineering specialist mastering dynamic context management, vector databases, knowledge graphs, and intelligent memory systems.

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Agent Skill design knowledge base — mechanisms, philosophy, patterns, pitfalls. Use when: designing new skills, reviewing skill quality, or deciding whether something should be a skill.

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Project documentation structure — standard proj-[name]/ layout with ADRs, stories, and operations guides. Use when: initializing docs for a new project, recording architecture decisions, or maintaining project knowledge bases.

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Implement semantic vector search with AgentDB for intelligent document retrieval, similarity matching, and context-aware querying. Use when building RAG systems, semantic search engines, or intelligent knowledge bases.

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Use the project wiki as RAG knowledge source — search wiki pages to answer codebase questions before exploring raw files

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Use when planning or upgrading an internal skill/workflow for business operations, especially when turning a messy idea into a structured skill plan, migration plan, acceptance checklist, or packaging decision. Particularly useful for Obsidian knowledge base consolidation, workspace migration, content library cleanup, and integrating multiple workbenches into one operating system.

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Expert-level inorganic chemistry knowledge. Use when working with coordination chemistry, transition metals, crystal field theory, organometallics, main group chemistry, solid state chemistry, acid-base theory, or inorganic reaction mechanisms. Also use when the user mentions 'coordination complex', 'ligand', 'crystal field', 'transition metal', 'oxidation state', 'organometallic', 'Lewis acid', 'VSEPR', 'symmetry', 'point group', 'solid state', or 'catalysis'.

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Use for any question about a codebase, its architecture, file relationships, or project content — especially when graphify-out/ exists, where the question should be treated as a graphify query first. Turns any input (code, docs, papers, images, videos) into a persistent knowledge graph with god nodes, community detection, and query/path/explain tools.

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Continuously detect recurring UI/UX concepts during frontend discussions, track conversation-wide recurrence, and register repeated concepts as structured knowledge assets in a Notion database via MCP. Activates when UI/UX principles, heuristics, laws, or design patterns recur during frontend work, or on manual @ux commands (@ux save, @ux skip, @ux link).

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This skill should be used when creating comprehensive project plans for system development or implementation projects. Use this skill when you need to create Project Charters, Project Plans, WBS, Gantt Charts, RACI matrices, Risk analysis, or other PMBOK-aligned project management artifacts. Outputs are in Markdown format with Mermaid diagrams for visualizations. Leverages comprehensive PM knowledge base in references/ directory (544KB, 11 files) including PMBOK standards, Software/SaaS best practices, IT industry guidance, and specialized PM methodologies.

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ローカルMarkdownファイルによる個人ナレッジベースを管理する。メモ・記録・ノートの保存、検索・参照、会議メモの構造化、既存ファイルの取り込みに使用する。Do NOT use for プロジェクトのソースコードやSDDドキュメントの管理。

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