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Test whether instructions planted in an agent's long-term memory or searchable knowledge base influence later behavior. Verify both a stored test marker and a resulting change in answers, permissions, or treatment of retrieved documents.
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Create new Feishu cloud documents from Markdown, a text format for structured content. Choose a folder or knowledge library location, and include tables, images, and diagrams in meeting notes or project plans.
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Create or update Claude skills that capture specialized knowledge and repeatable workflows. Guides the organization of instructions, scripts, references, and templates, then covers initialization, validation, and packaging into a distributable skill file.
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Extract a YouTube video’s full transcript and metadata, meaning details such as its title, channel, and like count, through the BrowserAct API. Use the results as source material for summaries, content research, or knowledge bases.
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Assess your Claude Code knowledge through multiple-choice questions with immediate feedback. Choose a quick check or a comprehensive assessment to identify gaps and receive a prioritized learning path, with practice projects included in the comprehensive mode.
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Create or update Claude skills that capture specialized knowledge and repeatable workflows. Guides the organization of instructions, scripts, references, and templates, then covers initialization, validation, and packaging into a distributable skill file.
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Organize papers from Zotero into an Obsidian project knowledge base. The skill separates source notes, research synthesis, and writing outputs, requiring evidence records and source links before findings become claims used in later work.
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Turn specialized knowledge and repeatable workflows into an Agent Skill. Work through concrete usage examples, write SKILL.md, organize reusable scripts and resources, and validate the package before producing a distributable .skill file.
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Set up an Obsidian knowledge base for a research repository containing code and Markdown. It creates project links, planning notes, source inventories, and code summaries, importing structure and summaries while leaving large research artifacts out.
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Coordinate a seven-stage literature review, from defining a research question to collecting and screening papers, building a searchable knowledge database, and producing PRISMA documentation. Specialized agents handle execution, with human approval at key decisions.
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Turn an accepted feature proposal into an implementation specification grounded in existing code. Define scope, explain design decisions, track unresolved questions, and document migration steps and tests, with implementation tasks added when the work is approved for building.
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Document an incident with a sourced timeline, clear user impact, and analysis that separates symptoms, triggers, and underlying causes. Produce a blameless review with action items that specify responsible teams, deadlines, and checkable completion criteria.
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Review whether a proposal, specification, or design decision addresses the right problem and follows from its goals and constraints. Receive prioritized findings with supporting evidence, confidence, and concrete alternatives or questions that would resolve each concern.
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Turn a design problem into an RFC, a proposal for review and discussion. Define who benefits and what changes, compare real alternatives, document drawbacks and open questions, and save a linked, validated draft.
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Use whenever datasets, cloud storage buckets, or data pipelines are mentioned — creating, saving, querying, listing, exploring, deleting, or processing data in S3, GCS, Azure Blob, or local storage. Also use when running any script that may create datasets as a side effect. Maintains a knowledge base at dc-knowledge/ (JSON + markdown). ALWAYS use this skill when the user creates a dataset, saves pipeline output, runs a data script, or references any storage bucket.
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Design any process, idea, problem, or body of knowledge into an ICM (Interpretable Context Methodology) workspace — folder structure as agent architecture — or restructure an existing folder, repo, or vault into one. Use when the user wants to (1) turn a recurring workflow into an agent-runnable folder pipeline, (2) organize scattered notes, files, or knowledge into a library one AI agent can walk, (3) map a team or company as connected context ("context map", "second brain", "team brain", "knowledge base for AI"), (4) audit a codebase or mixed folder into a walkable edit map (objects, processes, change-impact) so later agents can change it without slurping the tree, (5) audit or restructure an existing workspace to ICM conventions, or (6) says "make this an ICM", "ICM this", "map this repo", "audit this folder", "what would a change hit", "build me a workspace", or "structure this for agents".
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Extract facts from meetings and update your knowledge base — person profiles, chronological log, and index. Use when the user asks "ingest my meetings", "update my knowledge base", "extract facts from meetings", "sync meetings to wiki", "backfill knowledge", or wants their PARA/Obsidian/wiki profiles updated from conversation data.
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Build, refresh and query a deterministic code knowledge graph to cut orientation-token cost. Triggers: knowledge graph, graphify, code graph, god nodes, orientation cost, map the codebase, what connects, callers of, blast radius.
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When the user wants to optimize for entity recognition, Knowledge Graph, or entity-based SEO. Also use when the user mentions "entity SEO," "entity optimization," "Knowledge Graph," "Knowledge Panel," "entity signals," "brand entity," "entity linking," "entity relationships," or "entity-first content." For structured data, use schema-markup.
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Confluence expert for spaces, knowledge bases, documentation, page layouts, macros, templates, and Jira-Confluence integration. Use for documentation strategy, space architecture, content organization, and collaborative knowledge management.
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Audit and repair an internal knowledge base — staleness, ownership gaps, orphans, duplication, and findability. Use when the wiki is untrusted, docs are out of date, nobody owns pages, or search returns the wrong answer.
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Comprehensive global knowledge worker salary data with total market value calculations, sector breakdowns, geographic comparisons, and authoritative sources. USE WHEN discussing knowledge worker compensation, salary benchmarking, economic analysis of professional labor markets, or AI impact on wages.
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Design learning tasks built on Ubuntu philosophy emphasising collective knowledge-building and mutual responsibility. Use when fostering collaboration that values community over individual competition.
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Design discipline-specific critical thinking tasks grounded in knowledge-contingent reasoning rather than generic skills. Use when embedding higher-order thinking into subject content.
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