679건 · 관련도순
Handle standalone administration tasks on a Tuwunel Matrix server, including registering users, creating rooms, managing membership, and uploading files. It also covers sending files to an administrator and identifies mention and room-joining requirements that affect Workers.
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Connect NanoClaw to Matrix rooms and direct messages through Chat SDK. The skill installs and registers the adapter, applies a compatibility patch, configures bot credentials, and checks the build and channel registration.
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Organize TeamHarness project and task files in shared workspaces, synchronize changes, and submit deliverables. It also guides publishing files to Matrix chat rooms and explaining file access through other requester channels.
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Identify whether a Matrix chat room is a request source or a task workspace, then create or reuse a project-specific task room. The skill also handles worker invitation details and preserves information about where requests originated.
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🇺🇸 UGC Matrix Growth Playbook — Scale user-generated content with AI + real creators. Complete SOP for UGC flywheel, creator recruitment, incentive design, multi-platform publishing. Proven at CPM $0.5, $10M ARR in 60 days with 70M impressions. Includes a full anonymized client case study. 🇨🇳 UGC矩阵号增长实操手册 — AI+真人创作者规模化用户生成内容。完整的UGC飞轮SOP、创作者招募、激励机制设计、多平台分发策略。已验证CPM $0.5，60天$1000万ARR，7000万曝光。含完整客户案例拆解（已脱敏）。 🇯🇵 UGCマトリックス成長プレイブック — AI＋リアルクリエイターでUGCをスケール。フライホイールSOP、クリエイター採用、インセンティブ設計、マルチプラットフォーム配信。CPM $0.5、60日で$10M ARR、7000万インプレッション実証済み。匿名化クライアント事例付き。 🇰🇷 UGC 매트릭스 성장 플레이북 — AI + 실제 크리에이터로 UGC 스케일링. 플라이휠 SOP, 크리에이터 모집, 인센티브 설계, 멀티플랫폼 배포. CPM $0.5, 60일 $10M ARR, 7000만 노출 검증 완료. 익명화된 클라이언트 사례 포함. Triggers: "UGC" | "UGC matrix" | "user generated content" | "creator program" | "creator economy" | "AI UGC" | "matrix accounts" | "矩阵号" | "UGC运营" | "创作者招募" | "UGC Program" | "content matrix" | "TikTok UGC" | "Instagram UGC"
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Guides communication in Matrix agent teams by choosing recipients, rooms, and when to mention someone. It covers task notifications and progress reports, helping agents avoid duplicate assignments and send concrete updates to the appropriate requester.
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Check current AgentTeams membership, worker status, and messaging identifiers through the agt CLI. Use the returned team metadata to prepare task assignments, contact the appropriate rooms, and manage worker readiness, waking, or sleeping.
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Guide agent replies in Matrix chat rooms, including when to mention a coordinator, report completion, raise blockers, or answer questions. The rules limit repetitive acknowledgments and stop exchanges that add no new task, question, or decision.
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Deliver TeamHarness messages to the correct room, channel, or session using recorded reply routes. It covers task handoffs and requester reports, while defining when to reply directly or suppress acknowledgements that could cause message loops.
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Improve MNN's Vulkan backend by separating CPU scheduling bottlenecks from GPU computation costs. It guides operator and shader changes, new feature integration with compatibility fallbacks, and device testing to verify both correctness and end-to-end performance.
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Look up current AgentTeams membership, Worker runtime state, and identity details when the conversation lacks them. The skill uses the agt command-line tool to confirm coordinator identities, team context, and room information without relying on old records.
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Stores and operates on sparse expression matrices for single-cell and large bulk RNA-seq, covering dgCMatrix/dgRMatrix/dgTMatrix when-each-is-fast, the dgCMatrix (CSC, R) <-> CSR (Python) implicit transpose, AnnData (cells-rows) <-> SingleCellExperiment (cells-cols) orientation flip, HDF5/h5ad vs Zarr cloud-native shift, HDF5SummarizedExperiment + DelayedArray for out-of-memory bulk, scanpy backed mode for large h5ad, the ~10-15% density crossover where dense beats sparse, 10X format proliferation (MTX vs CellRanger H5 vs h5ad), the dense-conversion memory blow-up, and Dask + Zarr for consortium-scale matrices. Use when choosing sparse format, working with single-cell-sized matrices, importing/exporting 10X, debugging R/Python interop transposes, processing matrices too large for RAM, or building cloud-native pipelines.
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Create a requirements traceability matrix linking requirements to design, test, and delivery. Use when the user says "traceability matrix", "RTM", "requirements traceability", "link requirements to tests", "trace requirements", "coverage matrix", "are all requirements tested", "requirements coverage", "forward traceability", "backward traceability" - even if they don't explicitly say "traceability matrix".
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Build a weighted decision matrix to evaluate options. Use when the user says "decision matrix", "compare options", "weighted scoring", "which option should we choose", "evaluate alternatives", "Wiegers priority matrix", "force field analysis", "decision table", "trade-off analysis", "option comparison" - even if they don't explicitly say "decision matrix".
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Stores and operates on sparse expression matrices for single-cell and large bulk RNA-seq, covering dgCMatrix/dgRMatrix/dgTMatrix when-each-is-fast, the dgCMatrix (CSC, R) <-> CSR (Python) implicit transpose, AnnData (cells-rows) <-> SingleCellExperiment (cells-cols) orientation flip, HDF5/h5ad vs Zarr cloud-native shift, HDF5SummarizedExperiment + DelayedArray for out-of-memory bulk, scanpy backed mode for large h5ad, the ~10-15% density crossover where dense beats sparse, 10X format proliferation (MTX vs CellRanger H5 vs h5ad), the dense-conversion memory blow-up, and Dask + Zarr for consortium-scale matrices. Use when choosing sparse format, working with single-cell-sized matrices, importing/exporting 10X, debugging R/Python interop transposes, processing matrices too large for RAM, or building cloud-native pipelines.
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Stores and operates on sparse expression matrices for single-cell and large bulk RNA-seq, covering dgCMatrix/dgRMatrix/dgTMatrix when-each-is-fast, the dgCMatrix (CSC, R) <-> CSR (Python) implicit transpose, AnnData (cells-rows) <-> SingleCellExperiment (cells-cols) orientation flip, HDF5/h5ad vs Zarr cloud-native shift, HDF5SummarizedExperiment + DelayedArray for out-of-memory bulk, scanpy backed mode for large h5ad, the ~10-15% density crossover where dense beats sparse, 10X format proliferation (MTX vs CellRanger H5 vs h5ad), the dense-conversion memory blow-up, and Dask + Zarr for consortium-scale matrices. Use when choosing sparse format, working with single-cell-sized matrices, importing/exporting 10X, debugging R/Python interop transposes, processing matrices too large for RAM, or building cloud-native pipelines.
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Stores and operates on sparse expression matrices for single-cell and large bulk RNA-seq, covering dgCMatrix/dgRMatrix/dgTMatrix when-each-is-fast, the dgCMatrix (CSC, R) <-> CSR (Python) implicit transpose, AnnData (cells-rows) <-> SingleCellExperiment (cells-cols) orientation flip, HDF5/h5ad vs Zarr cloud-native shift, HDF5SummarizedExperiment + DelayedArray for out-of-memory bulk, scanpy backed mode for large h5ad, the ~10-15% density crossover where dense beats sparse, 10X format proliferation (MTX vs CellRanger H5 vs h5ad), the dense-conversion memory blow-up, and Dask + Zarr for consortium-scale matrices. Use when choosing sparse format, working with single-cell-sized matrices, importing/exporting 10X, debugging R/Python interop transposes, processing matrices too large for RAM, or building cloud-native pipelines.
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Analyze large matrices before solving linear systems. Check structure and numerical stability, recommend preprocessing and solver settings, estimate selected solution values without a full solve, and assess convergence, memory use, and computational cost.
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Design a role permission matrix showing which business areas each role should view or edit, including confidentiality levels. Get a review workflow and, on request, empty CSV templates, SQL table definitions, JSON Schema, or Notion mappings.
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Plan and measure defensive deception operations with MITRE Engage. Connect decoy systems and credentials to specific attacker techniques, define measurable objectives, and document operating boundaries, response procedures, and criteria for assessing results.
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Compare growth options across existing and new products and markets using the Ansoff Matrix, a four-part planning framework. Assess opportunities, resources, competition, and risks, then develop market launch plans and a phased roadmap for priority options.
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Compare business growth options across existing and new products and markets. The skill connects each option to documented demand signals, rates its risk, and recommends an order of action with the assumption that could change it.
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Provides delayed computation of a matrix of residuals after fitting a linear model to each column of an input matrix. Also supports partial computation of residuals where selected factors are to be preserved in the output matrix. Implements
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Guides building a multi-jurisdiction privacy compliance matrix for organisations operating across multiple countries. Covers common requirements identification, jurisdiction-specific deltas, gap analysis, and harmonised control frameworks. Keywords: multi-jurisdiction, compliance matrix, harmonised controls, gap analysis, jurisdiction mapping.
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