430 skills · sorted by relevance
Híbrido RNN+Transformer com inferência O(n). Tempo linear, contexto infinito, sem cache KV. Treina como GPT (paralelo), infere como RNN (sequencial). Projeto Linux Foundation AI. Produção em Windows, Office, NeMo. RWKV-7 (março de 2025). Modelos até 14B parâmetros.
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Cursor Cloud Agentにタスクを委託するよう依頼された際に発動。エージェント作成、SSEストリーム監視（stream）、実行キャンセル（cancel）、ステータスポーリング（フォールバック）、Pull Request状態確認、Linear紐付け、レビュー・フォローアップを行う。
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Run the Tamanu release-branch CUTOFF checks when preparing to cut a new release/X.YY branch: confirm the previous release's hotfixes are merged to main, reconcile the commits since the previous release against the "Merged to main" card list from Linear, and scan for data/reporting/schema changes. Use when the user is cutting a Tamanu release and wants to verify the codebase is ready, wants to check main against the previous release branch, or wants to reconcile commits with a Linear "Merged to main" column (they should paste the card list). Handles Tamanu's train-release model (release/X.YY branches vs vX.YY.Z patch tags) and the cherry-pick model where the same logical fix has different SHAs on different branches. Purely git-based — no live database or Canopy access needed. Not for verifying an existing release branch's hotfix integrity (see pre-release-checks) or for deciding which tests to run (see scope-tamanu-release-tests).
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Manage Linear issues, projects, and teams
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Linear multi-agent build pipeline with file hand-offs in production_artifacts/, run after /bdbrainstorm or /grill-me. This is the linear variant — no state.json, no repair loop, no dispatcher graph — distinct from startcycle-graph, which adds durable state and automated escalation. Use when an approved plan should be built, when the user types /startcycle or "run a startcycle", or when you pick a startcycle variant from the situation yourself (no user prompt needed).
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Triage Linear issues and claim work with the Linear MCP tools - find the triage queue or your assigned work, check for duplicates and existing owners, set team/priority/labels, and claim an issue (assign to me, move to In Progress) only after confirming nobody else owns it. Use for "triage the queue", "what should I work on", "claim LIN-123".
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Write an evidence-based status update from Linear data - summarize what shipped, what is in progress, what is blocked or stale for a project, cycle, or a person's issues, and optionally post it as a Linear project status update after the user approves the text. Use for "status for project X", "weekly update", "what moved this cycle".
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Linear: manage issues, projects, teams via GraphQL + curl.
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RNN+Transformer hybrid with O(n) inference. Linear time, infinite context, no KV cache. Train like GPT (parallel), infer like RNN (sequential). Linux Foundation AI project. Production at Windows, Office, NeMo. RWKV-7 (March 2025). Models up to 14B parameters.
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Analyze nonlinear dynamical systems — phase portraits, fixed points, stability analysis, bifurcation diagrams, Poincare sections, Lyapunov exponents, and chaos detection. Use for any autonomous or non-autonomous ODE system where qualitative behavior matters.
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Solve partial differential equations — finite differences, spectral methods, and physics-informed neural networks (PINNs via DeepXDE). Supports 1D/2D/3D, steady/transient, linear/nonlinear PDEs with Dirichlet, Neumann, and periodic boundary conditions.
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Reads, inspects, and writes Flow Cytometry Standard (FCS) files from conventional, spectral, and mass cytometry (CyTOF), and parses FlowJo/Cytobank/Diva workspaces. Covers FCS 2.0/3.0/3.1/3.2 internals ($PnE linear-vs-log, $DATATYPE, $SPILLOVER vs SPILL vs $COMP, $TIMESTEP), channel/parameter metadata, the silent linearize/truncate defaults, and R (flowCore, flowWorkspace, CytoML) plus Python (FlowKit, readfcs) readers. Use when loading flow or mass cytometry data, mapping detector channels to antibodies, extracting the event matrix, choosing a reader, or bridging FCS to the scanpy/AnnData ecosystem before preprocessing.
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Manage Linear issues, projects, and teams via the GraphQL API. Create, update, search, and organize issues. Uses API key auth (no OAuth needed). All operations via curl — no dependencies.
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Mirror issues and status across issue trackers with stable external-ID mapping to avoid duplicates. Load when syncing GitHub and Linear issues, mirroring ticket status, or keeping two trackers in sync. Also triggers on "issue sync", "sync issues", "mirror issues to", "keep Linear and GitHub in sync", or bidirectional issue tracker updates. Requires API access on both sides — stops if credentials missing.
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Reads, inspects, and writes Flow Cytometry Standard (FCS) files from conventional, spectral, and mass cytometry (CyTOF), and parses FlowJo/Cytobank/Diva workspaces. Covers FCS 2.0/3.0/3.1/3.2 internals ($PnE linear-vs-log, $DATATYPE, $SPILLOVER vs SPILL vs $COMP, $TIMESTEP), channel/parameter metadata, the silent linearize/truncate defaults, and R (flowCore, flowWorkspace, CytoML) plus Python (FlowKit, readfcs) readers. Use when loading flow or mass cytometry data, mapping detector channels to antibodies, extracting the event matrix, choosing a reader, or bridging FCS to the scanpy/AnnData ecosystem before preprocessing.
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When the user wants to cut 1D materials optimally, minimize waste in linear cutting, or solve one-dimensional cutting stock problems. Also use when the user mentions "1D cutting," "linear cutting optimization," "rod cutting," "pipe cutting," "beam cutting," "trim loss," "cutting stock problem," "pattern generation," or "column generation for cutting." For 2D problems, see 2d-cutting-stock. For general trim loss, see trim-loss-minimization.
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Query and manage Linear issues, projects, and team workflows.
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Create HTML slide decks for humanities lectures and research presentations, organizing sources, arguments, and evidence. A coordinated navy and warm-yellow template gives the slides a calm, scholarly appearance.
Analyze application and system performance to find bottlenecks, the points that slow processing. Use resource usage and performance data to plan improvements to resource allocation, load balancing, caching, and algorithms, then compare results after changes.
Turn complex goals into actionable plans by mapping dependencies, prioritizing tasks, and allocating time, budget, and people. Supports coordination across multiple agents and revises plans when progress or constraints change.
Analyze networks of people, web pages, or systems using PageRank, a method that scores importance from connections. Identify influential nodes and communities, generate personalized recommendations, and examine communication bottlenecks to guide network improvements.
Design and implement ways for multiple agents or distributed computers to agree on decisions. Covers weighted voting, task allocation, coordination, and protocols that handle faulty or malicious participants, with tools for mathematical analysis.
Reduce data with many features into fewer dimensions using UMAP. Create 2D or 3D views, prepare inputs for clustering, compare parameter settings, and project new samples while checking whether the results remain stable and meaningful.
Use SymPy to simplify expressions, solve equations, and calculate derivatives, integrals, and matrices with exact symbolic results. Specify assumptions, verify solutions, and turn mathematical expressions into numerical functions, source code, or LaTeX output.