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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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Linear: manage issues, projects, teams via GraphQL + curl.
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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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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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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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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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为人文学科课程与研究报告制作HTML幻灯片，梳理资料、论点和依据，并以深海军蓝与暖黄色营造沉静的学术视觉风格。
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.
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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.
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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.
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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.
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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.
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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.
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Plan and document studies that assess whether an analytical procedure suits its intended use. Select the governing framework, evaluate calibration, accuracy, precision, and detection limits, and compare methods using acceptance criteria defined before data collection.
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Design and build an OpenMAIC lesson series using a spiral curriculum: core ideas return with deeper explanations, new representations, and unfamiliar applications. It maps conceptual growth across lessons and checks that revisits add understanding.
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Calculate how to divide serving memory between recurrent state and KV cache, two memory pools used by hybrid models. Use startup logs and workload settings to recommend a ratio, estimate concurrency, and identify the limiting pool.
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Analyze scheduled token releases, their recipients, and trading volume to estimate potential selling pressure. Review project treasury holdings, operating runway, and token supply growth to assess funding sustainability and the effect of dilution on staking yields.
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Develop an eight-part article series examining one company's competitive strengths, earnings, assets, management, and valuation. Review figures, sources, accounting definitions, and claims across the series to prepare consistent articles for public publication.
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Model trading costs and execution assumptions in backtests, including slippage, the gap between expected and simulated fill prices. Compare price impact, fees, execution delays, and order splitting to assess how assumptions affect strategy results.
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