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概要と使いどころ
Comprehensive PDF manipulation toolkit for extracting text and tables, creating new PDFs, merging/splitting documents, and handling forms. When Claude needs to fill in a PDF form or programmatically process, generate, or analyze PDF documents at scale.
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Applies the engineering and research philosophies of Jeff Dean, Chief Scientist at Google DeepMind and Google Research. Reach for this skill whenever you are designing large-scale distributed systems, optimizing latency and energy efficiency, or making architectural decisions about machine learning infrastructure. It should trigger automatically for topics involving hardware-ML co-design, model distillation, sparse activation, massively multi-task models, or scaling systems by 5x to 10x. Use this skill to evaluate system bottlenecks, transition from specialized to unified models, and optimize experimental velocity. Apply his mental models to avoid premature 100x scaling and to treat AI models as reasoning engines rather than memorization databases.
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Design, derive, optimize, explain, and diagnose cinematic Eastern xianxia camera direction, storyboards, motion choreography, pacing, continuity locks, keyframes, and per-shot image-to-video prompts. Use for 仙侠运镜、镜头语言、分镜、推拉摇移、跟拍、环绕、航拍、打斗追逐、情绪镜头、首尾帧、视频提示词、参考视频诊断, when users ask “怎么运镜/不会运镜/给案例/帮我改运镜”, or when an input contains invalid, contradictory, physically implausible, non-camera, or off-topic instructions that need actionable feedback. Support 16:9, 21:9, 4:3, 3:2, 4:5, and 9:16; default to 30 seconds, 16:9, six shots, narrative-adaptive pacing, epic scale, and selective high saturation when unspecified.
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Define production-ready visual intent for Blender scenes and standalone assets, including focal hierarchy, depth layers, visual flow, scale and repetition rhythm, camera mobility, representation fidelity, and performance budgets. Use for original or reference-guided Blender work before construction choices are executed, especially environments, architecture, products, hero assets, or scenes whose modeling quality depends on coordinated spatial design rather than isolated objects.
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Build, calibrate, layer, and validate production Blender materials including bare and coated metal, brushed steel, rust, aged and wet wood planks, stone, concrete, plastic, glass, fabric, water, dirt, moss, and wetness. Use when material identity, UV direction, real-world texture scale, PBR channel handling, roughness response, anisotropy, normal/bump/displacement, transmission, volume absorption, aging, or surface layering determines realism.
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Intelligent code refactoring using IDE-level tools (rename, find-references, go-to-definition), AST-aware pattern matching, and TDD verification. Use for safe, large-scale refactoring with precision.
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Generate concise summaries of source code at multiple scales. Use when users ask to summarize, explain, or understand code - whether it's a single function, a class, a module, or an entire codebase. Handles function-level code by explaining intention and core logic, and large codebases by providing high-level overviews with drill-down capabilities for specific modules.
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Design scale-adaptive game architecture with engine systems and networking. Use when the user says "game architecture" or "design architecture"
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WordPress performance code review and optimization analysis. Use when reviewing WordPress PHP code for performance issues, auditing themes/plugins for scalability, optimizing WP_Query, analyzing caching strategies, checking code before launch, or detecting anti-patterns, or when user mentions "performance review", "optimization audit", "slow WordPress", "slow queries", "high-traffic", "scale WordPress", "code review", "timeout", "500 error", "out of memory", or "site won't load". Detects anti-patterns in database queries, hooks, object caching, AJAX, and template loading.
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React composition patterns that scale. Use when refactoring components with boolean prop proliferation, building flexible component libraries, or designing reusable APIs. Triggers on tasks involving compound components, render props, context providers, or component architecture.
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Standardize a 2D animation baseline image with `/img2mo-std xxx.png/pos`. Use when preparing a character, creature, prop, or weapon baseline before motion generation, especially if the source image is too large, tightly cropped, lacks transparent action margin, has a white background, or later walk/attack/idle frames show clipping, overlap, scale popping, or inconsistent character size.
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Deploy, manage, and scale applications on Kubernetes clusters using manifests, Helm charts, and autoscaling configurations. Use when the user requests kubernetes deployment or provides relevant inputs for this workflow.
日本語の概要は準備中です。原文の説明を表示しています。
Think and work like an expert MEMS Engineer. Use when a task calls for MEMS Engineer judgment. Reasons from scale-dependent mechanics, squeeze-film damping, and electrostatic pull-in through DRIE Bosch/surface micromachining, CoventorMP/COMSOL, foundry PDKs, LDV/WLI metrology, and AEC-Q103 qual while treating release stiction, DRIE scallop bias, package-stress offset drift, and functional-WLT-vs-reliability gaps as first-class failure modes.
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Think and work like an expert Landscape Ecologist. Use when a task calls for Landscape Ecologist judgment. Reasons from scale-explicit pattern-process feedbacks, configuration over composition, and functional rather than graphical connectivity through FRAGSTATS, landscapemetrics, Circuitscape resistance surfaces, NLMR neutral models, and block cross-validation, while treating MAUP grain artifacts, classification error propagation, isolation-by-distance confounding isolation-by-resistance, and resistance surfaces unvalidated by movement as first-class failure modes.
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Think and work like an expert Geodynamics & Tectonics Scientist. Use when a task calls for Geodynamics & Tectonics Scientist judgment. Reasons from plate kinematics, lithospheric rheology, and interseismic-versus-coseismic strain partitioning through GAMIT/GLOBK and MintPy geodesy, Okada/viscoelastic slip inversion, OxCal paleoseismic chronologies, ASPECT mantle modeling, and OpenQuake/USGS NSHM hazard while treating InSAR atmospheric delay, monument instability, unmodeled postseismic afterslip, and incompatible-timescale rate stacking as first-class failure modes.
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Think and work like an expert Geographic Information Scientist (GIS). Use when a task calls for Geographic Information Scientist (GIS) judgment. Reasons from location, topology, scale, and positional uncertainty through PostGIS/GDAL pipelines, explicit EPSG/datum choices, kriging with cross-validated variograms, and ISO 19115/FGDC metadata while treating MAUP and ecological fallacy, Web Mercator area statistics, floating-point slivers and broken topology, and spatial-autocorrelation-inflated significance as first-class failure modes.
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Think and work like an expert Food Engineer. Use when a task calls for Food Engineer judgment. Reasons from water activity, thermal microbiology, transport-coupled reaction, and rheology through heat-penetration studies, F0/D/z lethality integration, HACCP with prerequisite programs, and CFR Title 21 LACF/acidified-food rules while treating cold-point under-processing, aw and pH drift, post-process contamination, and unvalidated scale-up as first-class failure modes.
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Think and work like an expert Connectomics Scientist. Use when a task calls for Connectomics Scientist judgment. Reasons from vEM acquisition and petascale alignment through FFN/RoboEM segmentation, FlyWire/neuPrint/MICrONS/H01 graphs, and synapse-level QC while treating split/merge errors, alignment tears, false synapses, and release-version drift as first-class failure modes.
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Think and work like an expert Dynamical Systems Theorist. Use when a task calls for Dynamical Systems Theorist judgment. Reasons from state spaces, invariant sets, bifurcations, and multiple time scales through normal-form classification, center-manifold reduction, Floquet/Poincaré maps, and continuation tools like AUTO, MatCont, and DynamicalSystems.jl while treating spurious chaos from finite-time Lyapunov bias, false limit cycles mistaken for tori, numerical blow-up versus true singularity, and Takens embedding artifacts as first-class failure modes.
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Think and work like an expert Bioprocess Microbiologist. Use when a task calls for Bioprocess Microbiologist judgment. Reasons from kLa/OTR–OUR balance, fed-batch μ control, off-gas RQ, van't Riet scale-up, and contamination (phage, bioburden, adventitious agents); treats antifoam kLa penalty, exponential-feed open-loop risk, and SUB vs stainless transfer as first-class failure modes.
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Think and work like an expert Biophysicist. Use when a task calls for Biophysicist judgment. Reasons from energy landscapes, kT-scale thermodynamics, conformational ensembles, and the equilibrium-versus-kinetics distinction through smFRET, optical/magnetic tweezers, patch clamp, cryo-EM, and MD with force-field validation while treating photobleaching and blinking, FRET crosstalk, tether and series-resistance artifacts, and sampling or force-field bias as first-class failure modes.
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Think and work like an expert Carbon Cycle Scientist. Use when a task calls for Carbon Cycle Scientist judgment. Reasons from carbon mass balance across reservoirs and timescales, sign conventions, and budget closure through the Global Carbon Budget protocol, ONEFlux/REddyProc eddy-covariance processing, atmospheric inversions (CarbonTracker, CAMS, GEOS-Chem), Δ¹⁴C/δ¹³C isotopic partitioning, and ILAMB model evaluation while treating NEE sign mismatches, gap-filled GPP read as measured, fixed-depth SOC comparisons, and uncounted lateral aquatic carbon export as first-class failure modes.
日本語の概要は準備中です。原文の説明を表示しています。
Think and work like an expert Atmospheric Scientist. Use when a task calls for Atmospheric Scientist judgment. Reasons from scale-dependent balances, Ertel PV on isentropic surfaces, and closed moisture/energy budgets through PV/omega/Q-vector diagnostics, reanalyses (ERA5, MERRA-2) and WRF/MPAS/CMIP runs, and obs validation (GRUAN sondes, IMERG, CERES), while treating reanalysis assimilation increments, retrieval biases, parameterized-vs-resolved convection, and internal-variability masking of forced trends as first-class failure modes.
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Content-derived infographic poster — reads the source file and builds a statistical poster from the facts already in it. Not a dashboard, not a CV, not an AntV template. Uses common-scale encodings (Cleveland–McGill floor), ISOTYPE unit counts (Neurath), custom data glyphs (Lupi/Fragapane), and a lossless data table. Palette, glyphs, and composition are derived from the source's own content. No pies, donuts, gauges, 3D charts, or fabricated KPIs. Part of the reimagine-it Content-Derived Design suite.
日本語の概要は準備中です。原文の説明を表示しています。