194 件 ・ 関連度順
概要と使いどころ
Master advanced AgentDB features including QUIC synchronization, multi-database management, custom distance metrics, hybrid search, and distributed systems integration. Use when building distributed AI systems, multi-agent coordination, or advanced vector search applications.
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。
Use this skill when simulating vehicle motion, calculating safe following distances, time-to-collision, speed/position updates, or implementing vehicle state machines for cruise control 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。
Master advanced AgentDB features including QUIC synchronization, multi-database management, custom distance metrics, hybrid search, and distributed systems integration. Use when building distributed AI systems, multi-agent coordination, or advanced vector search applications.
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。
Spatial reasoning, coordinate geometry, transformations, and trigonometry for geometric problem solving. Covers Euclidean geometry (points, lines, angles, congruence, similarity), triangle geometry (Pythagorean theorem, laws of sines and cosines), circle geometry (tangent lines, inscribed angles, power of a point), coordinate geometry (distance, midpoint, slope, conic sections), transformations as functions (rotation, reflection, translation, dilation), trigonometry (unit circle, identities, inverse functions), and geometric proof techniques. Use when reasoning about shapes, angles, spatial relationships, coordinate problems, or trigonometric computations.
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。
Martial arts as body discipline — the shared pedagogical structure across striking, grappling, and weapon arts (stance, distance, timing, ukemi, live partner work, graded ranking, and the ethical container the best schools enforce). Covers karate, judo, jiu-jitsu (Brazilian and traditional Japanese), aikido, kendo/kenjutsu, boxing, muay Thai, and wrestling at enough depth that an agent can place a user into a reasonable first-month practice and recognize the safety failures that matter most. Leans on Moshé Feldenkrais's judo background and Yang Jwing-Ming's martial scholarship for the internal-to-external bridge. Use for any query about beginning a martial art, training injury patterns, graded progression, or the ethics of combat training.
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。
Foundational measurements and relationships. The axioms of the system — numbers, distance, angles, and the geometry of seeing.
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。
Comprehensive Python library for astronomy and astrophysics. This skill should be used when working with astronomical data including celestial coordinates, physical units, FITS files, cosmological calculations, time systems, tables, world coordinate systems (WCS), and astronomical data analysis. Use when tasks involve coordinate transformations, unit conversions, FITS file manipulation, cosmological distance calculations, time scale conversions, or astronomical data processing.
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。
Master advanced AgentDB features including QUIC synchronization, multi-database management, custom distance metrics, hybrid search, and distributed systems integration. Use when building distributed AI systems, multi-agent coordination, or advanced vector search applications.
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。
Measure ACSets better than authors via surjectivity gadgets, Betti numbers, Möbius classification, and p-adic ultrametric distance
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。
Master advanced AgentDB features including QUIC synchronization, multi-database management, custom distance metrics, hybrid search, and distributed systems integration. Use when building distributed AI systems, multi-agent coordination, or advanced vector search applications.
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。
Write or rewrite prose so it sounds like a human wrote it — not a frontier model. Named in homage to Rabindranath Tagore, whose prose carried what frontier models reach for and miss: a point of view, specificity over abstraction, and restraint over puffery. Merges two complementary approaches: a 29-pattern catalog of AI tells (from humanizer) plus an 8-rule operating system with an 8-dimension scoring gate (extending stop-slop). Use when drafting, editing, or reviewing any prose: essays, posts, docs, reports, emails. Detects and removes inflated symbolism, promotional language, superficial -ing analyses, vague attributions, em dash overuse, rule of three, AI vocabulary, passive voice, negative parallelisms, filler phrases, inanimate-verb constructions, narrator-from-a-distance voice, and metronomic rhythm. Adds back the things AI writing usually lacks: point of view, stakes, specificity, restraint, varied rhythm, and trust in the reader.
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。
Use whenever writing, reviewing, or debugging .NET/C# code that uses the BallisticCalculator NuGet package (namespace BallisticCalculator) or its Gehtsoft.Measurements unit types — even when the user doesn't name the package explicitly but is clearly doing external/interior ballistics in .NET (bullet drop, velocity, energy, windage, spin drift, time of flight, zeroing a scope) for rifles, air rifles, bows, or artillery. Covers the full public API (Ammunition, Rifle, Atmosphere, Wind, ShotParameters, TrajectoryCalculator, TrajectoryPoint); standard, custom, .drg, and multi-BC drag tables; saving/loading data and building your own file format around it (BXml and System.Text.Json serialization); and building or rendering scope reticles (e.g. to SVG). Also use it for this library's Gehtsoft.Measurements Measurement<T> unit types (DistanceUnit, VelocityUnit, AngularUnit, WeightUnit, PressureUnit, …). Skip for: generic physics or projectile-motion exercises, a different ballistics library (e.g. GNU/JBM), game-engine or Unity projectile motion, plain unit conversions, and non-code ballistics questions (load-data or forensics advice). Self-contained: no access to the library source or binaries is required — prefer this over scanning the package to rediscover the API. Describes 1.1.13+, including the named ZeroRangeCantBeReachedException / TrajectoryCannotBeCalculatedException failures.
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。
Plan a multi-stop tour route with waypoint optimization, drive/walk time estimation, and POI discovery along the route using OSM data. Covers geocoding, nearest-neighbor and TSP-based ordering, time/distance matrix calculation, and itinerary generation with points of interest. Use when planning a road trip or walking tour with multiple destinations, optimizing visit order to minimize travel time, discovering sites along a route, or comparing driving versus walking versus public transport options.
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。
Pythonic wrapper around RDKit with a simplified interface and sensible defaults. Preferred for standard drug discovery work — SMILES/SELFIES/InChI conversion, molecule standardization and sanitization, descriptors, ECFP and other fingerprints, Tanimoto distance matrices, Butina clustering and diverse subset picking, Bemis-Murcko scaffolds and scaffold splits, BRICS/RECAP fragmentation, 3D conformer generation, SDF/CSV/Excel and cloud I/O, and parallel processing via n_jobs. Returns native rdkit.Chem.Mol objects, so it composes with RDKit throughout. Also trigger on datamol, `import datamol as dm`, dm.to_mol, dm.standardize_mol, dm.cluster_mols, or dm.pick_diverse. For advanced control or custom parameters, use the rdkit skill directly.
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。
"Apply the Uppsala Internationalization Model to analyze gradual foreign market entry based on psychic distance and experiential learning. Use this skill when the user needs to plan a staged internationalization sequence, understand why firms enter culturally similar markets first, or evaluate whether a firm's international expansion follows the establishment chain from export to subsidiary.".
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。
"Solve vehicle routing problems to optimize delivery routes under capacity and time constraints. Use this skill when the user needs to plan delivery routes, minimize transportation costs, or optimize fleet utilization — even if they say 'delivery route optimization', 'fleet routing', or 'minimize driving distance'.".
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。
The measurement surface for ALL Pulp DSP and audio-pipeline work — read it BEFORE writing or gating DSP, not only when something already sounds wrong. Covers the C++ harness (signal generators, metrics, assertions, RenderScenario, contracts), the offline Audio Doctor (magnitude/frequency response, THD/THD+N, phase/group delay), and their Python sibling the Audio Quality Lab (tools/audio/quality-lab — null residual + alignment, LTAS log-spectral distance, spectral flux/centroid, HNR, Theil-Sen drift slope, Kaiser-sinc resampling, license-guarded corpus, regression-net ratchet). TRIGGER on AUTHORING work — "build/design an oscillator/filter/synth/effect", "add a DSP module", "what should the acceptance gate be", "how do I measure aliasing / anti-aliasing / alias floor", "null against a reference", "is this DSP correct", "choose a tolerance", "golden/regression corpus for audio", "measure drift or jitter", "A/B two renders" — AND on DEBUGGING work — "is there sound / no audio / I hear nothing", "does this filter/compressor/synth/delay produce the right signal", "prove the DSP / prove the contract", "measure the frequency response", "what's the THD / is it distorting", "what's the group delay / phase response / measured latency", "magnitude response curve", "render a test tone and assert", "audio regression", "64-frame works but 128 is silent", "sample-rate change pitch-shifted it", "describe what's in this buffer", "audio doctor", "compare before/after a DSP refactor". Reach for this BEFORE hand-rolling any FFT, null test, alias measurement, pitch tracker, or golden-render script — most of it already exists in one of the two lanes. Test/tool layer over HeadlessHost — deterministic, no audio device, no speakers. Off the realtime thread entirely.
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。
Use when a task needs the judgment of a commercial pilot — computing density-altitude-adjusted takeoff/landing distance against runway available, checking weight-and-balance CG against the envelope (not just gross weight), deciding an IFR/VFR go/no-go against personal minimums instead of legal minimums, interpreting a METAR/TAF (TEMPO/PROB groups, 1-2-3 alternate rule) for a go decision, or setting divert/turn-back triggers before a flight departs.
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。
Use when a task needs the judgment of an Automotive Engineer — computing weight transfer and tire friction-circle limits for a braking-while-cornering maneuver to set brake-force distribution, sizing a powertrain and gear ratio against a 0-60 mph acceleration target while checking traction versus power limits, sizing a crumple zone's crush distance against FMVSS 208 occupant-deceleration limits, or checking a powertrain-mount or driveline natural frequency against engine firing-order excitation for NVH isolation. Distinct from an automotive-service-technician (diagnoses and repairs a vehicle already designed) — this role owns the system-level design decisions (structure, powertrain sizing, suspension geometry, restraint/crash structure, NVH) that produce the vehicle the technician later services.
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。
Guide for annotating ENCODE peaks with genomic features using ChIPseeker and GREAT. Use when users need to assign peaks to genes, determine genomic feature distribution (promoter, intron, intergenic), or perform gene ontology enrichment of peak-associated genes. Trigger on: peak annotation, ChIPseeker, GREAT, peak to gene, genomic feature, promoter enrichment, gene ontology, peak distribution, TSS distance, nearest gene.
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。
The user's synced Google Health Connect data from their Android device: daily metrics (steps, distance, calories, heart rate, HRV, VO2max), sleep sessions (stages, quality, efficiency), and workouts.
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。
The user's synced Apple Health (HealthKit) data: daily metrics (steps, distance, calories, heart rate, HRV, VO2max), sleep sessions (stages, quality, efficiency), and workouts.
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。
Compound fields (Name, Address, Geolocation): SOQL access rules, DML semantics, component access in Apex/LWC, reporting column behavior, formula field restrictions. NOT for creating a new custom field — use admin/custom-field-creation. NOT for formula syntax and functions — use admin/formula-fields. Trigger keywords: BillingAddress, MailingAddress, ShippingAddress, StateCode, CountryCode, GeocodeAccuracy, Location field type, displayLocationInDecimal, __Latitude__s, __Longitude__s, DISTANCE, GEOLOCATION, Custom Address Fields, AddressSettings, System.Address, System.Location, Person Account name.
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。
Comprehensive regression model diagnostics and assumption checking. Use when validating regression models, checking assumptions (linearity, homoskedasticity, normality, independence), detecting outliers/influence, testing multicollinearity, or when user mentions residuals, heteroskedasticity, VIF, Cook's distance, or diagnostic plots.
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。