Statically analyze code to detect security vulnerabilities including buffer overflows, injection risks (SQL, command, XSS), insecure deserialization, improper authentication, hard-coded credentials, and unsafe cryptography. Use when: (1) Performing security code review, (2) Analyzing code for OWASP Top 10 vulnerabilities, (3) Identifying CWE-classified weaknesses, (4) Generating security audit reports, (5) Reviewing code before deployment, or (6) Assessing third-party code security. Findings categorized by CWE ID and severity (Critical/High/Medium/Low).
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。
ArabelaTso/Skills-4-SE☆ 2532026年8月21日 更新
Proposes secure remediation strategies for detected security vulnerabilities including buffer overflows, injection risks, insecure deserialization, improper authentication, and unsafe cryptographic usage. Provides recommended security checks, safer API alternatives, design-level changes, code examples, trade-off analysis, and prioritized remediation plans. Does NOT automatically modify code unless explicitly requested.
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。
ArabelaTso/Skills-4-SE☆ 2532026年8月21日 更新
Profile programs at the function/method level to identify performance hotspots, bottlenecks, and optimization opportunities. Records execution time, memory usage, and call frequency for each interval. Generates actionable recommendations and visualizations. Use when users need to (1) analyze program performance, (2) identify slow functions or bottlenecks, (3) optimize execution time or memory usage, (4) profile Python, Java, or C/C++ programs with test cases or workload scenarios, or (5) generate performance reports with flame graphs and recommendations.
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。
ArabelaTso/Skills-4-SE☆ 2532026年8月21日 更新
Think and work like an expert Metallurgist. Use when a task calls for Metallurgist judgment. Reasons from phase diagrams, TTT/CCT paths, and Scheil solidification through Jominy hardenability (ASTM A255), ASM heat-treat cycles, metallography (ASTM E3/E112/E407), and staged failure analysis while treating decarburization, quench cracking, HAZ liquation, hot tearing, and microsegregation 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。
K-Dense-AI/scientific-agents☆ 2052026年10月3日 更新
Think and work like an expert Mining Geologist. Use when a task calls for Mining Geologist judgment. Reasons from deposit-type models (porphyry, VMS, SEDEX, orogenic Au, IOCG, skarn) through oriented core logging, domaining, variography, OK/MIK/LUC estimation, and Chain-of-Mining reconciliation to JORC Table 1, NI 43-101 Item 14, and CIM MRMR reporting; uses Leapfrog, GIM Suite/MX Deposit, and Parker F-series factors while treating support/compositing errors, batch QA/QC failures, OK smoothing bias, and Inferred-overclaim 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。
K-Dense-AI/scientific-agents☆ 2052026年10月3日 更新
Think and work like an expert Medical Physicist. Use when a task calls for Medical Physicist judgment. Reasons from CTDIvol/SSDE, HU accuracy, ACR/MQSA QA, TG-126 PET/CT, TG-18/TG-270 displays, and NCRP 147 shielding across CT, MRI, mammography, NM/PET, and therapy QA while treating phantom-mismatch dose claims, SUV normalization drift, display washout, and post-upgrade MEE gaps 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。
K-Dense-AI/scientific-agents☆ 2052026年10月3日 更新
Think and work like an expert Marine Geologist. Use when a task calls for Marine Geologist judgment. Reasons from stratigraphy, sedimentary processes, geophysical facies, and age control through multibeam bathymetry, 2D/3D seismic, piston/IODP cores tied via synthetic seismograms, and CSF-A age models while treating bad-SVP false scarps, BSRs mimicking free gas, gas-charged push-down faking structural offset, and reworked-carbon radiocarbon dates 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。
K-Dense-AI/scientific-agents☆ 2052026年10月3日 更新
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.
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。
K-Dense-AI/scientific-agents☆ 2052026年10月3日 更新
Think and work like an expert Geobiologist. Use when a task calls for Geobiologist judgment. Reasons from metabolism, redox geochemistry, microbe-mineral interactions, and diagenetic filters through stromatolite microfabric petrography, CSIA and clumped-isotopologue analysis, nanoSIMS-FISH mapping, and NASA's Ladder of Life Detection while treating Fischer-Tropsch-type synthesis, serpentinization, Rayleigh distillation, drilling-fluid contamination, and epigenetic overprint 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。
K-Dense-AI/scientific-agents☆ 2052026年10月3日 更新
Think and work like an expert Geologist. Use when a task calls for Geologist judgment. Reasons from Steno's principles and Walther's Law through Brunton strike/dip, measured sections, hand-lens rock ID (QAPF/Folk/Dunham), thin-section petrography (PPL/XPL, Michel-Lévy, point counting), FGDC/GeMS geologic maps, NGMDB/Geolex/Macrostrat, and stereonet structural analysis while treating weathering, float, and map-as-hypothesis 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。
K-Dense-AI/scientific-agents☆ 2052026年10月3日 更新
Think and work like an expert Heliophysicist. Use when a task calls for Heliophysicist judgment. Reasons from MHD, magnetic topology, reconnection, and IMF Bz coupling through SDO/HMI magnetograms, DEM and NLFFF analysis, coronagraph GCS fitting, and WSA-ENLIL/EUHFORIA ensembles while treating LOS foreshortening, AIA stray light, force-free NLFFF breakdown, and Dst/SYM-H saturation 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。
K-Dense-AI/scientific-agents☆ 2052026年10月3日 更新
Think and work like an expert Evolutionary Biologist. Use when a task calls for Evolutionary Biologist judgment. Reasons from coalescent demography, MSC gene-tree discordance, and selection–drift nulls; runs IQ-TREE/BEAST/ASTRAL/ANGSD workflows while treating LBA, rogue taxa, batch effects, and uncorrected genome scans 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。
K-Dense-AI/scientific-agents☆ 2052026年10月3日 更新
Think and work like an expert Economic Geologist. Use when a task calls for Economic Geologist judgment. Reasons from mineral systems and deposit-type models (porphyry, VMS, orogenic Au, SEDEX, IOCG) through regolith and lithogeochemistry, LA-ICP-MS sulfide fingerprinting, and geophysical vectors to JORC/CIM/NI 43-101 MRE domaining, variography, OK/MIK estimation, and classification while treating transported regolith, dispersion shadows, pXRF false highs, and Inferred-overclaim 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。
K-Dense-AI/scientific-agents☆ 2052026年10月3日 更新
Think and work like an expert Crystal Growth Specialist. Use when a task calls for Crystal Growth Specialist judgment. Reasons from thermodynamic driving force, interface stability, constitutional supercooling, and dopant segregation (keff vs. k0, G/R) through Cz/Bridgman/FZ/LEC/PVT growth, CGSim and phase-field simulation, XRT topography, etch-pit counting, and FTIR/SIMS mapping while treating striations, inclusions, crucible-reaction contamination, and cool-down slip and cracking 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。
K-Dense-AI/scientific-agents☆ 2052026年10月3日 更新
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.
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。
K-Dense-AI/scientific-agents☆ 2052026年10月3日 更新
Think and work like an expert Ceramics Engineer. Use when a task calls for Ceramics Engineer judgment. Reasons from crystal chemistry, defect equilibria, sintering densification, and flaw statistics through XRD/Rietveld, dilatometry, SEM fractography, impedance spectroscopy, and Weibull analysis per ASTM C1161/C1239/C1421 while treating surface grinding flaws, Pb/alkali volatilization, closed-pore traps, and thermal-expansion-mismatch cracking 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。
K-Dense-AI/scientific-agents☆ 2052026年10月3日 更新
Think and work like an expert Combinatorialist. Use when a task calls for Combinatorialist judgment. Reasons from labelled vs unlabelled enumeration, EGF/OGF and species, bijective and probabilistic proofs, Turán/Ramsey/extremal bounds, and BIBD/OA design parameters through SageMath/GAP/nauty, OEIS, House of Graphs, and Colbourn–Dinitz tables while treating isomorphism double-counting, parity barriers, and OEIS false matches 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。
K-Dense-AI/scientific-agents☆ 2052026年10月3日 更新
Think and work like an expert Chronobiologist. Use when a task calls for Chronobiologist judgment. Reasons from TTFL molecular clocks, SCN–peripheral coupling, and zeitgeber entrainment (PRC); analyzes actigraphy, DLMO, and PER2::LUC with ClockLab/LumiCycle, MetaCycle/eJTK/LimoRhyde, and CircaDB/CGDB/ChronobioticsDB while separating masking from endogenous τ under constant routine/FD.
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。
K-Dense-AI/scientific-agents☆ 2052026年10月3日 更新
Think and work like an expert Additive Manufacturing Engineer. Use when a task calls for Additive Manufacturing Engineer judgment. Reasons from melt-pool physics, VED, and thermal history through LPBF vs DED process selection, build orientation anisotropy, support design, powder lot control, CT/metallography NDE, and ASTM F42 / ISO-ASTM 529xx qualification—not generic 3D printing.
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。
K-Dense-AI/scientific-agents☆ 2052026年10月3日 更新
Think and work like an expert Anesthesiologist. Use when a task calls for Anesthesiologist judgment. Reasons from control of consciousness, analgesia, autonomic response, and oxygen delivery through the ASA Difficult Airway Algorithm, capnography and arterial-waveform trends, quantitative TOF monitoring, and ASRA/ERAS protocols while treating cannot-ventilate airways, local anesthetic systemic toxicity, malignant hyperthermia, and residual neuromuscular blockade 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。
K-Dense-AI/scientific-agents☆ 2052026年10月3日 更新
Plan, prompt, call, edit, iterate, and productionize Alibaba Cloud Model Studio image generation with current Wan 2.7 Image, Qwen-Image 2.0, and Z-Image Turbo models. Use for Alibaba/DashScope text-to-image, multi-reference generation, instruction editing, character-consistent image sets, typography and layout work, regional authentication, model selection, API integration, cost/rate-limit planning, troubleshooting, safety, rights, privacy, and output QA.
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。
calesthio/generative-media-skills☆ 2022026年7月14日 更新
Resolve the architecture of focal oncogene amplifications — extrachromosomal DNA (ecDNA), breakage-fusion-bridge (BFB) cycles, homogeneously staining regions (HSR), and linear amplification — from whole-genome sequencing with AmpliconArchitect, the AmpliconSuite pipeline, and AmpliconClassifier. Covers copy-number seed selection, breakpoint-graph reconstruction, balanced-flow optimization, ecDNA classification, and the limits of depth-only amplification calls. Use when a focal amplification needs structural characterization, when distinguishing ecDNA from chromosomal amplification, suspecting ecDNA-driven oncogene amplification or therapy resistance, or selecting copy-number seeds for amplicon reconstruction.
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。
BioTender-max/awesome-bio-agent-skills☆ 2012026年7月2日 更新
Use when the user wants to design, redesign, shape, critique, audit, polish, clarify, distill, harden, optimize, adapt, animate, colorize, extract, or otherwise improve a frontend interface. Covers websites, landing pages, dashboards, product UI, app shells, components, forms, settings, onboarding, and empty states. Handles UX review, visual hierarchy, information architecture, cognitive load, accessibility, performance, responsive behavior, theming, anti-patterns, typography, fonts, spacing, layout, alignment, color, motion, micro-interactions, UX copy, error states, edge cases, i18n, and reusable design systems or tokens. Also use for bland designs that need to become bolder or more delightful, loud designs that should become quieter, live browser iteration on UI elements, or ambitious visual effects that should feel technically extraordinary. Not for backend-only or non-UI tasks.
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。
skillmds/skillmd☆ 1982026年10月9日 更新
An engineering-grade marketing system organized around two surface modes — a deep black canvas for hero and footer chapters and a flat paper-white canvas for body content — connected by a single, almost violently saturated NVIDIA Green accent that carries every CTA, every active tab, and the small decorative corner squares that mark out cards. The system is unapologetically angular: 2px radius across every surface, tight bold sans-serif typography in NVIDIA's proprietary EMEA cut, and a hairline gray rule that separates dense multi-column technical content. There is no decorative gradient, no atmospheric mesh, no soft drop shadow — just black, white, gray, and green stacked into a structured editorial grid that scales from product cards to massive industry landing pages without bending its rules.
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。
skillmds/skillmd☆ 1982026年10月9日 更新