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cccskills

「conda」の検索結果

159 件 ・ 関連度順

概要と使いどころ

Installs a self-contained conda instance that is managed by the R/Bioconductor installation machinery. This aims to provide a consistent Python environment that can be used reliably by Bioconductor packages. Functions are also provided to e

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。

bioMate-AI/biomate-bioconductor-kb8042026年6月21日 更新

rapidapi

無料

Google Flights Live and Booking.com Live search via RapidAPI. Secondary source for cash flight prices and hotel availability when SerpAPI needs a second opinion.

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。

borski/travel-hacking-toolkit6932026年10月12日 更新

Use when the user wants a VALID experiment instead of a guess — hypothesis, one variable, sample size and runtime math, statistical significance, primary versus secondary metrics, multi-arm designs, and a results template, across Optimizely, VWO, and native Meta and Google tests. Trigger on 'A/B test', 'split test', 'how long should I run the test', 'is this result significant', 'test two versions', 'which creative is actually better'. Also use when a winner was declared after two days on tiny numbers. Not for — scaling the proven winner, see `55-scaling-ads-global`; analyzing data already collected, see `13-data-analysis-global`; auditing the account, see `21-ads-audit-global`.

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。

minhnv0807/ai-business-skills6132026年9月12日 更新

Python-based workflow manager for reproducible, scalable pipelines. Define rules with file-based dependencies; Snakemake resolves execution order and parallelism. Runs local, SLURM, LSF, AWS, GCP via profiles; per-rule conda/Singularity envs. For NGS pipelines, ML training, and multi-step file processing. Use Nextflow for Groovy dataflow or nf-core integration.

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。

jaechang-hits/SciAgent-Skills3782026年9月29日 更新

Predict RNA secondary structure, MFE folding, base-pair probabilities, RNA-RNA interactions via ViennaRNA Python bindings. Pipeline: sequence → MFE → partition function and pair-probability matrix → dot-bracket → duplex. Use for siRNA/sgRNA targeting, ribozyme design, RNA accessibility. Use RNAfold CLI for batch use without Python.

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。

jaechang-hits/SciAgent-Skills3782026年9月29日 更新

Provides AWS CloudFormation patterns for DynamoDB tables, GSIs, LSIs, auto-scaling, and streams. Use when creating DynamoDB tables with CloudFormation, configuring primary keys, local/global secondary indexes, capacity modes (on-demand/provisioned), point-in-time recovery, encryption, TTL, and implementing template structure with Parameters, Outputs, Mappings, Conditions, cross-stack references.

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。

giuseppe-trisciuoglio/developer-kit3572026年9月10日 更新

Design, configure, test, bake, and validate Blender physical effects including Cloth, Soft Body, Rigid Body, collisions, constraints, Fluid, smoke, fire, Dynamic Paint, Ocean, Wave, particles, Boids, force fields, fracture, debris, and secondary effects. Use when gravity, inertia, collision, flexibility, pressure, flow, flocking, emission, or breaking causes the requested result.

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。

XliuXjianX/blender-production-skills2522026年8月15日 更新

Think and work like an expert Forensic Chemist. Use when a task calls for Forensic Chemist judgment. Reasons from chain of custody, validated methods, measurement uncertainty, and class-versus-individual characteristics through GC-MS, LC-MS/MS, FTIR, and SWGDRUG-aligned identification under ISO/IEC 17025, while treating carryover contamination, secondary transfer, isomer co-elution, and upgrading equivocal results into source attribution 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-agents2052026年10月3日 更新

Think and work like an expert Computational Scientist. Use when a task calls for Computational Scientist judgment. Reasons from Roache code/solution verification and ASME V&V 10/20/40 credibility through MMS/GCI, UQ ensembles, and Snakemake/Nextflow/CWL pipelines with conda-lock/Apptainer provenance while treating environment drift, workflow cache staleness, and validation-vs-calibration conflation 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-agents2052026年10月3日 更新

Think and work like an expert Computational Linguist. Use when a task calls for Computational Linguist judgment. Reasons from UD/PTB formalisms, validate.py/eval.py (LAS/MLAS/ELAS), and evalb .prm settings through Stanza/UDPipe pipelines, PropBank/FrameNet/AMR/UMR layers, IAA (κ, Krippendorff α), CONDA contamination checks, and ARR reproducibility while treating tokenizer mismatch, oracle inflation, train–test leakage, and guideline 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-agents2052026年10月3日 更新

Think and work like an expert Agricultural Entomologist. Use when a task calls for Agricultural Entomologist judgment. Reasons from pest population dynamics, economic injury levels and thresholds, and degree-day phenology through systematic scouting, IRAC mode-of-action rotation, RCBD efficacy trials, and conservation biocontrol while treating misidentification, secondary pest flares from enemy removal, resistance under repeated MoA, and trap-catch-without-field-verification 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-agents2052026年10月3日 更新

Use when enhancing, upscaling, restoring, denoising, sharpening, deinterlacing, stabilizing, motion-deblurring, colorizing, SDR-to-HDR converting, or frame-rate/slow-motion converting video (and secondarily images) with Topaz Labs — whether cleaning up AI-generated video, compressed UGC, or old archival footage, or building a generate-low-res-then-upscale delivery pipeline. Covers choosing the right named Topaz model for a specific footage problem, setting parameters, driving the Topaz Platform (Video/Image) REST API's async job lifecycle, judging when enhancement helps versus when it introduces artifacts (over-smoothing, temporal shimmer, face hallucination), and QA of enhanced output. Do not use for originating new video content, non-Topaz upscalers, or purely editorial cuts.

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-skills2022026年7月14日 更新

ui-craft

無料

Polishes UI primitives one at a time using 2026 research-backed patterns — adds loading/icon states to buttons, replaces inline skeletons with primitives, adds secondary actions to errors, ensures 48px touch targets and visible focus indicators, applies a standard motion token ladder. Use when: 'make the UI feel more polished', 'add attention to detail', 'reduce component duplication', 'tighten the design system', 'apply craft to the frontend'.

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/skillmd1982026年10月9日 更新

A three-surface marketing system organized around alternating black, white, and PlayStation Blue chapters that scroll past the viewer like a console launch trailer. Each section has a single editorial purpose — hero photography, console product render, PS Plus tier callout, news strip — and each owns one of three full-bleed canvas modes. The chrome is unusually quiet for a gaming brand: bright PlayStation Blue (`#0070d1`) carries every primary CTA as a fully-rounded pill, the proprietary SST face renders display copy at a signature weight 300 (light) for an airy, premium feel, and a crisp 8px-radius secondary card system carries product info on either canvas mode. The system never decorates — no gradient backgrounds on chrome, no atmospheric mesh, no drop shadows beyond a faint section-divide. Imagery does all the heavy lifting: console glamour shots, game key art, and PS Plus tier illustrations occupy 60-90% of every section, with copy compressed into a small editorial slot.

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/skillmd1982026年10月9日 更新

Designs Amazon A+ Content (formerly Enhanced Brand Content) — the 8 module suite that appears below the standard product carousel for Brand Registered sellers. Covers Hero Banner (21:9 / 2388×1024), Pain Points / Selling Points / Technology / Data / How-to-Use / Variants (3:2 / 1536×1024), and Endorsement (21:9), with mobile safe-area rule, 30pt text floor, and cross-module consistency anchored to the main image URL. Use when the user says "A+ page", "A+ content", "Amazon A+", "Brand Content", "Enhanced Brand Content", "亚马逊详情页", "A+ 详情页", "21:9 banner", "Hero Banner", "Amazon detail page module", or any request for the brand-registered detail-page module suite. For the 1:1 main image and carousel secondary images, see the `product-shots-main-image` skill.

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。

motiful/product-shots1022026年6月8日 更新

Design a developmental band system mapping student growth from early childhood through upper secondary. Use when building competency-based curriculum architecture for a school or programme.

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。

nota-america/forgecat-agent-profiles902026年9月24日 更新

Retrieves and analyzes FHIR Coverage and Organization resources to produce a structured insurance summary with coordination of benefits analysis. Use when user asks to "check insurance", "coverage details", "verify coverage", "insurance summary", "what plan is the patient on", "primary vs secondary insurance", or "coverage status". Do NOT use for clinical data, demographics beyond insurance, or billing claim submission.

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。

FDU-INS/Insurance-Skills762026年7月12日 更新

Execute Guidewire secondary workflow: Claims processing in ClaimCenter. Use when implementing FNOL, claim investigation, reserves, payments, and settlement. Trigger with phrases like "claimcenter workflow", "create claim", "file fnol", "process claim", "claim settlement", "claim payment".

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。

FDU-INS/Insurance-Skills762026年7月12日 更新

Execute Guidewire secondary workflow: Claims processing in ClaimCenter. Use when implementing FNOL, claim investigation, reserves, payments, and settlement. Trigger with phrases like "claimcenter workflow", "create claim", "file fnol", "process claim", "claim settlement", "claim payment".

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。

FDU-INS/Insurance-Skills762026年7月12日 更新

Transforms Claude into a CFA-level financial analyst for specialty finance, regulatory compliance, and industry-specific analysis. Use when performing private credit pricing, insurance reserving, FP&A variance analysis, wealth planning, restructuring recovery analysis, real estate valuation, venture capital analysis, ESG assessment, regulatory capital analysis (Basel III), compliance reporting (MiFID II, GIPS), credit derivatives (CDS, CVA), convertible bond analysis, lease accounting (ASC 842/IFRS 16), pension funding/LDI, sovereign risk assessment, real option valuation, equity research (SOTP, target price), commodity spread trading, treasury operations, PPP infrastructure modelling, onshore fund structuring, offshore fund structuring, transfer pricing analysis (BEPS, Pillar Two), tax treaty optimisation, FATCA/CRS compliance, economic substance analysis, regulatory reporting (AIFMD, Form PF), AML/KYC compliance, crypto/DeFi analysis, municipal bond analysis, structured products, trade finance, fund of funds (J-curve, commitment pacing, manager selection, secondaries), bank analytics (NIM, CAMELS, CECL, deposit beta, loan book), carbon markets (credit pricing, ETS, CBAM, offsets, shadow carbon price), or private wealth (concentrated stock, philanthropic vehicles, wealth transfer, direct indexing, family governance) analysis is required. Pairs with corp-finance-mcp tools for computation.

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。

FDU-INS/Insurance-Skills762026年7月12日 更新

Use the corp-finance-mcp server tools for specialty finance, regulatory, and compliance calculations. Invoke when performing private credit (unitranche, direct lending, syndication), insurance (loss reserving, premium pricing, Solvency II SCR), FP&A (variance analysis, break-even, working capital, rolling forecast), wealth management (retirement planning, tax-loss harvesting, estate planning), restructuring (recovery analysis, distressed debt), real assets (property valuation, project finance), venture capital (dilution, convertible instruments, fund returns), ESG (scoring, climate/carbon, green bonds, SLL), regulatory capital (Basel III, LCR/NSFR, ALM), compliance (MiFID II best execution, GIPS reporting), credit derivatives (CDS pricing, CVA/DVA), convertible bonds (binomial tree pricing, scenario analysis), lease accounting (ASC 842/IFRS 16, sale-leaseback), pension & LDI (funding analysis, liability-driven investing), sovereign risk (bond analysis, country risk), real options (binomial valuation, decision trees), equity research (SOTP, target price), commodity trading (spread analysis, storage economics), treasury management (cash management, hedge effectiveness), infrastructure finance (PPP models, concession valuation), crypto (token valuation, DeFi analysis), municipal bonds (pricing, credit analysis), structured products (notes, exotic), trade finance (LC, supply chain), fund structuring (US onshore, UK/EU, Cayman/BVI offshore, Luxembourg/Ireland), transfer pricing (BEPS/Pillar Two, intercompany pricing), tax treaty (treaty network optimization, holding structures), FATCA/CRS (reporting, entity classification), economic substance (multi-jurisdiction testing), regulatory reporting (AIFMD Annex IV, SEC Form PF, CFTC CPO-PQR), AML compliance (KYC risk scoring, sanctions screening), fund of funds (J-curve, commitment pacing, manager selection, secondaries pricing), bank analytics (NIM analysis, CAMELS rating, CECL provisioning, deposit beta, loan book), carbon markets (credit pricing, ETS compliance, CBAM, offset valuation, shadow carbon price), private wealth (concentrated stock, philanthropic vehicles, wealth transfer, direct indexing, family governance). All computation uses 128-bit decimal precision.

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。

FDU-INS/Insurance-Skills762026年7月12日 更新

Industrial production of iron and steel from ore to finished product — blast furnace, Bessemer converter, open-hearth, basic oxygen, electric arc, continuous casting, rolling, and secondary metallurgy. Covers the chemistry of decarburization, dephosphorization, and desulfurization, the metallurgy of plain carbon steels, the evolution from puddling and rolling to BOF and EAF, and the process-structure-property chain that makes mild steel the default structural material of the industrial era.

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。

Tibsfox/gsd-skill-creator712026年7月20日 更新

Harmonic analysis, voice leading, chord function, and modulation techniques for tonal music. Covers triads, seventh chords, Roman numeral analysis, figured bass, voice leading rules, cadence types, secondary dominants, modulation techniques, chromatic harmony (Neapolitan, augmented sixth chords), jazz lead sheet notation, and functional vs. linear harmonic thinking. Use when analyzing chord progressions, writing voice leading, identifying key areas, or interpreting harmonic function in any tonal style.

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。

Tibsfox/gsd-skill-creator712026年7月20日 更新

Primary and secondary source analysis for historical reasoning. Covers source classification, sourcing (author/context/purpose), corroboration across multiple sources, contextualization within time and place, and bias detection. Use when evaluating historical evidence, assessing source reliability, or constructing evidence-based historical arguments.

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。

Tibsfox/gsd-skill-creator712026年7月20日 更新