本文へ移動
cccskills

「taxonomy」の検索結果

203 件 ・ 関連度順

概要と使いどころ

Mainland-Chinese TV-series craft, documents and production chain (国产剧创作体系与制片链) — the China layer parallel to the Japanese and Korean/French skills. Distilled from Yao Kougen 姚扣根《电视剧写作概论》(2016; series taxonomy, four Chinese script formats, the 3-minute/15-minute/episode-end suspense law, 36 situations), Zhang Wei 张巍《电视剧改编教程》(2014; five source types, sell-point migration, six case studies), Zhang Mingzhi & Song Peiyi《电视剧出品人与制片人教程》(2016; running-time rules, two-stage censorship, scene-breakdown sheet, contracts), Zhao Binbin《影视剧片段改编教程》(2016; film to stage fragment), plus official Chinese renderings of US TV terms from the translated Douglas and Blum textbooks. Use when writing or judging a 国产剧, turning a novel or IP into a 30–50 episode drama, writing a 策划书 / 分集梗概 / 人物小传, formatting a Chinese teleplay, sizing episode count and word count, checking content red lines and the 立项/备案/审查 chain, reading a Chinese screenwriter contract, or mapping US series vocabulary onto Chinese usage.

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。

jtydhr88/screenwriting-skills1,6482026年10月3日 更新

ra-hook

無料

短视频钩子(开头)类型选择与写法,中文名「钩子」。Use when 起钩子、写钩子、钩子怎么写、钩子没思路、设计前5秒钩子、写视频开头/口播稿开头, or when the user asks 视频开头怎么做、开头模板、hook 类型、帮我起个钩子, including during ra-洗稿 script rewriting and 选题深化. Provides a scenario-based taxonomy of 7 hook types with decision flow, prerequisites, sentence templates, and common mistakes. For diagnosing and optimizing an existing hook draft, use dbs-hook instead; this skill chooses the type, dbs-hook polishes the execution.

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。

Pluviobyte/rnskill1,6422026年9月21日 更新

mcsb

無料

Microsoft Cloud Security Benchmark (MCSB v2) control-domain taxonomy and NIST 800-53 / CIS Controls crosswalk for planning and reviewing Azure cloud resources.

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。

microsoft/hve-core1,5212026年10月13日 更新

Intent-based observability + traceability router across layers, boundaries, and signals. Routes to vendor-specific skills via category taxonomy; owns transport tuning, meta-observability, incident forensics. Use for observability, traceability, telemetry, APM, RUM, metrics, logs, traces, profiles, SLO, incident forensics, tracing architecture work.

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。

first-fluke/oh-my-agent1,3412026年10月13日 更新

Delimits putative species boundaries from molecular data within the de Queiroz 2007 unified-lineage framework using ASAP (Puillandre 2021 successor to ABGD), mPTP C++ (Kapli 2017 successor to bPTP; bPTP is Python NOT R), GMYC single/multi-threshold (Pons 2006; Fujisawa 2013), multilocus BPP v4 with prior calibration from data (NOT defaults; Yang 2015), SNAPP + BFD* for SNP delimitation, DELINEATE (Sukumaran 2021) speciation-process modeling to address Sukumaran & Knowles 2017 PNAS critique that MSC delimits structure not species, integrative-taxonomy congruence (Padial 2010; Carstens 2013), Dsuite for introgression testing before sister claims (Malinsky 2021), and Meyer & Paulay 2005 barcoding-gap-absence caveat. Use when delineating species from DNA barcoding data, resolving cryptic complexes, choosing among ASAP/mPTP/BPP/DELINEATE, calibrating BPP priors, distinguishing introgression from ILS, or applying the Sukumaran-Knowles oversplitting correction.

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。

GPTomics/bioSkills1,2192026年8月15日 更新

Detects and removes contamination in genome assemblies via two disjoint workflows - foreign-sequence screening of a single-organism (eukaryote/isolate) assembly with NCBI FCS-GX (GenBank-submission-mandatory), FCS-adaptor, and BlobToolKit blob plots; and MAG/bin quality assessment with CheckM2 plus GUNC (chimerism) plus GTDB-Tk taxonomy, judged against MIMAG. Covers why CheckM2 alone is blind to disjoint-marker chimeras, the FCS-GX RAM wall, organelle/NUMT triage, strain heterogeneity, and the HGT-vs-contamination (tardigrade) trap. Use when screening an assembly for foreign contamination before GenBank submission, assessing MAG completeness/contamination/chimerism, deciding which contigs to remove, or distinguishing real HGT from contaminant contigs.

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。

GPTomics/bioSkills1,2192026年8月15日 更新

Processes eDNA metabarcoding from raw paired-end reads to species tables, navigating ASV (DADA2, UNOISE3) vs OTU (swarm v2) decision (Callahan 2017 vs Schloss multi-copy-16S critique), marker/primer choice (Leray COI, MiFish 12S, 515F/806R 16S, ITS2) with primer-specific bias, OBITools3 v3 command-name break (obi stats plural; .tar.gz taxonomy), tag-jumping with dual-indexing (Schnell 2015; NovaSeq 10x MiSeq), decontam as screening-not-classifier (Davis 2018), read-counts-not-abundance critique (Lamb 2019), site-occupancy modeling (Ficetola 2015), Naive-Bayes calibration limits (Bokulich 2018), and eDNA decay (Strickler 2015). Use when going from raw eDNA FASTQ to species tables, picking marker + denoising pipeline, deciding whether read counts represent abundance, applying occupancy modeling, configuring OBITools3 v3, or interpreting decontam output. Not for clinical 16S microbiome (see microbiome/amplicon-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。

GPTomics/bioSkills1,2192026年8月15日 更新

Retrieve records from NCBI databases using Biopython Bio.Entrez (EFetch, ESummary). Use when downloading sequences, fetching GenBank/GenPept records, getting document summaries, parsing nested XML, navigating GI deprecation, choosing between rettype+retmode combinations, and parsing into Biopython SeqRecord/SwissProt objects. Covers nucleotide, protein, gene, pubmed, sra, gds, taxonomy, snp, clinvar.

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。

GPTomics/bioSkills1,2192026年8月15日 更新

Run remote BLAST searches against NCBI servers using Biopython Bio.Blast.NCBIWWW. Use when identifying unknown sequences, finding homologs, picking the correct BLAST program (blastn/blastp/blastx/tblastn/tblastx/psiblast/megablast/dc-megablast), interpreting Karlin-Altschul E-values, avoiding the max_target_seqs trap (Shah 2019), choosing composition-based statistics, or limiting searches by organism. Covers RID lifecycle, database choice (nt/nr/refseq_select/swissprot), word-size and CBS taxonomy.

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。

GPTomics/bioSkills1,2192026年8月15日 更新

Search NCBI databases using Biopython Bio.Entrez (ESearch, EInfo, EGQuery, ESpell). Use when finding records by keyword, building reproducible field-qualified queries, navigating the Entrez Query Translator, exploiting the history server for large result sets, handling retmax caps, or interpreting weekly index lag. Covers PubMed, Nucleotide, Protein, Gene, SRA, GEO, Assembly, Taxonomy, ClinVar, dbSNP.

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。

GPTomics/bioSkills1,2192026年8月15日 更新

Build local BLAST databases and run searches using NCBI BLAST+ command-line tools. Use when running >50 queries, building custom databases with -parse_seqids and -taxid, downloading prebuilt NCBI databases via update_blastdb.pl, choosing -task variants (megablast/dc-megablast/blastn/blastn-short), tuning soft/hard masking, scaling threads, or extracting hits with blastdbcmd. Encodes BLAST v5 vs v4 database format, taxonomy filtering, makeblastdb pitfalls.

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。

GPTomics/bioSkills1,2192026年8月15日 更新

Use when a SPEC, INNOVATE, or VALIDATE (Layer 2) approach hinges on an unverified runtime/library/external mechanism: run a probe from the 8-family taxonomy and produce a VIABLE/NOT-VIABLE/INCONCLUSIVE VERDICT artifact.

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。

withkynam/vibecode-pro-max-kit1,1502026年6月21日 更新

End-to-end analytics implementation for web and SaaS: GA4, Google Tag Manager, event taxonomy, conversion tracking, and UTM strategy. Use when building a tracking plan, debugging missing events, setting up GTM, or auditing existing analytics.

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。

borghei/Claude-Skills9012026年10月7日 更新

Feature flag strategy, lifecycle, and operations. Use when designing a flag taxonomy, planning a gradual rollout, building kill switches, auditing flag debt, defining governance, running progressive delivery, or rolling back via flags.

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。

borghei/Claude-Skills9012026年10月7日 更新

Use when the user mentions GPT Image 2.0 or GPT Image 2.5, gpt-image-2, gpt-image-2.5, gpt_image_2_5, GPT-Image-2 prompts, the Flare / Sunburst variants, a transparent-background image, or wants to generate an image with GPT Image 2.0 or 2.5. Covers when to prefer GPT Image 2.5 over 2.0 (transparent background, xhigh/max quality, extra aspect ratios — from platform and OpenAI facts), the CLI-vs-MCP disagreement on gpt_image_2, the three-format prompt taxonomy (Format A structured JSON for UI mockups and layout-dense images; Format B dense cinematic prose for single-subject scenes; Format C auto-derive meta-prompt for theme-only concepts), per-format craft patterns, output conventions, the 6-item pre-delivery checklist, and cross-surface workflow context (companion static-ads-workflow.md for ad recreation; higgsfield-marketing-studio cross-surface-workflow.md §3 for ms_image / DTC Ads Higgsfield-native alternative).

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。

OSideMedia/higgsfield-ai-prompt-skill7332026年9月27日 更新

Convert YouTube videos to SEO-optimized blog posts. Extract video title, description, and content, then generate a search-engine-friendly blog post with embedded video, cover images, optimized metadata, structured Markdown sections, clean resource blocks, and canonical 5-8 keywords. Auto-generates English filenames and saves to the configured Hexo blog posts directory. Includes tag management rules to maintain a clean, consistent tag taxonomy.

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。

wlzh/skills6832026年10月11日 更新

Progressive L1-L6 refactoring hierarchy, 22 code smell taxonomy, atomic transformations, test code smells, and Fowler refactoring catalog

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。

nWave-ai/nWave6162026年9月16日 更新

Canonical AT completeness gate — research-anchored 7-category taxonomy (C1-C7) + 15-item mechanical checklist. Paradigm-neutral. Drives acceptance-designer reviewer verdict deterministically.

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。

nWave-ai/nWave6162026年9月16日 更新

Monthly on the last weekday, light browser lane. Re-tests every theme and every severity rule against a month of real ticket evidence and rewrites strategy/themes.md wherever the evidence disagrees with the assumption. It merges two themes the evidence shows are one, splits a theme whose tickets have two different answers, retires a theme with no volume, creates a theme for a cluster that kept landing unclassified, and rewrites a severity rule wherever the outcomes contradict it. Theme ids are never reused and never renumbered. It holds every outbound action unless you released the channel, and it never touches a credential.

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。

markfulton/ai-employees6072026年10月10日 更新

Failure taxonomy and allowed/forbidden repairs for a failing E2E test. Use when a Playwright/Maestro/Detox/XCUITest/Espresso/Appium test fails and you must decide whether to repair the test or route to a real bug.

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。

HoangNguyen0403/agent-skills-standard5732026年10月12日 更新

PTES-aligned penetration testing methodology for backend, frontend, and mobile. Provides attack taxonomy, exploit techniques per vulnerability class, and platform-specific test matrices. Use when executing pentest workflow, planning security assessments, mapping attack surfaces, or building threat models.

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。

HoangNguyen0403/agent-skills-standard5732026年10月12日 更新

SaaS analytics event taxonomy, metric formulas (MRR, churn, LTV), provider-agnostic tracking, funnel analysis, cohort setup, and privacy-respecting instrumentation.

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。

vibeeval/vibecosystem5332026年8月9日 更新

Product analytics - event taxonomy, funnel analysis, A/B testing, retention metrikleri.

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。

vibeeval/vibecosystem5332026年8月9日 更新

Provides design token system and theming framework for consistent, customizable UI styling across all components. Covers complete token taxonomy (color, typography, spacing, shadows, borders, motion, z-index), theme switching (CSS custom properties, theme providers), RTL/i18n support (CSS logical properties), and accessibility (WCAG contrast, high contrast themes, reduced motion). This is the foundational styling layer referenced by ALL component skills. Use when theming components, implementing light/dark mode, creating brand styles, customizing visual design, ensuring design consistency, or supporting RTL languages.

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。

ancoleman/ai-design-components5252025年12月11日 更新