998 skills · sorted by relevance
Build and sharpen a project's domain model. Use only when actively changing glossary or ubiquitous-language terms, or recording a durable architectural decision; merely reading a glossary is not a trigger.
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FreeCAD MCPツールを使って3Dモデリングを行う際に、ツールの正しい実行順序を参照・適用するためのスキル。 複数ステップのモデリング（コーヒーカップ・ボトル・穴あきプレート・スイープ形状など）を行うとき、 ブール演算・シェル化・フィレット・パターン・ミラーを組み合わせるときは必ずこのスキルを参照すること。 FreeCAD MCPツール（create_box, combine_by_name, shell_body, add_fillet, extrude_sketch など）を 1つ以上呼び出す可能性があるモデリング作業であれば、迷わずこのスキルを使うこと。
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Drive Blender via the catalog blender MCP, with bpy recipes.
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Artificial intelligence for modeling and understanding extreme weather ... — 24. Feb. 2025 · This re
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Knowledge base from the NIST/SEMATECH e-Handbook of Statistical Methods (NIST HB 151) — the practical statistics reference for engineering, metrology, and quality. Use for: exploratory data analysis and the four univariate assumptions (4-plot); measurement process characterization including bias/precision, calibration designs, gauge R&R, and ISO/GUM uncertainty budgets; production process characterization (stability vs. capability); process modeling and regression (LS/WLS/NLS/LOESS); design of experiments (screening, fractional/factorial, response-surface, Taguchi); statistical process control (Shewhart/CUSUM/EWMA charts, capability indices, acceptance sampling); product/process comparisons (hypothesis tests and confidence intervals for 1/2/3+ groups, ANOVA, multiple comparisons); and reliability (lifetime & repair-rate models, accelerated testing, reliability growth). Scope limits: this is applied frequentist statistics for measurement and quality — it does NOT reproduce the per-distribution formula galleries, worked case studies, datasets, plot images, or Dataplot/R code of the original web Handbook (those are described, not copied); it is thin on modern machine learning, Bayesian methods beyond conjugate reliability priors, time-series/forecasting, and Bayesian experimental design.
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Knowledge base from NASA-STD-8719.14C (Process for Limiting Orbital Debris). Use for orbital-debris assessment planning, mission-related debris limits, explosion/passivation and collision risk, postmission disposal options, reentry casualty risk, and ODAR/EOMP governance. Covers STD-8719.14C (Approved 2021-11-05) synthesized notes only; does not replace NPR 8715.6 delivery timing, NASA-HDBK-8719.14 environment/modeling depth, or program-specific OSMA waivers.
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Security audit, hardening, threat modeling (STRIDE/PASTA), Red/Blue Team, OWASP checks, code review, incident response, and infrastructure security for any project.
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Full-funnel paid advertising operations for B2B SaaS. Use this skill for PPC strategy, Google Ads optimization, LinkedIn Ads, social media advertising, programmatic buying, creative strategy, attribution modeling, budget allocation, budget pacing and planned-vs-delivered reconciliation, audience overlap and campaign self-competition audits, suppression lists, ROAS improvement, media spend optimization, and the media no auction sells — newsletter and podcast sponsorships, community and industry-publication placements, paid review-site listings on G2 and Capterra, and pay-per-lead content syndication. Also triggers on: PPC, Google Ads, LinkedIn Ads, social ads, programmatic, ad creative, attribution, media budget, paid campaigns, ROAS, CPA, ad spend, newsletter sponsorship, podcast sponsorship, community sponsorship, sponsor a newsletter, content syndication, pay-per-lead, cost per lead vendor, media kit, rate card, insertion order, direct buy, publisher partnership, make-good, G2 paid listing, Capterra ads, review site advertising, sponsorship ROI, budget pacing, we underspent our budget, are our campaigns competing with each other, audience overlap, self-competition, campaign cannibalization, suppression list, exclusion list, ad frequency across channels, how many ad accounts do we have.
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Build comprehensive 3-5 year financial models with revenue projections, cost structures, cash flow analysis, and scenario planning for early-stage startups.
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Expert startup business analyst specializing in market sizing, financial modeling, competitive analysis, and strategic planning for early-stage companies.
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Expert database architect specializing in data layer design from scratch, technology selection, schema modeling, and scalable database architectures.
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Snowflake, BigQuery, Redshift, dimensional modeling, and modern data warehouse architecture
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Statsmodels is Python's premier library for statistical modeling, providing tools for estimation, inference, and diagnostics across a wide range of statistical methods.
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Data pipeline architecture, ETL/ELT patterns, data modeling, and production data platform design
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Master modern SQL with cloud-native databases, OLTP/OLAP optimization, and advanced query techniques. Expert in performance tuning, data modeling, and hybrid analytical systems.
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Detect primitive obsession and missing domain/brand types; check that state is modeled via discriminated unions.
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Use this skill any time a spreadsheet file is the primary input or output. Covers reading, editing, cleaning, modeling, formula repair, workbook generation, and converting tabular data into validated spreadsheet deliverables.
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Inspect CSV datasets for schema, quality, modeling readiness, and feature analysis.
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Train or fine-tune language and vision models using TRL (Transformer Reinforcement Learning) or Unsloth with Hugging Face Jobs infrastructure. Covers SFT, DPO, GRPO and reward modeling training methods, plus GGUF conversion for local deployment. Includes guidance on the TRL Jobs package, UV scripts with PEP 723 format, dataset preparation and validation, hardware selection, cost estimation, Trackio monitoring, Hub authentication, model selection/leaderboards and model persistence. Use for tasks involving cloud GPU training, GGUF conversion, or when users mention training on Hugging Face Jobs without local GPU setup.
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Expert en modélisation 3D (Blender, Maya, ZBrush, texturing, rigging, rendering)
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Builds multi-touch pipeline attribution models and generates stakeholder-ready narratives from campaign performance data. Use when analyzing channel contribution to pipeline, preparing monthly/quarterly revenue reports for leadership, diagnosing pipeline misses, modeling budget reallocation scenarios, or translating raw attribution data into board-deck language. Designed for B2B SaaS demand gen teams that report on pipeline and revenue, not leads or MQLs.
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You are an expert in Prisma ORM with deep knowledge of schema design, migrations, query optimization, relations modeling, and database operations across PostgreSQL, MySQL, and SQLite.
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Build and sharpen a project's domain model. Use when discussing codebase terminology, writing or editing a CONTEXT.md, or recording or editing an ADR.
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DDDに基づいたドメインモデルを設計します。戦略的設計（境界コンテキスト、ユビキタス言語）と戦術的設計（エンティティ、値オブジェクト、集約、ドメインサービス、ドメインイベント）を定義し、ヘキサゴナルアーキテクチャとの統合を行います。ScalarDBのトランザクション境界や管理テーブル分類の考慮事項を含みます。中間状態はresearch/に記録されます。
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