Test and debug browser UIs using Chrome DevTools MCP — DOM inspection, console errors, network requests, performance traces, and visual verification. Load when building or debugging anything that renders in a browser, verifying a UI fix, profiling Core Web Vitals in a real page, or the user asks for browser testing with DevTools. Requires chrome-devtools MCP configured. Not for backend-only or CLI work. Pairs with frontend-design and performance-optimization.
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dvy1987/agent-loom☆ 32026년 8월 8일 업데이트
Backend architecture patterns, API design, database optimization, and server-side best practices for Node.js, Express, and Next.js API routes.
한국어 요약은 준비 중입니다. 원문 설명을 표시하고 있습니다.
nimoqup046-collab/agora☆ 32026년 3월 26일 업데이트
ClickHouse database patterns, query optimization, analytics, and data engineering best practices for high-performance analytical workloads.
한국어 요약은 준비 중입니다. 원문 설명을 표시하고 있습니다.
nimoqup046-collab/agora☆ 32026년 3월 26일 업데이트
Frontend development patterns for React, Next.js, state management, performance optimization, and UI best practices.
한국어 요약은 준비 중입니다. 원문 설명을 표시하고 있습니다.
nimoqup046-collab/agora☆ 32026년 3월 26일 업데이트
Optimize Bazel builds for large-scale monorepos. Use when configuring Bazel, implementing remote execution, or optimizing build performance for enterprise codebases.
한국어 요약은 준비 중입니다. 원문 설명을 표시하고 있습니다.
nimoqup046-collab/agora☆ 32026년 3월 26일 업데이트
Comprehensive AWS cost analysis and optimization recommendations using AWS CLI and Cost Explorer
한국어 요약은 준비 중입니다. 원문 설명을 표시하고 있습니다.
nimoqup046-collab/agora☆ 32026년 3월 26일 업데이트
Angular performance optimization and best practices guide. Use when writing, reviewing, or refactoring Angular code for optimal performance, bundle size, and rendering efficiency.
한국어 요약은 준비 중입니다. 원문 설명을 표시하고 있습니다.
nimoqup046-collab/agora☆ 32026년 3월 26일 업데이트
Optimize content for AI search and LLM citations across AI Overviews, ChatGPT, Perplexity, Claude, Gemini, and similar systems. Use when improving AI visibility, answer engine optimization, or citation readiness.
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nimoqup046-collab/agora☆ 32026년 3월 26일 업데이트
Create, iterate, and scale paid ad creative for Google Ads, Meta, LinkedIn, TikTok, and similar platforms. Use when generating headlines, descriptions, primary text, or large sets of ad variations for testing and performance optimization.
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nimoqup046-collab/agora☆ 32026년 3월 26일 업데이트
Quantifies biodiversity from species abundance/incidence tables using Hill numbers (iNEXT) with coverage-based rarefaction-extrapolation (Chao & Jost 2012), asymptotic richness via Chao1/ACE/jackknife as a lower bound, Baselga turnover/nestedness partition with the Podani alternative as sensitivity check, mandatory Hellinger transformation before ordination (Legendre & Gallagher 2001), Faith PD and SES_MPD/SES_MNTD with explicit null-model choice, and Maire 2015 functional-diversity dimensionality optimization. Use when comparing diversity across sites with unequal sampling effort, picking the right richness estimator for singleton-heavy amplicon data, partitioning beta diversity into turnover vs nestedness, reporting Hill-number effective species counts rather than raw entropies, computing SES_MPD with explicit null-model justification, or deciding whether to apply standard metrics to compositional amplicon data. Not for clinical 16S microbiome diversity (see microbiome/diversity-analysis).
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peacezha/HPClaw☆ 32026년 10월 11일 업데이트
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.
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peacezha/HPClaw☆ 32026년 10월 11일 업데이트
Generates 3D conformer ensembles using RDKit ETKDGv3 with knowledge-enhanced distance geometry, MMFF94/UFF force-field optimization, CREST + GFN2-xTB semi-empirical refinement, and macrocycle-aware torsion preferences. Provides explicit decision rules for single vs ensemble conformer use, RMSD pruning, energy windows, conformer count, and force-field choice. Use when preparing 3D ligands for docking, generating descriptor input for 3D QSAR, or sampling macrocycle/peptide conformational ensembles.
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peacezha/HPClaw☆ 32026년 10월 11일 업데이트
Performs 3D shape-based similarity searching using ROCS (OpenEye), USRCAT (ultra-fast), Open3DAlign (RDKit), ESPSim (electrostatic), and ShaEP with explicit handling of Tanimoto-Combo (shape + color), shape vs ECFP4 complementarity, conformer-ensemble searching, alignment optimization, and scaffold hopping. Use when searching for shape-mimicking compounds with different scaffolds, identifying bioisosteric replacements, prospective scaffold hopping, or expanding hit series beyond 2D similarity.
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peacezha/HPClaw☆ 32026년 10월 11일 업데이트
Performs alchemical free-energy calculations including relative binding free energy (RBFE / FEP+) and absolute binding free energy (ABFE) via OpenFE, FEP+, GROMACS, AMBER pmemd, and OpenMM with explicit lambda window scheduling, soft-core potentials, REST2 enhanced sampling, MBAR/BAR analysis, and cycle closure validation. Compares ML alternatives (Boltz-2 affinity, DeepDock). Use when ranking analogs by binding affinity beyond docking accuracy, performing prospective lead optimization, or validating SAR predictions.
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peacezha/HPClaw☆ 32026년 10월 11일 업데이트
Performs molecular similarity searching using Tanimoto, Tversky, Dice, and cosine coefficients on bit/count fingerprints with explicit choice rules for symmetric vs asymmetric measures, scaffold-hopping vs lead-optimization regimes, activity-cliff diagnosis, and large-library nearest-neighbor methods (BulkTanimoto, Annoy MHFP6, USRCAT). Use when ranking compounds by structural resemblance to a query, clustering libraries, finding analogs, or diagnosing activity cliffs.
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peacezha/HPClaw☆ 32026년 10월 11일 업데이트
Use when a dispatcher, operations manager, or owner asks how to plan loads to minimize empty (deadhead) miles, sequence freight efficiently, balance regional capacity, design dedicated loops, or build a load-pairing strategy across customers. Covers loaded-ratio math, lane balance, region-pair pricing, and software-supported optimization.
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x3allamerican/skills☆ 32026년 5월 17일 업데이트
Use when a carrier asks how to improve MPG, lower fuel cost per mile, manage fuel surcharge, set up a fuel-purchase strategy (in-network vs out-of-network), train drivers on fuel-efficient driving, spec new tractors for fuel economy, or benchmark fleet MPG against industry averages.
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x3allamerican/skills☆ 32026년 5월 17일 업데이트
Apply recognition-primed decision making to agents operating under time pressure, uncertainty, and ambiguous cues. Use for situation assessment, RPD-style action selection, and decision-support design in operational settings. NOT for batch optimization, static planning with full information, or tasks where exhaustive search is cheap and harmless.
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curiositech/port-daddy☆ 32026년 10월 19일 업데이트
Plan database migrations before executing them: risk assessment, dependency mapping, multi-service sequencing, rollback budgets, and stakeholder communication plans. Use when deciding HOW to migrate, not when writing the actual DDL. NOT for: writing migration SQL (use database-migration-manager), data ETL pipelines (use data-migration-specialist), query optimization, or ORM configuration.
한국어 요약은 준비 중입니다. 원문 설명을 표시하고 있습니다.
curiositech/port-daddy☆ 32026년 10월 19일 업데이트
Apply recognition-primed decision making to agents operating under time pressure, uncertainty, and ambiguous cues. Use for situation assessment, RPD-style action selection, and decision-support design in operational settings. NOT for batch optimization, static planning with full information, or tasks where exhaustive search is cheap and harmless.
한국어 요약은 준비 중입니다. 원문 설명을 표시하고 있습니다.
curiositech/port-daddy☆ 32026년 10월 19일 업데이트
Schema design, normalization decisions, indexing strategies, and migration safety for relational databases. Use when designing tables, choosing between normalize vs denormalize, selecting index types, planning zero-downtime migrations, or setting up connection pooling. Activate on "schema design", "normalization", "denormalization", "foreign key", "index strategy", "migration", "connection pooling", "composite key", "surrogate key", "soft delete", "polymorphic association". NOT for PostgreSQL-specific query tuning or EXPLAIN analysis (use postgresql-optimization), NoSQL or document database design, or cloud database provisioning.
한국어 요약은 준비 중입니다. 원문 설명을 표시하고 있습니다.
curiositech/port-daddy☆ 32026년 10월 19일 업데이트
Digital equity and trauma-informed design for marginalized populations. Activate on "accessibility", "offline-first", "trauma-informed", "reentry", "recovery population", "shared device", "unstable phone", "digital equity", "design justice", "low-literacy", "intermittent access". NOT for general UX, marketing optimization, or enterprise SaaS design.
한국어 요약은 준비 중입니다. 원문 설명을 표시하고 있습니다.
curiositech/port-daddy☆ 32026년 10월 19일 업데이트
Safe database migration manager for zero-downtime DDL changes and rollback plans. Activate on: database migration, schema change, DDL, rollback plan, zero-downtime migration, Prisma migrate, Drizzle kit, Flyway, column rename, table alter. NOT for: query optimization (use database-optimizer), ORM modeling (use data-pipeline-engineer), backup/restore (use devops-automator).
한국어 요약은 준비 중입니다. 원문 설명을 표시하고 있습니다.
curiositech/port-daddy☆ 32026년 10월 19일 업데이트
Expert in drone systems, computer vision, and autonomous navigation. Specializes in flight control, SLAM, object detection, sensor fusion, and path planning. Activate on "drone", "UAV", "SLAM", "visual odometry", "PID control", "MAVLink", "Pixhawk", "path planning", "A*", "RRT", "EKF", "sensor fusion", "optical flow", "ByteTrack". NOT for domain-specific inspection tasks like fire detection, roof damage assessment, or thermal analysis (use drone-inspection-specialist), GPU shader optimization (use metal-shader-expert), or general image classification without drone context (use clip-aware-embeddings).
한국어 요약은 준비 중입니다. 원문 설명을 표시하고 있습니다.
curiositech/port-daddy☆ 32026년 10월 19일 업데이트