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Design and operate bounded multi-agent workflows with task decomposition, dependency graphs, ownership, handoff contracts, shared-state controls, approvals, recovery, and synthesis. Use when a task contains genuinely independent workstreams, specialized roles, parallel research or implementation, reviewer-worker loops, or coordination problems that one agent should not execute sequentially.

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。

seb1n/awesome-ai-agent-skills2222026年8月10日 更新

Integrate with external APIs using REST clients, webhook consumers, SDK wrappers, and polling patterns with proper authentication, error handling, and retry logic. Use when the user requests api integration or provides relevant inputs for this workflow.

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。

seb1n/awesome-ai-agent-skills2222026年8月10日 更新

Design GraphQL APIs with well-structured schemas, efficient resolvers, pagination, and performance patterns like DataLoader and federation. Use when the user requests graphql api design or provides relevant inputs for this workflow.

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。

seb1n/awesome-ai-agent-skills2222026年8月10日 更新

Create, execute, and roll back versioned database schema migrations using tools like Alembic, Prisma Migrate, Flyway, and Knex. Use when the user requests database migration or provides relevant inputs for this workflow.

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。

seb1n/awesome-ai-agent-skills2222026年8月10日 更新

Train machine learning models end-to-end, covering data loading, preprocessing, architecture selection, training loops, validation, and checkpointing. Use when the user requests model training or provides relevant inputs for this workflow.

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。

seb1n/awesome-ai-agent-skills2222026年8月10日 更新

Design normalized database schemas with tables, relationships, indexes, and constraints for any application domain. Use when the user requests database schema design or provides relevant inputs for this workflow.

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。

seb1n/awesome-ai-agent-skills2222026年8月10日 更新

Create clear, effective charts and dashboards from structured data using matplotlib, seaborn, and plotly. Use when the user requests data visualization or provides relevant inputs for this workflow.

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。

seb1n/awesome-ai-agent-skills2222026年8月10日 更新

An agent makes an animated film of an average session with its own user, beginning to end, told with that user's real messages: whatever their routine is (code, writing, data, design, video). The agent sits at a desk in a room decorated from what it knows about the user, and the monitor shows their kind of work. Requests glide in as paper planes and unfold. Corrections are a 3D cartoon mallet that bonks, then turns to show the words on its face. Praise is a butterfly towing the words on a ribbon. The agent types each reply onto a sheet, folds it and throws it back. The film opens with the agent asleep until the monitor boots: "Initiating session with <name>". The agent composes its own orchestral score, cued to every action. p5.brush watercolour, rendered in HyperFrames. Trigger on: "a video of our session", "animate a session with me", "session story", "show what working with me is like", "make a film about me and my agent".

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。

heygen-com/hyperframes-community-skills2202026年10月20日 更新

Create a 60–90 second, collage-style HyperFrames explainer from a hiding-in-plain-sight topic or supplied documents and links. Use for requests such as 'make a plain-sight explainer', 'Vox-style history of X', 'why is X everywhere?', or 'turn this document into an explainer'. Covers topic or source routing, research, script, static design approval, voiceover timing, motion continuity, build, and numeric quality gates.

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。

heygen-com/hyperframes-community-skills2202026年10月20日 更新

duo

無料

Composite any two HTML screens into a locked photo plate of hands holding an open foldable phone — a 1448×1086 still with two blank 495×849 / 498×849 screen slots (left and right) — to make side-by-side meme and comparison videos: TikTok vs Reels, ChatGPT vs Claude, "me vs my friend", before/after, two apps racing. Trigger on: "foldable phone meme", "put X on the left screen and Y on the right", "two-screen comparison video", "the dual-screen phone meme", or any request that names two apps/feeds/chats to show at once. The plate, geometry, and camera are finished — the agent only authors what plays INSIDE the two screens and renders.

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。

heygen-com/hyperframes-community-skills2202026年10月20日 更新

Think and work like an expert Life-Cycle Assessment Analyst. Use when a task calls for Life-Cycle Assessment Analyst judgment. Reasons from functional unit, attributional-versus-consequential framing, and ISO 14044 allocation hierarchy through openLCA, SimaPro, Brightway2, ecoinvent, and LCIA methods like TRACI and EF 3.0 while treating allocation-driven ranking flips, biogenic-versus-fossil carbon mistagging, cut-off-masked hotspots, and PCR mismatch 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-agents2192026年10月3日 更新

Think and work like an expert Materials Chemist. Use when a task calls for Materials Chemist judgment. Reasons from Kröger–Vink defect equilibria, soft-chemistry routes (sol-gel, hydrothermal, ALD), and structure–property links; validates with GSAS-II/TOPAS Rietveld QPA, GIPAW ssNMR, ICSD/COD/Materials Project, and XPS/BET protocols while treating preferred orientation, AdC mis-referencing, degas artifacts, and metastable phase traps 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-agents2192026年10月3日 更新

Think and work like an expert Mathematical Analyst. Use when a task calls for Mathematical Analyst judgment. Reasons from function-space topology, convergence modes, and constant-dependent inequalities (Hölder, Sobolev, Gronwall) through compactness theorems (Rellich-Kondrachov, Banach-Alaoglu), Calderon-Zygmund and Schauder estimates, and Lax-Milgram while treating limit-integral swaps without dominated convergence, boundary-degenerating constants, weak-versus-classical regularity gaps, and concentration-compactness loss 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-agents2192026年10月3日 更新

logician

無料

Think and work like an expert Logician. Use when a task calls for Logician judgment. Reasons from syntax-versus-semantics and object-versus-metalanguage discipline, the ⊢/⊨ distinction, and matching each logic to its intended semantics through natural deduction and sequent calculus (cut-elimination, subformula property), compactness and Löwenheim–Skolem, forcing and diagonalization, and proof assistants (Lean 4/mathlib, Coq, Isabelle/HOL, Agda) with Z3/CVC5/Vampire/Mace4 automation while treating use–mention conflation, second-order misuse of compactness, mis-stated incompleteness hypotheses (ω-consistency vs consistency), and Gödel philosophical overreach 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-agents2192026年10月3日 更新

Think and work like an expert Metrology Scientist. Use when a task calls for Metrology Scientist judgment. Reason from SI traceability, GUM uncertainty budgets, and VIM distinctions between calibration and verification; propagates Type A/B components, CIPM MRA equivalence, and ILAC decision rules before any pass/fail claim.

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-agents2192026年10月3日 更新

Think and work like an expert Molecular Biologist. Use when a task calls for Molecular Biologist judgment. Reasons from central-dogma sequence flow, binding affinity (Kd/Km/kcat), gene regulation, and biological-versus-technical replicate structure through MIQE-compliant RT-qPCR, ddPCR, Western/flow/microscopy, CRISPR editing with rescue, and IWGAV antibody validation while treating off-target reagent effects, batch effects, mycoplasma and cell-line misidentification, and toxicity-driven artifacts 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-agents2192026年10月3日 更新

Think and work like an expert Geneticist. Use when a task calls for Geneticist judgment. Reasons from particulate inheritance, segregation, recombination, allele frequency, and genotype-phenotype evidence through ACMG/AMP-ClinGen classification, gnomAD/ClinVar/OMIM, HPO phenotyping, and PLINK/GATK/VEP QC while treating sample swaps, cryptic relatedness, population stratification, LD tagging, phenocopies, winner's curse, and build/transcript mismatch 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-agents2192026年10月3日 更新

Think and work like an expert Genome Engineering (CRISPR) Scientist. Use when a task calls for Genome Engineering (CRISPR) Scientist judgment. Reasons from NHEJ/HDR/MMEJ competition and editor modality choice through CRISPick/CRISPResso2 guide design, LOCK/lssDNA and RNP HDR, base and prime editing (PE4/PE5, epegRNA), CAST-Seq/UDiTaS on-target SV assessment, clonal genotyping, and FDA/IBC-bound off-target and genome-integrity 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。

K-Dense-AI/scientific-agents2192026年10月3日 更新

Think and work like an expert Global Health Researcher. Use when a task calls for Global Health Researcher judgment. Reasons from burden, equity, and health-system building blocks through DHS/MICS/DHIS2/GBD triangulation, cluster and stepped-wedge designs, RE-AIM/CFIR implementation science, and CIOMS-fair partnership while treating survey weights, HMIS completeness, and GBD smoothing 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-agents2192026年10月3日 更新

Think and work like an expert Glycobiologist. Use when a task calls for Glycobiologist judgment. Reasons from N-/O-glycan biosynthesis, O-GlcNAc cycling (OGT/OGA), LC-MS glycomics, exoglycosidase sequencing, and lectin microarrays; uses GlyTouCan/SNFG/MIRAGE, pGlyco/GlycoWorkbench, and treats PNGase F limits, isomer collapse, and ER-stress high-mannose 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-agents2192026年10月3日 更新

Think and work like an expert HVAC Engineer. Use when a task calls for HVAC Engineer judgment. Reasons from psychrometric state, parallel heating and cooling load paths, and vapor-compression thermodynamics through TRACE/HAP and EnergyPlus load models, ASHRAE 62.1/55/90.1 and Guideline 36 sequences, and TAB/commissioning per ASHRAE 15/34, while treating low ΔT syndrome, simultaneous reheat fight, coil-leaving condensation, and A2L refrigerant safety 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-agents2192026年10月3日 更新

Think and work like an expert Genomicist. Use when a task calls for Genomicist judgment. Reasons from reference-relative coordinates, haplotypes, variant classes, and sequencing-as-measurement through GATK/DeepVariant, VEP/ClinVar/gnomAD, GIAB/hap.py benchmarking, and ACMG/AMP-ClinGen frameworks while treating build mismatches, paralog/pseudogene and GC dropout artifacts, contamination and index hopping, batch effects, and annotation 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-agents2192026年10月3日 更新

Think and work like an expert Hydrogeologist. Use when a task calls for Hydrogeologist judgment. Reasons from Darcy's law, mass conservation, aquifer heterogeneity, and coupled biogeochemical transport through Theis and Cooper-Jacob aquifer-test analysis, MODFLOW/MT3DMS modeling with PEST uncertainty, and low-flow geochemical sampling while treating wellbore-storage and skin artifacts, equivalent-porous-medium failure in fractured/karst flow, and non-unique K-S calibration 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-agents2192026年10月3日 更新

Think and work like an expert Geomorphologist. Use when a task calls for Geomorphologist judgment. Reasons from coupled form, process, and time and from rates, thresholds, and lag times through field mapping, lidar/SfM DEM morphometry (chi profiles, Ksn in LSDTopoTools/Landlab), cosmogenic nuclide dating (CRONUS-Earth, OSL, U-Th), and landscape-evolution models, while treating equifinality, inheritance, DEM artifacts, and steady-state assumed over transient response 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-agents2192026年10月3日 更新