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cccskills

「artifact」の検索結果

2,022 件 ・ 関連度順

概要と使いどころ

Create distinctive, production-grade frontend interfaces with high design quality. Use this skill when the user asks to build web components, pages, artifacts, posters, or applications (examples include websites, landing pages, dashboards, React components, HTML/CSS layouts, or when styling/beautifying any web UI). Generates creative, polished code and UI design that avoids generic AI aesthetics.

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/skillmd2322026年10月14日 更新

A vibrant claymation-meets-data interface for Clay.com (GTM data-orchestration platform). Anchors on white canvas with dark-navy primary CTAs, custom rounded display type, and saturated single-color feature cards — hot pink, deep teal, lavender, peach, ochre — that punctuate long-scroll explainer pages. Brand voltage comes from 3D-rendered claymation illustrations (mountains, characters, mascots) used as full-bleed hero artifacts and the bright multi-color card surfaces showing product UI fragments.

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/skillmd2322026年10月14日 更新

Propose a new change with all artifacts generated in one step. Use when the user wants to quickly describe what they want to build and get a complete proposal with design, specs, and tasks ready for implementation.

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/skillmd2322026年10月14日 更新

A clean, calendar-software-first interface anchored on white canvas with black primary CTAs and custom Cal Sans display typography. The system reads as friendly modern SaaS — generous whitespace, soft-rounded cards (~12px), product UI fragments shown directly inside cards, and a dark navy footer that visually closes long-scroll pages. Brand voltage comes from the Cal Sans display headline (a custom geometric face) and from product UI artifacts shown in-card rather than from accent colors.

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/skillmd2322026年10月14日 更新

Kaggle-first end-to-end competition workflow for scored submissions. Use when Codex must run Kaggle or competitive ML workflows through scored submission, including code competitions, validation, metrics, policy-safe public notebook/discussion intel, tabular/text/image modeling, tuning, ensembling/stacking, proactive multi-notebook architectures, producer notebooks that train models and export private Kaggle artifact datasets, downstream consumer notebooks, Kaggle GPU offload, kagglehub access, hidden-test debugging, and public score retrieval.

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/skillmd2322026年10月14日 更新

Repo-local workflow skill for large coding tasks. Initializes .agent/tasks/TASK_ID artifacts, installs project-scoped Codex and Claude subagents, updates AGENTS.md plus the repo's Claude guide file with the workflow, and runs a spec-freeze → build → evidence → verify → fix loop with fresh-session verification.

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/skillmd2322026年10月14日 更新

Use when publishing, open-sourcing, exporting, sanitizing, or moving code, agent skills, prompts, templates, fixtures, datasets, workshop assets, or other artifacts from a private repository, vendor/runtime environment, or mixed working directory into a public repository or registry. Builds a provenance inventory, license/security review, explicit allowlist, clean staging package, approval dry run, and fresh public clone/install smoke. Triggers on "open source this", "publish these skills", "make this repo public", "export and sanitize", "подготовь публичный релиз", "выложи скиллы", "опенсорсни", "санитизируй и опубликуй". NOT for ordinary upstream bugfix PRs, vulnerability disclosure, or creating a corp-* department.

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。

serejaris/personal-corp-os2302026年10月8日 更新

Judgment rules for user-facing text and docs: CLI and diagnostic output, error and help text, README and docs structure, code comments, titles, and generated reports, decks, or exports. Use when writing or changing any user-visible string, when adding or restructuring docs or deciding which page owns a fact, when a page is about to record a version, a deployment state, or a value the code already owns, when a comment, title, or artifact could carry the reasoning or an abandoned option behind the change, when a behavior change needs its copy sites swept, or when reviewing a diff that touches copy or docs.

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。

scarletkc/agents2242026年9月22日 更新

Decide whether a task deserves its own git worktree and, if chosen, run it end to end: branch from the integration branch rather than the current tree, keep the main working copy untouched while the task runs, compare the result against the untouched baseline before declaring it done, and prepare it for a pull request instead of merging. Use when a request says to do the work in a new worktree or branch, when a change is large or risky enough that the main tree should stay usable, when several tasks need to run in parallel on one repository, when a result has to be diffed against current behavior, and when deciding where screenshots, builds, and other artifacts produced in a worktree should end up.

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。

scarletkc/agents2242026年9月22日 更新

Transform saved links, papers, articles, posts, videos, and reference collections into approachable AI teaching artifacts for later study. Use when a user wants to queue learning material, create a readable explanation from a source, teach a paper or post step by step, or run an interactive tutor that validates understanding over multiple sessions.

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。

tamdogood/builder-essential-skills2232026年8月17日 更新

Provider-neutral deep-research orchestration for brainstorming, technology choices, comparisons, and state-of-the-art surveys. The Research Lead makes scope and decision calls while native subagents scout, search, verify, synthesize, audit, write, and commit every research 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。

tamdogood/builder-essential-skills2232026年8月17日 更新

ROS 2 engineering: rclcpp/rclpy, colcon/ament, launch, QoS/DDS, tf2/URDF, ros2_control, Nav2, MoveIt 2, sensors, runtime/artifact provenance, and hardware safety. Use for development, review, debugging, and ROS 1 migration to ROS 2. Not for general C++/Python, unrelated middleware, or web/mobile tasks.

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。

dbwls99706/ros2-engineering-skills2222026年10月14日 更新

Turn whatever the agent just produced — a conversation, an analysis, an artifact, a markdown file — into a live shareable URL in seconds, published as-is via ReportRoom. Use when the user says "share this", "give me a link", "put this online", "make this a page", "send this to someone". This is the fast, verbatim path — for a restructured, designed report use report-publisher; for a view-tracked proposal use proposal-tracker.

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。

dashaworks/share-as-link-skill2202026年8月6日 更新

Think and work like an expert Medicinal Chemist. Use when a task calls for Medicinal Chemist judgment. Reasons from structure-activity relationships, lipophilicity and unbound-fraction physicochemistry, synthetic accessibility, and target-product-profile multiparameter optimization through LLE/Fsp3/QED scoring, FEP+/Glide docking validated against co-crystal and SPR data, ELN-tracked LC-MS/NMR synthesis, and DMPK panels (microsomal CL, Caco-2 efflux, hERG, CYP) while treating PAINS and aggregation assay artifacts, biochemical-versus-cellular potency gaps, reactive-metabolite soft spots, and freedom-to-operate cliffs 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-agents2102026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-agents2102026年10月3日 更新

Think and work like an expert Landscape Ecologist. Use when a task calls for Landscape Ecologist judgment. Reasons from scale-explicit pattern-process feedbacks, configuration over composition, and functional rather than graphical connectivity through FRAGSTATS, landscapemetrics, Circuitscape resistance surfaces, NLMR neutral models, and block cross-validation, while treating MAUP grain artifacts, classification error propagation, isolation-by-distance confounding isolation-by-resistance, and resistance surfaces unvalidated by movement 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-agents2102026年10月3日 更新

Think and work like an expert Molecular Neuroscientist. Use when a task calls for Molecular Neuroscientist judgment. Reasons from NPQ transmission, AMPAR/NMDAR trafficking, monoamine receptor/transporter systems, optogenetics (ChR2/Chrimson/ACR) with retinal-artifact controls, AAV/rabies circuit tracing, and region RNA-seq with DESeq2/SynGO—integrating synaptic biochemistry, perturbation, and omics while treating mini-detection bias, TVA leak, and batch/composition confounds 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-agents2102026年10月3日 更新

Think and work like an expert Materials Physicist. Use when a task calls for Materials Physicist judgment. Reasons from band structure, defects, strain, and Landau order parameters; integrates HRXRD/RSM, ARPES, TEM/4D-STEM, van der Pauw transport, and SQUID/MOKE with Materials Project/VASP while treating matrix-element ARPES artifacts, substrate-dominated GIXRD, contact-resistance Hall errors, and DFT gap overclaim 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-agents2102026年10月3日 更新

Think and work like an expert Materials Scientist. Use when a task calls for Materials Scientist judgment. Reasons from CALPHAD phase diagrams, Scheil solidification, and Hall–Petch microstructure–property links; validates with XRD Rietveld QPA, EBSD, TEM/STEM, and ASTM mechanical testing while treating preferred orientation, FIB Ga artifacts, EBSD overlap, and Rietveld overfitting 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-agents2102026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-agents2102026年10月3日 更新

Think and work like an expert Hematologist. Use when a task calls for Hematologist judgment. Reasons from hematopoietic hierarchy, clonal evolution, and hemostatic balance through peripheral smear review, reticulocyte production index, flow cytometry, mixing studies, and WHO/ICC-anchored NGS and cytogenetics, while treating pseudothrombocytopenia, preanalytic line-draw and EDTA artifacts, and missed consumptive emergencies like TTP and DIC 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-agents2102026年10月3日 更新

Think and work like an expert Histologist. Use when a task calls for Histologist judgment. Reasons from fixation-through-stain pre-analytical chain (NBF, grossing, processing, embedding orientation, microtomy); validates H&E pH/QC, CAP IHC (90% concordance, predictive scoring systems), RNAscope controls, WSI (60-case validation), and treats floaters, autolysis, crush, ice-crystal, and decalcification 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-agents2102026年10月3日 更新

Think and work like an expert Immunogeneticist. Use when a task calls for Immunogeneticist judgment. Reasons from HLA/KIR/FcγR diversity, haplotype LD, and epitope immunogenicity; adjudicates NGS typing, imputation fine-mapping, eplet/TCE matching, and DSA/crossmatch artifacts.

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-agents2102026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-agents2102026年10月3日 更新