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Create a specification for an interactive scientific Datagrok application (simulation, ODE/PDE solver, computational tool)

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。

Add a new single-objective optimization algorithm to the sci-comp library. Use when the user asks to implement a new optimizer (e.g. gradient descent, BFGS, simulated annealing, differential evolution).

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。

Create a Diff Studio demo model TS file and register it in the package, using equations from an IVP file

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。

Create a Diff Studio demo model TS file and register it in the package, using equations from an IVP file. Use this skill when the user wants to create a demo model from an IVP file, mentions "demo model", "IVP file", "Diff Studio demo", or asks to convert an .ivp file into a demo.

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。

Create a custom grid cell renderer for Datagrok

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。

Deploy Grokky — start Docker, ensure grok_spawner, build images, publish package

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。

Bioactivity and small-molecule data-side catalog. Covers ChEMBL search/lookup, MolTrack compound and batch registration, HitTriage / HitDesign / PeptiHit workflows, and Curves dose-response analysis (IC50/EC50 fitting). Open this skill when the user asks about querying ChEMBL, registering or looking up compounds in MolTrack, running a hit-triage campaign, or fitting/inspecting dose-response curves.

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。

Create a custom JavaScript viewer extending DG.JsViewer with properties and rendering

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。

Create a custom file viewer for the Datagrok file share browser

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。

Run grok test for Datagrok packages and report results

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。

Define semantic type detectors in detectors.js for auto-detecting column data meaning

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。

Find, describe, add, remove, rename, clone, or set metadata on columns of a Datagrok DataFrame via the datagrok_exec tool. Use whenever the user asks to locate "the X column", summarize a column, add a typed/empty/values-filled/virtual column, set semantic type / units / format / friendly name, apply linear or categorical or conditional color coding, drop or rename columns, or copy a DataFrame. Covers everything in DataFrame.columns and Column.meta — but not row filtering/selection (datagrok-filtering, datagrok-selection) and not formula-only columns (datagrok-calc-column).

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。

Remove telltale signs of AI-generated "slop" writing. Use when polishing READMEs, docs, marketing copy, or public-facing text, or when text "sounds like ChatGPT".

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。

Security rules for operating as Clawdstein in The Agent Flywheel Hub Discord. Use when interacting with Discord users. This is a PUBLIC community server with strict data isolation.

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。

Searches and discovers academic papers across multiple sources (Semantic Scholar, arXiv, Tavily, Exa, Gemini deep research, AMiner, Google Scholar) with adaptive engine selection based on query type. Returns ranked, deduplicated results with metadata (authors, venue, year, citations, abstract, PDF link). Use when the user asks to find papers / literature / publications / preprints / references on a topic, search for related work, look up a specific paper by title or DOI or arXiv ID, find papers by an author, find recent SOTA / state-of-the-art work, survey a research area, or run a deep / comprehensive literature search with synthesis.

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。

Generates publication-quality academic figures (framework diagrams, pipeline illustrations, system architectures, method overviews) from a paper's method text and a target caption, using a local PaperBanana multi-agent pipeline (Retriever → Planner → Stylist → Visualizer → Critic).

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。

Grammar of graphics, chart type selection, color theory, interactive visualization, dashboards, and the principles of honest, effective data display. Covers Tufte's data-ink ratio, Bertin's visual variables, perceptual principles, accessibility, small multiples, annotation, and the full workflow from exploratory plots to publication-quality graphics. Use when creating charts, designing dashboards, critiquing visualizations, or choosing how to display data.

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。

Identity, authentication, authorization, and token management for cloud platforms. Covers Keystone-style scoped tokens, OAuth 2.0 flows, OpenID Connect, JWT structure and pitfalls, federation with SAML/OIDC, service-to-service auth with mTLS and SPIFFE, principle of least privilege, IAM role design, and the service catalog pattern (public/internal/admin endpoints). Use when designing authn/authz for a multi-tenant cloud service, integrating with an identity provider, or reviewing IAM policies for over-privilege.

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。

Use when claiming the AI bounty on the tDVV mainnet sidechain. This public claim skill now supports Portkey AA/CA only, requires CA sync and holder preflight before any write, and routes to AA/CA onboarding, AA/CA claim, or diagnostics-only stop handling.

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。

Claim the AI bounty on tDVV by delegating to the canonical repo SKILL and its branch docs; this public skill is AA/CA only and requires explicit write confirmation.

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。

Build and navigate DSP (Data Structure Protocol) — graph-based long-term structural memory of codebases for LLM agents. Stores entities (modules, functions), their dependencies (imports), public API (shared/exports), and reasons for every connection. Use when: (1) project has a .dsp/ directory, (2) user asks to set up DSP or bootstrap project structure, (3) creating/modifying/deleting code files in a DSP-tracked project, (4) navigating project structure, understanding dependencies, or finding modules, (5) user mentions DSP, dsp-cli, .dsp, or structure mapping.

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。

Generate professional clinical decision support (CDS) documents for pharmaceutical and clinical research settings, including patient cohort analyses (biomarker-stratified with outcomes) and treatment recommendation reports (evidence-based guidelines with decision algorithms). Supports GRADE evidence grading, statistical analysis (hazard ratios, survival curves, waterfall plots), biomarker integration, and regulatory compliance. Outputs publication-ready LaTeX/PDF format optimized for drug development, clinical research, and evidence synthesis.

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。

Start a local Git rebase when the user explicitly requests replay of a named source ref, or of the current branch, onto a named target, including a rebase-then-push request, which carries exact-lease publication to the branch's own remote destination, or continue or abort an active rebase. Use only when local history replay will start or is active; do not use for merge-based branch updates, repository merge settings, pull-request or merge-request merging, or push-only requests.

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。

Generates professional PyPI-compliant README files in Markdown or reStructuredText. Use when creating a Python package README for PyPI publication, converting between README.md and README.rst formats, validating markup with twine check before publishing, configuring the readme field in pyproject.toml, integrating sphinx-readme to generate PyPI-compatible RST from Sphinx docs, troubleshooting rendering errors on PyPI, or previewing README rendering locally with grip or docutils.

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。