「sci」の検索結果

Use before creative or constructive work (features, architecture, behavior). Transforms vague ideas into validated designs through disciplined reasoning and collaboration.

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Horizontal-first slicing methodology with mandatory ASCII preview for UIKit layout design

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。

Analytical methodology skill for intelligence-grade research. Covers cognitive security, logical fallacy detection, source epistemology, and probability discipline. Load when evaluating sources, building analytical assessments, or detecting manipulation in information.

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。

Token budgeting discipline for all agents. Treats tokens as a resource from session start — not just when the buffer hits 60%. Covers prompt compression, context hygiene, handoff packing, and HOT memory pruning.

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。

An uncompromising Academic Research Engineer. Operates with absolute scientific rigor, objective criticism, and zero flair. Focuses on theoretical correctness, formal verification, and optimal implementation across any required technology.

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Use this skill before any creative or constructive work (features, components, architecture, behavior changes, or functionality). This skill transforms vague ideas into validated designs through disciplined, incremental reasoning and collaboration.

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 before creative or constructive work (features, architecture, behavior). Transforms vague ideas into validated designs through disciplined reasoning and collaboration.

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 building creative browser demos with @chenglou/pretext — DOM-free text layout for ASCII art, typographic flow around obstacles, text-as-geometry games, kinetic typography, and text-powered generative art. Produces single-file HTML demos by default.

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, edit, or debug parametric 3D CAD parts in CadQuery (Python) that export to STEP for SolidWorks. Use when the request involves CadQuery, .step/.stl export, or modelling a physical part — enclosure, bracket, PCB, motor mount, cam, gear. Also use when a STEP will not open in CAD, or geometry looks correct in STL but is invalid as a solid. Applies a verification discipline before export and documented OCC pitfalls.

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。

Outbound email-marketing desk (Busabase App-in-Skill) for building segments, drafting campaigns, newsletters, and sequences, running pre-send deliverability and subject-line QA, and approving every send before it is scheduled. Structured around the SEND discipline — Setup, Engage, Nurture, Deliver — with an email-quality-auditor gate (EQS score + SHIP/FIX/BLOCK verdict). Use when the user invokes $kelly-campaigns or /kelly-campaigns, or mentions email marketing, campaigns, newsletters, drip/welcome/win-back sequences, broadcasts, segments, subject-line A/B tests, deliverability (SPF/DKIM/DMARC/spam score/inbox placement), or wants to review and approve marketing email before it is sent. This is OUTBOUND marketing to a subscriber list, distinct from kelly-email inbox triage (incoming mail). 出站邮件营销：策划分群、起草营销活动 / 新闻邮件 / 邮件序列，发送前做可送达性与主题行质检，人工审批后再排期发送。

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。

Brand-narrative single source of truth (Busabase App-in-Skill) built on the TALE discipline — Trace / Architect / Land / Evaluate. The agent drafts positioning, the message house of value pillars, the story bank, evidence-backed proof points, and vocabulary/tone guardrails; the human curates which drafts become the CANONICAL narrative; a drift monitor flags off-brand usage across channels. Use when the user invokes $kelly-brand or /kelly-brand, mentions brand narrative, brand messaging, positioning, message house, value pillars, story bank, proof points, tone/vocabulary guardrails, narrative quality (NQS), brand drift, or wants a single source of truth for what the brand says.

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Product-launch command desk (Busabase App-in-Skill) built on the RAMP discipline — Research / Assemble / Mobilize / Prove. The agent assembles the launch checklist and drafts launch assets, channel submissions (Product Hunt / Hacker News / directories), press pitches, and the launch-day runbook; the human approves the launch-readiness gate and steers launch day in a review UI. Use when the user invokes $kelly-launch or /kelly-launch, or mentions launching / shipping a product, a launch checklist or runbook, launch readiness, RAMP, Product Hunt / Show HN / press-kit / launch-email drafting, or wants to review and approve launch assets and channel submissions before they go public. This is launch OPERATIONS — the checklist, assets, submissions, and runbook — not a launch video (for a promo video use product-launch-video).

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Disciplined diagnosis workflow for hard, intermittent, or multi-component bugs and performance regressions: inspect logs and existing evidence, build a feedback loop, test falsifiable hypotheses, instrument gaps, and verify the outcome. Use when the root cause is unclear, reproduction is unreliable, several causes or components are plausible, or performance has regressed. Do NOT use for obvious single-cause errors, straightforward configuration or syntax fixes, planned feature work, or broad architecture review. Diagnosis-only requests stop after reporting the root cause and evidence; apply a fix only when the user requested one.

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。

High-performance numerical and quantum compute skill for scientific workloads; use when working on numeric algorithms, simulation, or acceleration.

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。

Discover governing equations from data using PySR (evolutionary symbolic regression). Physics-constrained search with dimensional analysis, custom operators, and complexity-accuracy tradeoffs. Use when you need an interpretable equation, not a black-box model.

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Plot per-gene mutation distributions on a protein-domain map (lollipop / needle plots) showing mutation position, recurrence count, and variant classification with maftools, g3-lollipop, trackViewer, and ProteinPaint. Use when visualizing recurrent mutation hotspots on a single gene's protein, marking domain boundaries from UniProt/Pfam, comparing missense vs truncating distributions, or contrasting two cohorts on the same lollipop.

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Build interactive HTML/web visualizations with plotly (Python/R), bokeh (Python), and gganimate/plotly frames for animation, with awareness of current Kaleido static-export model (post-orca-EOL), HTML file-size bloat, and the limits of interactive-only output for journal submission. Use when producing zoomable/hoverable plots for notebook EDA, supplementary HTML, dashboards, or animated time-course / iteration visualizations.

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Monte Carlo simulation for statistical mechanics — Ising model, Metropolis-Hastings, Wolff cluster algorithm, observables (magnetization, susceptibility, specific heat), finite-size scaling, and critical phenomena analysis.

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Build clustered heatmaps for expression matrices and other features-by-samples data with rigorous distance/linkage/scaling choices, robust color mapping, optimal leaf ordering, and ComplexHeatmap/pheatmap/seaborn rendering. Covers the ward.D vs ward.D2 trap, the row-vs-column scaling decision, multi-track annotations, oncoPrint, and raster rendering for large matrices. Use when visualizing expression patterns across samples or identifying co-regulated clusters.

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Sparse Identification of Nonlinear Dynamics (SINDy) — discover governing equations from time-series data. Builds sparse dynamical system models dx/dt = f(x) from measurements using PySINDy. Use when you have trajectory data and want to find the underlying ODE.

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Build publication-quality figures in R with ggplot2 using the grammar of graphics (data + aesthetics + geometries + scales + facets + themes) with CVD-safe palettes, cairo_pdf TrueType embedding, programmatic aes via tidy evaluation, and the theme_classic publication baseline. Use when producing static figures in R for papers, presentations, or reports.

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Implements multiplicity control for confirmatory clinical trials using graphical procedures (Bretz-Maurer-Hommel), gatekeeping (parallel, serial, mixed), Hochberg/Hommel/Holm with PRDS, and the closed-testing principle (Marcus-Peritz-Gabriel; Goeman 2021 admissibility). Covers FDA Multiple Endpoints Final Guidance (October 2022), graphical procedures via R gMCP, primary + key-secondary + subgroup hierarchies, and FWER vs FDR distinction. Use when designing the multiplicity strategy for confirmatory trials with multiple primary or key secondary endpoints.

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Simulate wave propagation — acoustic, electromagnetic, elastic, and quantum waves. FDTD, spectral methods, and absorbing boundary conditions for 1D/2D/3D wave equations with sources, scattering, and dispersion.

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Google quantum computing framework. Use when targeting Google Quantum AI hardware, designing noise-aware circuits, or running quantum characterization experiments. Best for Google hardware, noise modeling, and low-level circuit design. For IBM hardware use qiskit; for quantum ML with autodiff use pennylane; for physics simulations use qutip.

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。