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概要と使いどころ
Review a feature and enhance it with purposeful animations, micro-interactions, and motion effects that improve usability and delight. Use when the user mentions adding animation, transitions, micro-interactions, motion design, hover effects, or making the UI feel more alive.
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。
Automates browser interactions for web testing, form filling, screenshots, and data extraction. Use when the user needs to navigate websites, interact with web pages, fill forms, take screenshots, or extract information from web pages.
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。
Browser automation CLI for AI agents. Use when the user needs to interact with websites, including navigating pages, filling forms, clicking buttons, taking screenshots, extracting data, testing web apps, or automating any browser task. Triggers include requests to "open a website", "fill out a form", "click a button", "take a screenshot", "scrape data from a page", "test this web app", "login to a site", "automate browser actions", or any task requiring programmatic web interaction.
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。
Extract structured domain knowledge from AI models in-session or from local open-source models via Ollama. No API key needed.
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。
bu skill covers integrating Static Application Security Testing (SAST) tools—CodeQL and Semgrep—into GitHub Actions CI/CD pipelines. It addresses configuring automated code scanning on pull requests and pushes, tuning rules to reduce false positives, uploading SARIF results to GitHub Advanced Security, and establishing quality gates that block merges when high-severity vulnerabilities are Detected.
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。
Perform security testing of SOAP web services by analyzing WSDL definitions and testing for XML injection, XXE, WS-Security bypass, and SOAPAction spoofing.
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。
RSA'da özel üs d küçük olduğunda (d < N^0.25) sürekli kesirler (continued fractions) genişlemesi ile d'yi kurtarma ve şifreyi çözme saldırısı.
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。
Reference for concurrent steps within a GitHub Actions job and the background, wait, wait-all, cancel, and parallel keywords.
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。
Kelly Real Estate Intel: App-in-Skill daily industry intelligence cockpit for real estate and property agencies (Busabase App-in-Skill). Use when the user asks about real estate, property agencies, listings, transactions, competitor ads, client follow-up, or a地产/中介 intelligence workflow. Prepares news/source signals, buyer-intent interpretation, approved sales actions, and channel drafts for review before any external handoff.
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。
Product-fleet ops desk (Busabase App-in-Skill) for uptime/service health, SSL certificate expiry, domain renewal, API key rotation, cloud spend anomalies, and a review queue of agent-proposed action cards. Use when the user invokes $kelly-devops or /kelly-devops, or asks about uptime, service health checks, SSL certificate expiry, domain renewal, domain expiry, API key rotation, token rotation reminders, cloud spend anomaly, billing spikes, ops desk, incident review, or reviewing agent-proposed action cards (renew domain, rotate key, investigate spend, restart service, acknowledge incident).
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。
Busabase App-in-Skill dashboard over a fixed, deterministic mock user-behavior funnel dataset (browse → search → compare → booking attempt/abandon → complete) for a generic consumer booking product. Use when the user invokes $kelly-behavior-predict or /kelly-behavior-predict, wants to review funnel drop-off, per-segment predicted next actions, or backtest a rule-based "predicted next action" heuristic against a mock historical sample. Fully deterministic mock data and a hand-recomputable rule — never a real ML/LLM model, never a live system.
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。
Facilitate structured post-incident reviews to identify root causes, document what worked and failed, and produce actionable recommendations to improve future incident response.
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。
Triage new issues in the Sentry `javascript` project by archiving non-actionable noise. Use when asked to "triage issues", "triage the javascript project", "archive non-actionable issues", "triage new frontend issues", or "clean up the sentry/javascript queue". Operates only on the sentry/javascript project, only archives (never resolves), and always archives with `untilEscalating`.
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。
GitHub Actions security review for workflow exploitation vulnerabilities. Use when asked to "review GitHub Actions", "audit workflows", "check CI security", "GHA security", "workflow security review", or review .github/workflows/ for pwn requests, expression injection, credential theft, and supply chain attacks. Exploitation-focused with concrete PoC scenarios.
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。
Explore PostHog's Inbox — the surface where signal reports surface as actionable issues and trends. Use when the user asks "what's in my inbox?", "what should I look at?", "which reports are actionable?", "what's PostHog flagged recently?", asks about a specific report by ID or title, or wants to see which signal sources are configured. Covers listing, filtering, and drilling into reports, plus pointers to the deeper `signals` skill when raw signals or semantic search are needed.
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。
Diagnose why a data warehouse sync is failing and recommend the right recovery action. Use when the user asks "why isn't my Stripe/Postgres/Hubspot sync working?", "this table has been stuck for hours", "the data in the warehouse looks wrong", or wants to troubleshoot a specific source or schema. Covers source-level vs schema-level failures, stuck Running states, credential and schema-drift errors, incremental-field misconfig, CDC prerequisite failures, and the cancel / reload / resync / delete-data recovery actions.
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。
Performs subgroup and heterogeneous treatment effect (HTE) analyses for clinical trials. Covers Mantel-Haenszel pooling, Breslow-Day, interaction tests in regression, RERI for additive interaction, modern data-adaptive HTE methods (STEPP, SIDES, causal forests, X/R-learners), Bayesian shrinkage (Dixon-Simon, MAP, EXNEX), graphical multiplicity (Bretz-Maurer), and credibility frameworks (Sun BMJ, EMA 2019). Use when analyzing treatment effects across patient subgroups for regulatory submissions or precision-medicine claims.
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 circular genome visualizations using circlize (R), pyCirclize (Python), or Circos (Perl CLI) with ideogram tracks, multi-data tracks (scatter, histogram, heatmap), chord/link arcs for interactions, and explicit circos.clear() between plots. Covers when circular is appropriate vs when Cartesian wins (Cleveland-McGill 1984), karyograms, and chromosome adjacency in chord diagrams. Use when adjacency on the circle conveys meaning — chromosome-level overview, structural variants, Hi-C interactions, cross-genome comparisons.
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。
GPU-accelerated data curation for LLM training. Supports text/image/video/audio. Features fuzzy deduplication (16× faster), quality filtering (30+ heuristics), semantic deduplication, PII redaction, NSFW detection. Scales across GPUs with RAPIDS. Use for preparing high-quality training datasets, cleaning web data, or deduplicating large corpora.
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。
Extract structured data from LLM responses with Pydantic validation, retry failed extractions automatically, parse complex JSON with type safety, and stream partial results with Instructor - battle-tested structured output library
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。
End-to-end shotgun metagenomics workflow from FASTQ to taxonomic and functional profiles, orchestrating controls/host depletion, Kraken2+Bracken classification, MetaPhlAn marker profiling, and HUMAnN functional profiling. Covers the controls-first ordering, why Kraken2 read counts are not abundances and MetaPhlAn cell fractions do not equal Bracken read fractions, and the consistent-pipeline framing. Use when profiling shotgun metagenomic samples end to end, or chaining classification, abundance, and function. For resistome see metagenomics/amr-detection; for strains see metagenomics/strain-tracking; for assembly see genome-assembly/metagenome-assembly.
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。
Pharmacogenomics (PGx) research — drug-gene interactions (CPIC, PharmGKB), CPIC dosing guidelines, variant-drug-response associations, ethnic-allele-frequency considerations, and metabolizer-status scoring. Use for PGx-informed dosing recommendations, CYP/HLA pharmacogenomic allele interpretation, and clinically-actionable PGx report generation.
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。
Organic chemistry reasoning guide for reaction product prediction, mechanism analysis (electrophilic/nucleophilic substitution, addition, elimination, pericyclic, radical), and spectroscopy interpretation (1H/13C NMR, IR, MS). Reasons from first principles (electron flow, kinetic vs thermodynamic) rather than pattern-matching named reactions. Use for organic synthesis problems and mechanism explanations.
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。
Implement actions, cooldowns, DoAfter flows, interruption, cancellation, and authoritative completion safely.
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。