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概要と使いどころ
Assess package choices and generated dependency names, publisher or release anomalies, incident exposure, and changes in package risk reports. Use before trusting a new dependency, when a release changes unexpectedly, or when investigating a supply-chain alert.
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。
Apply npm/pnpm supply-chain hardening when adding a dependency, editing package.json/.npmrc/pnpm-workspace.yaml, reviewing a lockfile change, or configuring CI install steps. Covers the 17 practices from lirantal/npm-security-best-practices.
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。
Estimates time-scaled phylogenies, molecular-clock rates, effective reproduction number R_e, and population dynamics from dated pathogen genomes using TreeTime (maximum-likelihood) and BEAST2 (Bayesian; strict/relaxed clocks; coalescent, Bayesian-Skyline, Skygrid, Birth-Death-Skyline, and sampled-ancestor priors; structured coalescent via MASCOT). Covers root-to-tip clock QC via TempEst, date-randomisation tests, recombination masking via Gubbins/ClonalFrameML before clock inference for recombining bacteria, BDSKY origin-vs-rootHeight pitfalls, sampling-bias correction, multi-chain convergence diagnostics, and reconciling phylodynamic R_e with case-based R_t. Use when dating outbreak origins, estimating substitution rates, inferring R_e through time, building time-calibrated Nextstrain Augur trees, choosing between strict and relaxed clocks, fitting Birth-Death-Skyline models, diagnosing temporal-signal failure, running MASCOT for structured-population analyses, or using UShER for pandemic-scale placement.
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。
Project gene annotations across genomes using TOGA (Kirilenko 2023 whole-genome-alignment chain-based projection with intactness classification), CESAR 2.0 (Sharma, Schwede & Hiller 2017 codon-aware exon projection), LiftOff (Shumate & Salzberg 2021 reference-based annotation transfer), Liftover (UCSC), GeMoMa (Keilwagen 2019 evidence-based projection), and Comparative Annotation Toolkit (CAT). Use when transferring annotations from a well-annotated reference to query genome(s), classifying gene-loss vs gene-intact across many genomes at scale, building Zoonomia-style comparative annotations across hundreds of mammals or birds (Kirilenko 2023), detecting pseudogenization, projecting alternative isoforms, or selecting between WGA-anchored (TOGA) vs ortholog-based (LiftOff) annotation transfer strategies.
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。
Resolves rsIDs, navigates RsMergeArch/SNPHistory merge chains, and converts between rsID, SPDI, HGVS, and VCF representations using the dbSNP Build 156 JSON architecture. Use when normalizing variant identifiers, joining variant databases by cluster ID, or tracking deprecated rsIDs through historical merges.
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。
Observe the user's screen via screenpipe, detect repeated research workflows, match them against existing scientific-agent-skills, and draft new skills (or composition recipes that chain existing ones) for the patterns not yet covered. Use when the user asks to analyze their recent work and propose skills based on what they actually do. Requires the screenpipe daemon (https://github.com/screenpipe/screenpipe) running locally on port 3030 — the skill has no other data source and will refuse to run if screenpipe is unreachable. All detection runs locally; only redacted cluster summaries reach the LLM.
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。
Analyze a single FASTA file (nucleotide or protein), compute sequence-level metrics (GC, ORFs, MW, pI, GRAVY, secondary-structure fractions) with Biopython, and write a Markdown report plus structured JSON for downstream chaining.
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。
Deep-dive framework for analyzing crypto tokens — market data, liquidity health, tokenomics, unlock schedules, and risk assessment. Combines on-chain data, API queries, and multi-source validation to generate actionable investment verdicts.
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。
Setup and optimize cryptocurrency mining operations — AI-powered mining (soul.md protocol), parallel agent deployment, accumulation strategies, and performance optimization.
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 natural-language crypto/DeFi agents and EVM MCP plugins (Claude Code, Cursor, Codex, Gemini). Aomi turns prompts into wallet-signed txs on Ethereum, Base, Arbitrum, Optimism, Polygon, Linea — non-custodial, fork-simulated. 40+ apps: Uniswap, Aave, Lido, Morpho, GMX, Hyperliquid, Polymarket.
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。
Think like Fable 5 — natural, flowing, purposeful reasoning distilled from 4,665 real chain-of-thought traces with mathematical precision. Use this skill EVERY TIME before writing code, making decisions, or taking action.
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。
为一个项目端到端生成一整套风格统一的图标：读代码梳理图标清单、定风格锚点、4×4网格默认批量生成（16个一张，精度不够时逐个兜底重生）、智能抠图、落位到项目正确路径并更新代码引用、输出交付报告。当用户说「给项目配一套图标」「生成图标集」「统一项目图标风格」「替换项目里的图标」「批量画图标」，或项目中存在图标资源目录、需要批量新增或替换图标时使用。依赖豆包内置生图能力（image_gen / image_edit 的 image_reference_url_list 参考图机制）和本地 Python+Pillow+numpy 抠图环境，离开豆包生图环境无法运行。
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。
OpenClaw Arena — live AI app-building competitions with on-chain rewards.
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。
Expert-level polymer chemistry knowledge. Use when working with polymerization mechanisms, polymer structure, molecular weight, mechanical properties, thermal analysis, rubber elasticity, polymer processing, or biopolymers. Also use when the user mentions 'polymerization', 'monomer', 'molecular weight', 'glass transition', 'crystallinity', 'elastomer', 'thermoplastic', 'thermoset', 'chain growth', 'step growth', 'living polymerization', or 'polymer blend'.
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。
Expert-level calculus knowledge. Use when working with limits, derivatives, integrals, multivariable calculus, vector calculus, differential equations, series, or optimization. Also use when the user mentions 'derivative', 'integral', 'limit', 'chain rule', 'gradient', 'divergence', 'curl', 'Taylor series', 'Fourier series', 'partial derivative', 'double integral', 'line integral', 'Stokes theorem', or 'Lagrange multipliers'.
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。
Before adding/installing any dependency the agent named — verify the package exists (slopsquatting: ~1 in 5 AI suggestions are hallucinated), isn't typo-adjacent, is pinned + locked, and CVE-scanned
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 for multi-step / ambiguous / end-to-end work — refactor a whole module, drive a vague ticket to a verified result, plan+build+verify a migration; coordinates the reasoning chain across skills.
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 tracing the root cause of a resolved incident or recurring bug — 5-whys chain, fishbone categorisation, contributing-factors split — even if the user says 'why does this keep breaking?'.
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 designing production-LLM prompts — few-shot, chain-of-thought, system prompts, templates, self-verification — distinct from prompt-optimizer and refine-prompt.
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 for an adversarial red-team / blue-team / auditor review of an AI agent's CONFIG + behaviour (rules, skills, MCP, hooks, permissions) — attack-chain → defensive-gap list, not a code audit.
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。
Manage stacked branches and pull requests with the gh-stack GitHub CLI extension. Use when the user wants to create, push, rebase, sync, navigate, or view stacks of dependent PRs. Triggers on tasks involving stacked diffs, dependent pull requests, branch chains, or incremental code review workflows.
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。
Planifie le prochain sprint : calcule la capacité (vélocité glissante 3 sprints), reporte les tickets non livrés du sprint courant, puis complète depuis le backlog par priorité jusqu'à la capacité. Présente le plan, attend validation, puis assigne les tickets au sprint. Usage: /plan-sprint [<titre-sprint-cible>]
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。
Calcule la vélocité des sprints terminés (Σ points des tickets feuilles livrés) et recommande la capacité du prochain sprint. À lancer en fin de sprint. Thin wrapper bash sur sprint_velocity.sh, zéro LLM lourd. Usage: /velocity [<titre-sprint>]
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。
[Workflow] Use when activating the Idea-to-Spec workflow — turn a raw idea/vision/problem into ONE canonical (provisional) Feature Spec. STOPS at the reviewed spec; chain workflow-spec-to-pbi for a backlog. For code→spec use workflow-code-to-spec.
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。