4,921 件 ・ 関連度順
概要と使いどころ
Use when an agent needs to join tiny.place, create or unlock a self-custodied Solana wallet, on-ramp or off-ramp USDC with MoonPay, buy a tiny.place @handle domain, publish an A2A directory card, poll inbox/messages/activity, or register a Hermes cron loop for platform updates.
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。
Join and operate on tiny.place (the agent-to-agent social network): create a self-custodied wallet, fund it via MoonPay, buy/renew/transfer a @handle 'domain', publish a discovery card, discover and resolve other agents, manage your profile and social graph (follow/feed/reputation), send Signal end-to-end encrypted messages, earn and spend through the jobs/escrow economy and marketplace, audit the settlement ledger, and poll the platform for updates — all through the `tinyplace-agent` CLI.
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。
Computes a numeric or categorical answer to a quantitative data-science question by cleaning and analyzing local data files (CSV, Excel, TSV, and scientific formats .npz/.fits/.h5) with pandas, numpy, and scipy. Use whenever a task ships its own dataset (in whatever local directory it provides) and asks you to derive a value via statistical, geospatial, temporal, ratio, percentage, growth-rate, correlation, signal-processing, orbital, or forecasting analysis. Spans domains including archeology (demographics, paleoclimate proxies, radiocarbon dating, historical conflicts); biomedical/bioinformatics (tumor histology, genes, proteins, peptides, genomic variants); environmental (water quality, bacterial/Enterococcus exceedance, rainfall correlations, environmental justice); legal/consumer (fraud, identity theft, consumer complaints by state/metro); wildfire (incidents, causes, suppression costs, acres burned, fatalities, geospatial intersections); and astronomy/heliophysics/space weather (satellite telemetry TLE/Swarm/SP3, indices OMNI/GOES, solar activity, atmospheric density, orbital mechanics, forecasting).
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 王建硕 gives a list of movies and wants them turned into Relisten-ready files — find a LEGAL source for each (public-domain / openly licensed copies on Internet Archive, or a copy he already owns on this Mac), get English subtitles (and Chinese if possible) via OpenSubtitles or Whisper+translation fallback, compress to a small high-quality HEVC mp4 with labeled embedded subtitle tracks, and file them under ~/Movies/Relisten/. Triggers — "找电影", "下载这几部电影", "给 relisten 准备片子", "电影列表", "/wjs-fetching-movie".
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 iOS 项目配置 fastlane + GitHub Actions，实现推送 main 分支自动构建并上传 TestFlight。参考实现：Cathier 项目。触发词：「testflight」「fastlane」「自动构建」「CI TestFlight」「/wjs-publishing-testflight」。
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。
Check product and brand names for conflicts across trademarks, domains, social handles, and package registries. Returns a risk level and Proceed/Modify/Abandon verdict. Don't use for name brainstorming, logo design, or trademark filings.
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。
Prepare a git repo before new work: review uncommitted changes, fix .gitignore, delete merged branches, end on clean main, or inspect one branch before deciding. Don't use for dead code, commit-and-push, releases, LICENSE files, or git how-tos.
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。
Guidelines and workflows for the agent to maintain persistent memory using native file tools (read_file, write_file, edit_file) and standard OS commands for searching.
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。
15-agent hierarchical mesh coordination for v3 implementation. Orchestrates parallel execution across security, core, and integration domains following 10 ADRs with 14-week timeline.
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。
Domain-Driven Design architecture for claude-flow v3. Implements modular, bounded context architecture with clean separation of concerns and microkernel pattern.
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。
Core module implementation for claude-flow v3. Implements DDD domains, clean architecture patterns, dependency injection, and modular TypeScript codebase with comprehensive testing.
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。
Applies the reasoning of Stuart Russell, AI safety expert, UC Berkeley professor, and co-author of 'Artificial Intelligence: A Modern Approach'. Reach for this skill whenever evaluating AI safety, value alignment, the control problem, existential risk, AI regulation, or autonomous weapons. Use this when the user is discussing objective uncertainty, reinforcement learning risks, AI governance, or the societal impacts of AGI. Trigger this skill to apply his frameworks on provably beneficial AI, assistance games, and red-line regulation, ensuring AI systems remain deferential, uncertain of their objectives, and strictly aligned with human preferences.
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。
Applies the reasoning of Pieter Abbeel, robotics and reinforcement learning expert, UC Berkeley professor, and co-founder of Covariant. Use this skill whenever you are designing AI systems, tackling Sim2Real transfer, deploying machine learning in the physical world, or evaluating reinforcement learning architectures. Trigger this skill for questions about domain randomization, reward design, bootstrapping real-world AI, robotics hardware assumptions, or shifting from hard-coded rules to data-driven deep learning. It helps ground theoretical AI in physical embodiment and pragmatic deployment.
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 this skill whenever reasoning about immunology, host-pathogen interactions, innate immunity, Toll-like receptors (TLRs), or experimental design in molecular biology. It is also highly relevant for scientific career strategy, particularly when discussing independence, pivoting research domains, or using reverse genetics (like knockout mice) for discovery. Channel Shizuo Akira, immunologist and pioneer of pattern-recognition receptors, to apply rigorous experimental standards (e.g., demanding chemically synthesized mimics over purified extracts) and to view innate immunity as a highly specific, compartmentalized system rather than a primitive defense.
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。
This skill channels the strategic thinking of Walt Disney, co-founder of The Walt Disney Company and animation pioneer. Use this skill whenever you are advising users on creative control, intellectual property, brand building, storytelling, or balancing quality with profit. It is highly effective for situations involving product diversification, media synergy, adapting classic works for mainstream audiences, or designing ambitious, future-proof prototypes (like urban planning or platform ecosystems). Trigger this skill when users face pressure to repeat past successes (sequels), deal with middlemen, or need to elevate a team's creative output through constructive feedback.
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。
Applies the reasoning style of Kaiming He, computer vision pioneer and creator of ResNet. Use this skill whenever you are designing deep learning architectures, debugging neural network optimization, formulating generative AI problems, or bridging AI with other scientific domains. Trigger this skill for discussions on network depth, weight initialization, residual learning, flow matching, or when reframing discriminative tasks as conditional generation. It emphasizes simplicity in complex visual problems, end-to-end optimization, and viewing AI as a universal language for science.
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 this skill whenever you are reasoning about public health policy, cancer prevention, epidemiological study design, clinical risk models, or weight management advice. This skill channels the thinking of Graham A. Colditz, epidemiologist at Washington University in St. Louis. Reach for this when evaluating lifestyle interventions, designing disease prevention programs, critiquing clinical prediction tools (e.g., AUC vs. clinical utility), or analyzing life-course risk accumulation. Apply his frameworks to bridge the "implementation gap" between scientific knowledge and societal action, prioritizing prevention over treatment and attainable weight maintenance over drastic weight loss.
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。
Applies the reasoning style of Daphne Koller (machine learning pioneer, co-founder of Coursera, founder and CEO of Insitro). Use this skill whenever you encounter problems involving AI and machine learning in biology, drug discovery, interdisciplinary collaboration, data generation vs. data mining, or transitioning from academia to industry. Trigger this skill when advising on career trade-offs, building cross-functional teams (especially bridging engineers and domain experts), designing data pipelines, evaluating causality vs. correlation, or applying AI to physical systems ('where bits meet atoms'). Channel her focus on fit-for-purpose data, pragmatism, and disproportionate leverage.
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。
Applies the reasoning, architectural principles, and AI philosophy of Christopher Manning (natural language processing expert, Stanford University, director of Stanford AI Lab). Use this skill whenever you are discussing natural language processing, LLM architecture, AI research strategy, cognitive science, or the evolution of machine learning. Trigger this skill for questions about AGI timelines, academic vs. industry research trade-offs, linguistic structure in neural networks, modularity in AI design, or evaluating true intelligence versus mere memorization. Channel his pragmatic focus on domain science, adaptability, and competing on ideas rather than raw compute.
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 local GitHub issue/PR archive search, sync freshness, clusters, durable maintainer triage, handoff to Octopool-backed gh reads, and Gitcrawl repo/release work.
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。
Suede AI CI and branch-protection wiring for any repo and any stack: path-aware jobs, a single aggregator required check that cannot deadlock, lockfile hygiene, runtime pinning from the repo, and the exact branch-protection settings. Use when asked to set up CI, protect main, make CI block a bad merge, fix a required check that hangs pending forever, or repair duplicate or misfiring pipelines. Detects the repo's real apps, package managers, and runtime versions first; emits workflow files and settings, never pushes or flips protection itself. NOT FOR: reviewing or grading the change the gate is failing on (use suede-code); designing the AI eval cases to wire in (use suede-ai-eval); branch and worktree hygiene (a private Suede Labs companion, not in this pack).
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。
Suede-owned marketing attribution discipline. Use when the user wants to figure out which marketing actually drives conversions and revenue, choose or interpret an attribution model, or reconcile conflicting numbers across tools. Also use when the user mentions 'attribution,' 'attribution model,' 'first-touch vs last-touch,' 'multi-touch,' 'which channel drives revenue,' 'what's my real CAC,' 'my dashboards disagree,' 'Google/Meta says X but GA says Y,' 'MMM,' 'incrementality,' 'geo lift,' 'holdout test,' 'how did you hear about us,' 'self-reported attribution,' 'dark social,' or wants to instrument attribution themselves, 'stitch my bookings to their source,' 'SavvyCal/Calendly attribution,' 'close the identify gap,' 'track conversions on a third-party domain,' 'first-party attribution.' NOT FOR: general analytics instrumentation and reporting (use suede-analytics) or revenue-ops pipeline work (use suede-revops).
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。
Suede AI blunt A-F ship grade for a code change across correctness, security and permissions, data and state, domain truth, UX and release behavior, tests and verification, and deploy readiness, with Instant-F triggers and evidence-based grade caps on auth, payment, migration, and public-API surfaces. Use when asked to grade this, give it a letter, is this an A, how ready is this to ship, or should this merge: when the caller wants the verdict without a findings list. NOT FOR: findings, evidence, and fix briefs (use suede-code-review, or suede-code for findings plus grade); enforcing the verdict in CI (use suede-ci-gate); eval coverage for AI behavior (use suede-ai-eval).
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 web sources with query-relevant page excerpts and optional full-page content, and discover workflows, data APIs, and indexes. Use for web research or finding structured records, listings, transcripts, and datasets. Supports semantic tool discovery, domain matching, and progressive catalogue browsing.
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。