1,277 件 ・ 関連度順
概要と使いどころ
Generate a daily digest of today's policy-authorized meetings and voice memos — key decisions, action items, and themes across available recordings. Use when the user asks "recap my day", "what happened in my meetings today", "daily summary", "what did I discuss today", "any action items from today", or wants a consolidated view of the day's conversations.
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 weekly marketing campaign performance data across channels. Use when analyzing multi-channel digital marketing data to calculate funnel metrics (CTR, CVR) and compare to benchmarks, compute cost and revenue efficiency metrics (ROAS, CPA, Net Profit), or get budget reallocation recommendations based on performance rules.
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。
Two pipelines ending at a scanner-look PDF. (1) Phone photos of paper documents (contracts, stamped certificates, receipts, forms, handwritten notes) → clean scanner-quality PDF: perspective rectification + noteshrink whitening + A4 assembly + mandatory whole-document check. Trigger: "把照片 做成扫描件", "photos to scanned PDF", "make this look scanned", "手机拍的 文档转 PDF", "盖章文件扫描", replacing pages in an existing scanned PDF, any CamScanner-like request. (2) A digital document with no signature yet (rendered docx/PDF, confirmation form, contract draft) → make it look hand-signed and scanned: synthesize a handwriting-style signature, composite it onto the signature line, apply the same scan-look post-processing. Trigger: "帮我做个手写签名", "生成签名盖到这份文件上", "做成签过字的扫描件", "synthesize a signature", any request for a document that needs to look signed without a real photographed signature. Do NOT hand-roll levels/contrast enhancement for scan-look — tried and rejected twice; this skill's pipeline is the proven 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。
Extract pixel-level data from an image of a chart or graph and produce a structured data table. Use when asked to extract data from a chart image, transcribe numbers from a graph, digitise a chart, or turn a screenshot of data into a table. Produces a structured table with extracted values, confidence levels, and a reconstructed chart source. Best used with Claude Opus 4.7 or newer for reliable chart data extraction.
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。
Get your attention back with a 30-day protocol that assumes you'll break it — a screen-time ledger without moralizing, friction engineering (what to delete, grayscale, where the phone sleeps), planned relapses, and honest replacement activities for the boredom that shows up on day 3. Use when someone says 'my screen time is 7 hours', 'I want a dumbphone', 'digital detox', 'I can't read books anymore', or 'my attention span is gone'. Produces the ledger, a personal friction plan, and the 30-day protocol with expected failure points.
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。
Compile the team's REAL updates into one async standup — pull what people posted in Slack (and moved in Notion/Linear), not a template for running standups. Use when asked to compile today's standup, pull the team's updates into one post, what did the team ship, or run async standup in Cowork. Reads a Slack channel and (optionally) the tracker via connectors, groups updates by person into shipped / in-progress / blocked, surfaces the blockers needing attention, and produces a standup-digest artifact ready to post back.
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。
Assess whether and how someone can safely stay in their own home as they age — the home hazards, the support gaps, and the modifications and services that make it work. Use when asked can my parent stay in their home safely, aging in place assessment, is it safe for them to live alone, or what do we need for them to stay home. Produces a room-by-room safety read (fall hazards, accessibility), an honest look at the daily-living and support gaps, the modifications and services that could close them, warning signs that home may no longer be safe, and how to raise it respectfully — helping a family make a clear-eyed, dignity-preserving decision. Not medical advice.
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 the conversations with aging parents that everyone postpones — the driving talk, the money talk, the care-options talk, the moving talk — each with an opener that doesn't ambush, a dignity-first script, rehearsal against realistic resistance, and the fallback when it goes badly. Use when someone says 'I need to talk to my dad about driving', 'my mum won't discuss her finances', 'we need to talk about care', or is dreading a visit for exactly this reason. Produces the conversation plan, a rehearsal, and the small-steps fallback. A preparation tool, not family therapy — and it says so when the situation needs more.
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 weekly marketing campaign performance data across channels. Use when analyzing multi-channel digital marketing data to calculate funnel metrics (CTR, CVR) and compare to benchmarks, compute cost and revenue efficiency metrics (ROAS, CPA, Net Profit), or get budget reallocation recommendations based on performance rules.
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。
Help users build a professional eye for quality, articulate the reasoning behind successful product paradigms, and develop the conviction to make high-stakes decisions before data is available.
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。
Help users design and execute a high-signal interview process that prioritizes real-world performance over superficial charisma or pedigree.
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 and remove AI slop — the generic, machine-default visual and copy tics of vibe-coded products — from a web project. Use when the user asks to "kill AI slop", "de-slop", "remove the AI look", "make this not look AI-generated", or clean up a landing page / UI / docs that feels templated. Detects and fixes the catalogue of tells: indigo→violet gradients, gradient-clip headlines, the default semantic palette, one-hue status boxes, atmospheric gradients, serif-italic emphasis, highlighted keywords, AI copywriting voice ("not just X — it's Y"), emoji everywhere, glowing status dots, wobbling spinners, colored-left-border callouts, pastel icon tiles, glassmorphism, over-rounding, oversized shadows, borders that die at corners, badge & pill spam, AI-drawn SVG icons, kickers over every heading, flat type hierarchies, invented stat rows, 01/02/03 section markers, cards nested in cards, the default Inter/Space Grotesk look, and more. Works on HTML/CSS, React/Vue/Svelte/Astro, Tailwind, PHP, and Markdown copy.
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。
Puts a built website live on a free HTTPS link, or your own .com with no DNS. Use when the user says "put it online", "go live", "make it live", "put this live", "publish my site", "share it with friends", "send my friends a link", "get a link", "make it public", "it only works on localhost" or "get a .com", or asks to deploy or host a site built with an AI tool (Claude Code, Cursor, Codex, Windsurf, Lovable, Bolt, v0, ChatGPT), or mentions DropTheHassle, and has not picked another host. Covers building first, CLI or MCP setup, deploying, the claim link, the live check, linking a server part the user hosts on AWS, Google Cloud, DigitalOcean or their own server with set_backend, and domain search. The agent never spends money. The human pays.
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 preparing an accepted ACM CCS paper for the ACM Digital Library proceedings, covering de-anonymization, the ACM sigconf final format, ACM rights and eRights forms, badge placement from artifact evaluation, incorporation of shepherd and minor-revision requirements, disclosure-timing coordination, registration, and in-person presentation.
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。
Subscribe to and scan industry newsletters for buying signals, competitor mentions, ICP pain-point language, and market shifts. Parses incoming newsletter emails via AgentMail, matches against keyword campaigns, and delivers a weekly digest of actionable signals. Use when a marketing team wants to turn newsletter subscriptions into an ongoing intelligence feed without manual reading.
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。
Monitor competitor content across blogs, LinkedIn, and Twitter/X on a recurring basis. Surfaces new posts, trending topics, and content gaps you can own. Chains blog-feed-monitor, linkedin-profile-post-scraper, and twitter-mention-tracker. Use when you want a weekly digest of what competitors are publishing and which topics are generating engagement.
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。
审查、安装、配置、验证、更新和移除 AgentDock Skill 时使用；负责来源校验、安全评估、环境配置、content digest、精确 skill_ref 与当前 managed 内容验收。
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。
Local vision CLIs: glance (describe/ask/OCR an image), ground (locate a target, pixel box), detect (element inventory), trace (image to SVG geometry), crop (cut a pixel box to a file), and scripts/html_shot.py (HTML file to image). Use for any task involving an image — questions, text, splitting and transcribing long screenshots or chat histories, locating elements, comparing, rebuilding as HTML/SVG, digitizing a sketch or diagram, reading values off a chart, operating a GUI from screenshots — and to re-check an image yourself when a description you were given lacks a detail.
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。
Identify tumor neoantigens from somatic variants with pVACtools (pVACseq/pVACfuse/pVACbind/pVACvector/pVACview) for personalized cancer vaccines and checkpoint biomarkers. Encodes the field's hard truth that binding prediction is the easy, near-solved part and single-digit-percent PPV lives downstream — so it centers clonality/CCF, HLA LOH (the silent invalidator), expression, proximal-variant phasing, agretopicity/foreignness quality, and the predicted->presented->immunogenic validation tiers. Use when nominating vaccine targets, ranking neoantigens, or building a tumor-to-candidate pipeline. Binding details in mhc-binding-prediction; ranking in immunogenicity-scoring.
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。
Nominates and assesses CRISPR off-target sites genome-wide. Enumerates candidate sites by mismatch and bulge tolerance with Cas-OFFinder/CRISPRitz, ranks them with the published CFD score (SpCas9-only, relative ranker) or MIT/CRISTA/energy models, runs variant-aware screening against gnomAD/individual genomes (CRISPRme), and frames the empirical genome-wide discovery assays (GUIDE-seq, CIRCLE-seq, CHANGE-seq, DISCOVER-seq, Digenome-seq) and high-fidelity nuclease choice (HiFi Cas9, Sniper-Cas9, eSpCas9, SpCas9-HF1). Use when assessing guide RNA specificity, choosing among candidate guides, screening a therapeutic guide against population variation, or planning empirical off-target validation. Distinguishes predicted vs detected vs validated. On-target activity scoring and deaminase (Cas-independent) base/prime-editor off-targets are separate 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。
Assigns GO terms, Pfam/InterPro domains, KEGG orthologs, EC numbers, and product names to predicted proteins using eggNOG-mapper (orthology), InterProScan (domain signatures), and KofamScan (KEGG), routing specialized functions to dbCAN/antiSMASH/AMRFinderPlus/SignalP. Covers the orthology-vs-domain-vs-homology paradigms, the annotation-error percolation cascade, domain-presence-is-not-function, GO IEA circularity in enrichment, evidence tiering, and bit-score/coverage thresholds. Use when adding functional annotation to predicted genes, choosing between eggNOG-mapper and InterProScan, or judging how much to trust a functional label.
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。
Detects and removes contamination in genome assemblies via two disjoint workflows - foreign-sequence screening of a single-organism (eukaryote/isolate) assembly with NCBI FCS-GX (GenBank-submission-mandatory), FCS-adaptor, and BlobToolKit blob plots; and MAG/bin quality assessment with CheckM2 plus GUNC (chimerism) plus GTDB-Tk taxonomy, judged against MIMAG. Covers why CheckM2 alone is blind to disjoint-marker chimeras, the FCS-GX RAM wall, organelle/NUMT triage, strain heterogeneity, and the HGT-vs-contamination (tardigrade) trap. Use when screening an assembly for foreign contamination before GenBank submission, assessing MAG completeness/contamination/chimerism, deciding which contigs to remove, or distinguishing real HGT from contaminant contigs.
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。
Infer gene regulatory networks from bulk or general expression data with mutual-information (ARACNe) and tree-ensemble (GENIE3, GRNBoost2) methods, and infer transcription-factor protein activity from regulons with VIPER and msVIPER. Covers the activity-not-edges paradigm, the undirected-association caveat, the DREAM5 wisdom-of-crowds and method-complementarity result, AUPRC-over-AUROC evaluation, and gold-standard incompleteness. Use when inferring a regulatory network from a bulk expression matrix, finding master regulators, or scoring TF activity from a signature. For single-cell motif-pruned regulons see scenic-regulons; for co-expression modules see coexpression-networks.
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。
Designs novel molecules using REINVENT 4 (de novo, scaffold decoration, linker design, R-group, molecular optimization), MolMIM, Diffusion-based generators (DiGress, DiffSMol), and JT-VAE with explicit handling of multi-parameter optimization (MPO), goal-directed scoring functions, transfer/reinforcement/curriculum learning, synthetic accessibility scoring, and chemical space exploration vs exploitation. Use when designing new chemical matter against a target, decorating a scaffold, linking fragments, or optimizing a hit for multiple ADMET / activity properties simultaneously.
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。