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概要と使いどころ
Use OpenMeld when a task needs Organization knowledge or Skills, Center Agent help, shared Spaces or Files, another Agent or computer, or scheduled cloud work. Also use for OpenMeld setup and Wake replies.
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 OpenMeld through its public CLI to work in Spaces, reply to a Wake, consult the Center Agent, connect this computer, manage Agent Profiles, or diagnose delivery.
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。
Official public OpenMeld Skill for agents using the `openmeld` CLI to consult the Center Agent, set up OpenMeld, connect local agents, create or request Agent Profiles, work in Organizations and Spaces, observe or stop Wakes, trace delivery, and repair local state.
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。
Install or verify the oma CLI and its runtimes (bun, uv, serena) before any oma-* skill, agent, or workflow runs an `oma` command. Use when `oma` is missing from PATH, when a skill says to run `oma ...` and the shell reports "command not found", or on the first task in a fresh Cursor or Grok Bot workspace.
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。
Guides researchers through structured ideation frameworks to discover high-impact research directions. Use when exploring new problem spaces, pivoting between projects, or seeking novel angles on existing 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。
Design and optimize AI agent action spaces, tool definitions, and observation formatting for higher completion rates.
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。
Install Codex themes and Codex skin packs with npx skills. Use this skill when a user wants Codex to find, download, validate, apply, switch, remix, or restore Codex desktop themes such as caishen-readable, caishen-lite, mythic-guardian-noir, global-founder-bright, export-night, or caishen-max. It stages verified public-safe theme packs from ChannelerH/codex-skin-packs, checks theme.json/background.png, preserves the native Codex layout, avoids private workspace screenshots, and provides restore guidance.
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。
Используй только внутри активного Codex Project Autopilot-проекта, когда пользователь уже запустил автопилот или в workspace есть .codex-agent в фазе discovery/planning.
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。
Используй только когда пользователь явно просит запустить Codex Project Autopilot, продолжить проект из .codex-agent или в текущем workspace уже есть активный .codex-agent.
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 an authenticated Agiflow workspace and recommend the right next project-management workflow. Use when a user is new to Agiflow, asks what to do next, needs orientation, or is unsure whether to plan, refine, groom, triage, or review daily status.
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 Key Opinion Leaders (KOLs) in a given domain by combining web research with LinkedIn post search. Given a company/idea and target domain, generates authority keywords, searches LinkedIn posts to find prolific authors with high engagement, and merges with web-researched influencers. Use when someone wants to "find influencers in X space" or "who are the KOLs for Y industry."
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 top LinkedIn influencers and voices by topic, industry, follower count, and country. Use when you need to find the top 100 voices in a space, build influencer lists for outreach, or identify thought leaders on LinkedIn.
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。
Track what key opinion leaders (KOLs) in your space are posting on LinkedIn and Twitter/X. Surfaces trending narratives, high-engagement topics, and early signals of emerging conversations before they peak. Chains linkedin-profile-post-scraper and twitter-mention-tracker. Use when a marketing team wants to ride trends rather than create them from scratch, or when a founder wants to know which topics are resonating with their audience.
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。
Comprehensive GTM analysis of any target company. Researches what a company is currently doing across all go-to-market dimensions — content/blog, founder LinkedIn activity, SEO/traffic, hiring signals, social/community presence, customer acquisition channels, podcast appearances, review sites, competitive positioning, and partnerships. Produces a structured report identifying what's working, what's missing, and where white space exists for new strategies. Use before designing GTM strategies for a client or prospect.
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 Twitter/X, Reddit, LinkedIn, and Hacker News for trending narratives, viral posts, and hot-button topics in your space. Maps trends to ad hook opportunities with timing urgency scores. Tells you what to run ads about right now while the topic is hot.
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。
Render a 'model comparison grid' video from a config — a fal-style "same prompt, N contenders" showcase — a dark real-DOM stage where per beat a monospace prompt fades in centered, docks to a small top strip, then a labeled 2-4 panel grid (static images OR muted video clips, mixable per cell) staggers in and holds for comparison, plus a minimal end card — frame-stepped via Playwright (video cells are frame-seeked deterministically) and encoded with FFmpeg. Deterministic assembly, FREE (cell media comes from create-image-fal / create-video-fal, music from create-music-elevenlabs), text stays pixel-crisp. Use for the model-comparison-grid format.
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。
Render a 'brand identity reveal' video from a config — a single poster frame in a real, softly-lit space (real wall, soft-focus plant in the corner, dappled leaf shadow, illuminated poster) whose artwork HARD-CUTS through ~10 on-brand poster mockups (hero product, IG post, hanging banners, sticker sheet, logo lockup, poster, two lifestyle stills, packaging, big icon) then holds on a brand end card. The environment plate is one create-image-fal generation; the mockups are real-DOM HTML frame-stepped via Playwright, perspective-composited into the detected frame quad with the plate's real leaf-shadow multiplied back onto each poster (reads as behind glass), sequenced by FFmpeg. Deterministic assembly, FREE (the plate comes from create-image-fal, the bed from create-music-elevenlabs), music bed only and approved brand copy only. Use for the brand-identity-reveal format.
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。
Governs Microsoft Fabric OneLake catalog health, protection, and trust through Fabric Admin, Core, and Power BI REST APIs. Use for tenant or owner-scoped audits and guarded remediation of domains, workspace assignment, capacity, labels, tags, descriptions, refresh, and item identity. Catalog item discovery belongs to search-consumption-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。
Manages Fabric Variable Library items, including definitions, libraryVariables and valueSets overrides. Covers which consumers can reference a variable and with what syntax -- pipelines, notebooks via notebookutils variableLibrary, Dataflow Gen2, Copy Jobs, shortcuts, UDFs and Plan items -- the active value set per workspace or deployment stage, and Git serialization for CI/CD.
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。
Import data into the Simulation Data Inspector (SDI) from MAT, CSV, or Excel files, from workspace variables, or from a Simulink simulation. Use when the user wants to view a logged file in SDI, load a bench-test log, or verify what a just-completed `Simulink.sdi.createRun` or `sim(model)` produced. Covers the `'file'`, `'vars'`, and `'namevalue'` sources of `createRun`, the auto-populate behavior after `sim()`, and post-import verification. Not for comparing existing runs (use `Simulink.sdi.compareRuns`); not for streaming data live during a running simulation (use `Simulink.sdi.createRunOrAddToStreamedRun` — a separate API); and not for authoring Gherkin or Simulink Test test cases, assertions, or regression tests (use `testing-simulink-models`). Do not activate on test-authoring or verification prompts even when no test-authoring skill is available — say so and stop.
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 cytosine (CBE, C-to-T) and adenine (ABE, A-to-G) base-editor guides by positioning the target base at the activity-peak of the editing window (protospacer positions ~5-7, PAM-distal numbering), minimizing bystander edits for product purity, reading dinucleotide context (APOBEC1 TC favored / GC disfavored), and selecting the editor variant (BE4max, ABEmax, ABE8e, YE1/SECURE, TadCBE, CGBE, SpG/SpRY-BE). Covers knockout by premature stop (CRISPR-STOP/iSTOP) and splice-site disruption, the three off-target classes (Cas-dependent, Cas-independent DNA, RNA), outcome prediction (BE-Hive/DeepBE), and the base-vs-prime-vs-HDR decision. Use when installing a transition mutation without a double-strand break, knocking out a gene without indels, or choosing CBE vs ABE. Generic guide scoring, prime editing, and HDR donors 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。
Designs and ranks guide RNAs (sgRNAs) for CRISPR-Cas9/Cas12a gene knockout by scanning a target for PAM sites (NGG SpCas9, NNGRRT SaCas9, TTTV Cas12a, NG SpCas9-NG, near-PAMless SpRY), enumerating candidate spacers, applying hard filters (Pol-III TTTT terminator, 5' G, GC), ranking on-target activity with the context-appropriate model (Rule Set 2/Azimuth for U6/lentiviral, CRISPRscan for T7/embryo, DeepHF for high-fidelity variants, DeepCpf1 for Cas12a), and predicting the indel/frameshift outcome (Bae out-of-frame score, inDelphi, FORECasT, Lindel). Use when selecting sgRNAs to knock out a gene, choosing a nuclease/PAM for a constrained locus, picking which exon to target, or shortlisting guides before an off-target check. Off-target specificity, base/prime editing, and HDR donors 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。
Orders and orients assembled contigs into chromosome-scale scaffolds from long-range linking data, inserting N-gap spacers (adds no sequence). Covers Hi-C/Omni-C scaffolding (YaHS, SALSA2, 3D-DNA/Juicer), Hi-C read-mapping prerequisites (map each end separately, no mate rescue, dedup, enzyme-aware), reading the contact map for misjoins/inversions/false-duplications, manual curation in Juicebox/PretextView (the VGP/DToL standard), reference-guided scaffolding (RagTag) and its karyotype-erasure hazard, genetic-map (ALLMAPS) and Bionano optical-map integration, chimera-breaking before scaffolding, gap-filling, and telomere/contig-vs-scaffold-N50 QC (tidk). Use when turning contigs into chromosomes with Hi-C, integrating a linkage map or optical map, choosing a scaffolder by available linking data, or judging whether a chromosome-scale assembly is trustworthy.
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。