「dan」の検索結果

Provides authoritative compatibility checks, pricing estimates, connection troubleshooting, pre-warming guidance, and infrastructure mutations for Amazon Keyspaces (for Apache Cassandra). Covers LWT/batch operations, secondary indexes, materialized views, capacity modes, TTL, PITR, CDC, auto-scaling, multi-region keyspaces, UDTs, nodetool diagnostics parsing, SQL-to-Cassandra migration, and Cassandra-to-Keyspaces migration scenarios. Agents frequently produce incomplete or incorrect answers about Keyspaces feature support without this skill loaded.

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。

KubeKey (kk) Usage Guide. For Kubernetes cluster lifecycle management including creation, scaling and deletion. Use this skill whenever the user mentions kubekey, kk commands, cluster setup, cluster management, adding nodes, deleting nodes, creating inventory files, configuring clusters, installing Kubernetes, or deploying K8s. Also use this skill when the user asks about inventory.yaml, config.yaml formats, CNI configuration, container runtime setup, offline installation, or artifact operations. Provides detailed guidance on kk subcommand usage, config file formats, inventory structure and common 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。

Configure this skill should be used when the user asks about "API contract", "api-contract.md", "shared interface", "TypeScript interfaces", "request response schemas", "endpoint design", or needs guidance on designing contracts that coordinate backend and frontend agents. Use when building or modifying API endpoints. Trigger with phrases like 'create API', 'design endpoint', or 'API scaffold'.

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。

Process use when you need to work with database indexing. This skill provides index design and optimization with comprehensive guidance and automation. Trigger with phrases like "create indexes", "optimize indexes", or "improve query performance".

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。

Execute use when you need to work with query optimization. This skill provides query performance analysis with comprehensive guidance and automation. Trigger with phrases like "optimize queries", "analyze performance", or "improve query speed".

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。

Organization-grade cloud and supply-chain attack-surface discovery: S3/GCS/Azure Blob bucket discovery via observed-name mining (CNAME/cert-SAN/Wayback) and bounded two-class permutation (6 prefixes x 15 suffixes on trusted tokens, bounded target-bound expansion on subdomain stems), existence (HEAD/GET) vs public-listing confirmation, object-key triage into 9 value tiers (database dumps, credentials, IaC state, kubeconfig, VCS dirs, config, archives, PII, logs), dangling-CNAME bucket-takeover detection, and the ownership-gated severity model that stops an unattributable public bucket from becoming a false CRITICAL; the fully offline AWS-account-ID recovery from a leaked AKIA/ASIA/AROA access key (base32 decode, runnable stdlib Python, canonical test vector, AWS-documentation-example-ID screening); dependency-confusion confirmation for npm/PyPI (internal-signal classifier -- private-registry binding vs org-namespace match -- paired with a read-only public-registry 404 check and the npm scope-claimability nuance the public search API misses); and passive cloud-native/container/Kubernetes/CI control-plane fingerprinting (Lambda URLs, API Gateway, Cloud Run, App Service, kubelet/etcd/K8s API/dashboard, Jenkins/GitLab/Argo CD) as an org-attribution and exposure surface. Passive/discovery only -- no exploitation, no credential submission, no active control-plane confirmation (a stage-6 validate_cloud active tier is described but out of scope). Use when enumerating a target's cloud storage footprint, recovering an AWS account ID from a leaked key, confirming a supply-chain dependency-confusion vector, or fingerprinting cloud-native/K8s/CI infrastructure for an authorized external recon 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。

Org-grade attack-surface mapping: given a company's legal identity, discover its ENTIRE owned internet footprint — corporate family -> owned domains -> owned netblocks/ASN -> live assets — with attribution discipline, not just DNS breadth. The org-first attribution pyramid (legal entity -> LEI/registration -> corporate family -> owned domains -> owned netblocks/ASN -> live assets). Corporate-identity resolution via the GLEIF LEI API (legal name -> LEI, exact-LEI direct-children expansion, downward-only depth-capped BFS, NEVER a name re-resolution), SEC-EDGAR full-text search + Exhibit-21 subsidiary entity names, OpenCorporates entity corroboration, Wikidata SPARQL corporate graph (P856/P355/P749/P1830). Domain attribution via reverse-WHOIS (WhoisXML preview-then-purchase quota guard, SecurityTrails associated-domains — both paid), crt.sh O= certificate-transparency organization pivot (keyless), infrastructure correlation (shared NS/MX/SaaS-TXT, netblock membership, reverse-DNS PTR), and the independent-evidence combiner (1-prod(1-w_i), rule of three, OwnerTier NONE/WEAK/MODERATE/STRONG/CONFIRMED) — discover-only `related:` candidates are NEVER auto-scanned. Netblock/ASN attribution via org-first RIR queries (ARIN Whois-RWS org-handle search, RIPE DB organisation + inverse-org search) that recover 'dark netblocks' with no DNS link to the seed, ASN discovery (RIPEstat + BGPView union), the HYPERSCALER-SCOPE GUARD (never attribute a whole AWS/GCP/Azure/Cloudflare announced range to a tenant — keep only the seed-containing block, tag shared_hosting_cdn), and org-identity-seeded internet-scan-index queries (Shodan/Censys/ZoomEye/FOFA/BinaryEdge org: filters + an always-on keyless crt.sh fallback). Promote-to-scan triage ranks forgotten discover-only netblocks by remote-access exposure (gateway-vendor/KEV/control-plane/datastore port scoring) into an operator queue. Attribution confidence rubric + anti-patterns (namesake grafting via GLEIF name re-resolution, single-signal ownership, hyperscaler over-attribution, privacy-WHOIS pivot poisoning, RIR org-name collisions). Passive/keyless-first OSINT only — every paid-key dependency is enrichment on top of a keyless core, never a hard requirement. Use when mapping an organization's full corporate-family internet footprint, resolving a legal entity to its LEI/subsidiaries, discovering domains/netblocks/ASNs an org owns beyond its one seed domain, auditing M&A/shadow-IT sprawl, or scoping an engagement that starts from a company NAME rather than a domain.

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 skills, agents, extras, hooks, plugins, and MCP connection settings with the Skillshare CLI. Use when the user asks to configure or run Skillshare, install or sync resources across AI tools, manage shared memory notes, review a session for lessons or dream over saved memories, import MCP settings, manage targets, audit skills, recover backups, or troubleshoot Skillshare configuration and sync. Covers global and project modes, noninteractive automation, and guidance for the terminal UI.

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。

Terminal security analysis for shell environments. This skill should be used when checking commands for supply-chain attacks before execution, scanning repositories for hidden content or config poisoning, scoring URLs for homograph attacks, setting up AI tool protection, inspecting Python package artifacts, governing untrusted tasks or Web3 commands, auditing browser extensions, creating provenance receipts, downloading and executing scripts safely, investigating why tirith blocked a command, managing trusted patterns, running security audits, configuring MCP gateway proxies, or working with threat intelligence databases. Also use when the user mentions "tirith", "pipe-to-shell", "homograph", "ANSI injection", "zero-width", "punycode", "terminal security", "shell hook", "cloaking detection", "supply chain attack", "bidi override", "invisible unicode", or "config poisoning". Even if the user does not explicitly name tirith, use this skill when they ask about protecting shell environments, intercepting dangerous commands, or hardening AI agent tool execution.

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 PRs for review by cleaning noisy history, improving PR descriptions, and adding reviewer guidance without changing code behavior. Use for "make this easy to review", "tidy this PR", "clean up commits", or "annotate the diff".

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 when sequencing an addition, refactor, or rewrite. Remove dead code, redundant validators, and stub references first, then build on the simpler base.

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。

Doctrine for designing and evolving any **SDK** Grida ships — TypeScript, Rust, or otherwise. "SDK" here means a surface that crosses a foreign-or-foreign-treated boundary: published packages, separately-versioned consumers, FFI bindings, public-by-design modules. An SDK's job is to refuse; a strict, honest surface rejects the wrong contents and keeps the package testable in isolation. Default is "core, not customizable"; customization is the exception, defended by a deciding table. Use when authoring or evolving any such surface — `@grida/*` published packages, engine crates (gridaco/nothing `crates/*`) published or FFI-exported, intent/message vocabularies, any contract a second author will compile against. Internal-only helper packages are welcome to follow, not forced. Companion skill for two-sided contract work: $sdk-seam. Critique partners: $pedantic, $etiology. Related: $naming.

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 writing or improving README files. Not all READMEs are the same — provides templates and guidance matched to your audience and project type.

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 slide decks and presentations for research talks. Use this for making PowerPoint slides, conference presentations, seminar talks, research presentations, thesis defense slides, or any scientific talk. Provides slide structure, design templates, timing guidance, and visual validation. Works with PowerPoint and LaTeX Beamer.

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 journal manuscripts, conference papers, research posters, and grant documents using venue-specific formatting guidance and bundled LaTeX scaffolds. Use when selecting an official template, checking current page or anonymity rules, adapting academic writing to a venue, or inspecting a submission PDF.

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。

Subdomain takeover detection and exploitation playbook. Use when targets have dangling CNAME/NS/MX records pointing to deprovisioned cloud resources, expired third-party services, or unclaimed SaaS tenants that an attacker can register to serve content under the victim's domain.

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 native iOS interfaces following Apple Human Interface Guidelines. Use when the user mentions "iPhone app", "iPad layout", "SwiftUI", "UIKit", "Dynamic Island", "safe areas", "HIG compliance", "SF Symbols", "haptic feedback", "iOS accessibility", "make my app feel native", or "follow Apple design guidelines". Also trigger when building tab bars, navigation stacks, sheets, or modals for iOS, implementing dark mode, or adapting layouts across screen sizes. Covers navigation patterns, accessibility, SF Symbols, and platform conventions. For general UI polish, see refactoring-ui. For affordance design, see design-everyday-things.

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 the small details -- triggers, rules, feedback, loops and modes -- that separate good products from great ones. Use when the user mentions "microinteraction", "button feedback", "loading state", "toggle design", "animation detail", "state transitions", "input feedback", "the interface feels dead", "make the UI feel responsive", or "add polish to interactions". Also trigger when designing form-validation responses, progress indicators, confirmation dialogs, or any element where the user expects immediate feedback. Covers trigger design, state rules, feedback mechanisms, and progressive loops. For overall UI polish, see refactoring-ui. For affordance design, see design-everyday-things.

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。

Guide for editing videos where the primary content is people talking — talking-head / 口播, interview / 访谈, lecture, tutorial, podcast, course content, and similar talking-driven formats. Use when the user wants speech editing on a talking video (剪口播 / 口播剪辑 / 去口癖 / clean up fillers / smooth speech), motion graphics layered onto talking video (口播加 MG / 加动画), or B-roll on a talking video (加 B-roll / add B-roll). For motion graphics specifically, use this together with the active Motion Graphics skill/workflow available in the current OpenChatCut environment — this skill adds talking-specific guidance (speech-rhythm timing, frame-aware placement, subject/caption protection, placement verification).

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。

OpenChatCut product knowledge — UI layout, editor features, and how generation providers are configured. Use when the user asks about the product interface, how to use a feature, where to find something, or needs GUI guidance for something the agent cannot do directly. Also use as fallback when a task fails and the user needs to complete it manually in the UI. NOT for live project-state queries ("where are my folders?", "what's on my timeline?", "where is clip X?") — those are answered by `read_project`, not by this skill.

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。

AI video generation via Fal.ai, Seedance 2.0, Kling, MiniMax Hailuo, xAI Grok Imagine, and OFox. Use when the user wants to generate a video clip — text-to-video, image-to-video, first/last-frame transitions, reference-guided generation, multi-shot, or generatively editing / extending an existing clip.

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。

Generate complete JSON-LD schema markup for blog posts with Article/BlogPosting, Person, Organization, BreadcrumbList, ImageObject, and optional FAQPage. Validates against Google requirements and warns about deprecated types. Use when user says "schema", "blog schema", "json-ld", "structured data", "schema markup", "generate schema".

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。

Query Google NotebookLM notebooks for source-grounded, citation-backed answers from user-uploaded documents. Manages notebook library, handles Google authentication, and supports smart discovery. Works standalone via /blog notebooklm or internally from blog-write and blog-researcher for source-grounded research context. Falls back gracefully when not configured. Use when user says "notebooklm", "notebook", "query notebook", "ask notebook", "notebook research", "source grounded research", "document query", "notebook 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。

Post-writing SEO validation with pass/fail checklist covering title tag length and keyword placement, meta description quality, heading hierarchy and keyword density, internal/external link audit with anchor text analysis, canonical URL verification, Open Graph meta tags (og:title, og:description, og:image), Twitter Card validation, structured data presence and validity, URL structure optimization, and image alt text presence. Produces prioritized fix list with specific recommendations. Use when user says "seo check", "check seo", "validate seo", "blog seo", "seo validation", "on-page seo", "title tag check", "meta description check", "heading check", "link 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。