「can」の検索結果

Neo4j Visualization Library (NVL) — framework-agnostic graph rendering for the browser. Covers @neo4j-nvl/base (NVL class, nodes/relationships, Canvas vs WebGL renderer), @neo4j-nvl/interaction-handlers (ZoomInteraction, PanInteraction, DragNodeInteraction, ClickInteraction, HoverInteraction, BoxSelectInteraction, LassoInteraction, KeyboardInteraction), and @neo4j-nvl/react (InteractiveNvlWrapper, BasicNvlWrapper, StaticPictureWrapper). Use when rendering a Neo4j graph in a browser, feeding driver results through nvlResultTransformer, choosing Canvas vs WebGL, wiring node/relationship click/hover/drag handlers, or embedding NVL in React, Vite, or vanilla JS apps. Does NOT handle Cypher query authoring — use neo4j-cypher-skill. Does NOT handle driver lifecycle, sessions, or executeQuery setup — use neo4j-driver-javascript-skill. Does NOT handle GraphVisualization/Needle default embed — use @neo4j-ndl/react.

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Use when you want deterministic evidence for a review - which already-installed scanners may be run against the checkout, their exact read-only invocations, how to triage their output, and what must never be run or installed

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Use when semgrep, osv-scanner, github-security or snyk MCP tools appear in your tool list - what each server is for, how to call it safely, what data leaves the machine, and how its findings are triaged

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Optimize Docker images with multi-stage builds, distroless bases, BuildKit cache mounts, multi-arch builds, compose watch, security hardening (non-root, seccomp, capabilities drop), and vulnerability scanning via docker scout/trivy. Use when user asks to write a Dockerfile, optimize image size, set up docker-compose, debug containers, harden container security, or scan for CVEs. Do NOT use for Kubernetes deployments (use kubernetes), CI/CD pipeline design (use ci-cd), or Terraform (use terraform).

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Search the agent skills ecosystem to discover and install skills that extend AI coding agent capabilities. Use when user asks "how do I do X" (X being a common task), "find a skill for X", "is there a skill that can...", or expresses interest in extending agent capabilities. Triggers on "find a skill", "install a skill", "skill for [task]", "can you do X", "I need help with [domain]", "how do I [task]". Do NOT use when user has explicitly asked to proceed without a skill, or when the task is better handled by agent's built-in capabilities (file operations, git, basic coding).

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Less common Hyperliquid actions and their rules - dead-man's switch (scheduleCancel), TWAP orders, spot orders, expiresAfter and nonces, API wallet approval from code, sub-account and vault addressing, HIP-3 dexs, and what the desk deliberately does not do (transfers, withdrawals, builder fees, staking). Write actions are Execution Trader only, on an approved ticket. Use when a ticket asks for one of these or when a user asks whether the desk can.

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Runs security audits on codebases — full scans, diff reviews, threat models, vulnerability triage, remediation guidance, and finding tracking. Activate when the user says "security scan", "audit this repo", "review this PR for security", "threat model", "triage vulnerabilities", "fix this vuln", or "track findings".

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Sub-skill: Scan any URL for agent readiness. Checks 22 standards across 5 categories, returns readiness level (0-5), status of all checks, and fix instructions.

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Recognize and extract text from scanned PDFs and images with ComPDF OCR workflows. Use for OCR, searchable PDF generation, text recognition, table recognition, and scanned-document extraction requests.

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Run market research, competitive analysis, investor due diligence, and industry scans. Use when the user wants market sizing, competitor comparisons, fund research, or tech scans.

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Skills for accessing and searching docs in DeepWiki/GitHub’s public code repositories can help users understand open-source project source codes, and users can also ask questions directly about the code docs.

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Analyze and optimize X (Twitter) posts for viral potential and reach using heuristics inspired by X's published open-source recommendation architecture. Use when user wants to: (1) Check if a post will go viral, (2) Score a tweet for engagement potential, (3) Optimize or rewrite a tweet for algorithmic reach, (4) Understand why a tweet underperformed, (5) Build audience in a specific niche. Triggers: "Check if this will go viral", "Make this post buzz", "Will this tweet perform well?", "Optimize my tweet", "How can I make this viral?", "rewrite this tweet", "improve my tweet engagement", "twitter algorithm", "tweet reach", "debug underperforming tweet", "バズるかチェックして", "Xでバズる投稿にして", "伸びるかチェックして", "この投稿を伸ばして", "投稿を改善して", "ツイートを最適化して"

Decomposition methodology for pm agent — turns an approved ARCH document into a Beads task list with explicit dependencies, time-boxes, and acceptance criteria. The pipeline can only orchestrate work it can see; this skill defines what "seeable work" looks like.

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画布能力由 canvas 工具契约提供，本文件仅保留操作顺序和数据安全约束。

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Determine whether front/side/back/top reference templates can be satisfied by one rigid 3D Blender model, choose a canonical source policy, and emit constraints before rebuilding. Use when multiview bboxes, silhouettes, part counts, or depth ratios contradict each other.

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Tests whether data supports a claim: A/B significance, peeking, sample size, eval error bars, multiple comparisons. Use when deciding if results are significant.

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Validate readiness to advance between development phases. Produces a PASS/CONCERNS/FAIL verdict with specific blockers and required artifacts. Use when user says 'are we ready to move to X', 'can we advance to production', 'check if we can start the next phase', 'pass the gate'.

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Read this skill before the first step that uses the built-in browser, the browser pane inside the Claude desktop app (also called the in-app browser, the browser pane, Claude's browser, or "your own browser"), whose tools are named mcp__Claude_Browser__* when the session runs in the desktop app and mcp__remote-devices__Claude_Browser__* when a cloud session is linked to the person's computer; before those tools are turned on there may be a single enable__mcp__remote-devices__Claude_Browser tool instead. It covers the pane's persistent sign-ins, tabs and preview_start, reading pages as text, site approvals, what the pane cannot open, and what to do when it cannot be reached. It is not for Claude in Chrome (mcp__claude-in-chrome__* tools), which has its own skill, and it does not decide which browser to use.

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Find similar design-registration candidates from a product image using Nexscope. Use for image-based design patent candidate screening with region, jurisdiction, Locarno and legal-status filters. Returns evidence for review, never an infringement or freedom-to-operate verdict.

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Query patent bibliographic (catalog) information from the Nexscope patent database by patent ID or publication number. Triggered when users mention patent bibliographic info queries, patent catalog information, patent applicant queries, patent inventor queries, patent classification codes, patent abstract retrieval, patent citation analysis, patent priority claims, patent application citations, patent examiner information, patent bibliographic data, inventor lookup, applicant lookup, patent classification, patent metadata, Nexscope, or patent citations. Even if the user does not explicitly mention "bibliographic info," this skill should be triggered whenever their need involves querying detailed metadata for a specific patent by patent ID or publication number.

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After scaffolded practice, run an unassisted check — a problem with no AI help. Separates what the learner can do with support from what they can do independently. Critical for preventing phantom attainment.

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-deploy canary monitoring. (gstack)

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Whole-repo audit for over-engineering. Like ponytail-review, but scans the entire codebase instead of a diff: a ranked list of what to delete, simplify, or replace with stdlib/native equivalents. Use when the user says "audit this codebase", "audit for over-engineering", "what can I delete from this repo", "find bloat", "ponytail-audit", or "/ponytail-audit". One-shot report, does not apply fixes.

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Lightweight, script-driven variant of data2motion for turning data into a smooth, on-brand animated chart (one self-contained HTML) — built for a TEXT-ONLY model that cannot see its own output. You never write HTML/CSS/SVG/animation; you extract the data, pick a chart, fill a small JSON spec, and run one build script that owns 100% of the look and the motion, so the result cannot drift from the house template style or lose its smoothness. Use to turn a number/stat/table/CSV/paragraph into a quick animated chart, data reveal, or KPI when you want guaranteed template fidelity with minimal reasoning and no image 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。