「poi」の検索結果

Extrem kurzes, substantielles Ausgabe-FORMAT fuer EINE Entscheidung oder Entscheidungsgruppe, wenn die dahinterstehende Analyse bereits existiert (im Chat entstanden, aus `decide`, aus `decision-briefing`, aus einem Ticket oder Dokument): Kontext in 2-3 Zeilen, Pro/Contra je Option als Stichpunkte im paveman/caveman-reduzierten Stil, Talking Points, eine begruendete Empfehlung, und ein Pfad/Link zur Vollanalyse zum Komplett-Nachlesen. Nutze diesen Skill bei "gib mir das kurz mit Pro Contra und Empfehlung", "executive summary zur Entscheidung", "kurzkontext zu <Thema>", "fass die Entscheidung X in einer Kurzform zusammen", /decision-shot, oder wenn ein Ergebnis an jemanden weitergereicht werden soll, der nur die Essenz braucht, nicht die volle Herleitung. NICHT nutzen, um viele offene Entscheidungen zu SAMMELN und per Buchstabe abzufragen -- das macht decision-briefing; NICHT nutzen, um eine Entscheidung erst zu ANALYSIEREN -- das macht decide. decision-shot setzt eine fertige Analyse voraus und komprimiert nur deren Praesentation.

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Points to the standalone module law-checker ("Legal Department"): source-grounded AI first-look legal assessments for German law with a statute registry and a statute-embodiment agent. Use this skill when a situation, contract, official notice, or legal question under German law should be checked with exact citations (article/section, paragraph, sentence) -- with a clear boundary: AI-assisted first orientation, not a substitute for a lawyer.

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Autonomer Langlauf-Modus ohne laufende Rückfragen — Startbedingungen (Ziel, Scope, Budgets, Checkpoints), Entscheidungsstufen und Abbruchregeln für unbeaufsichtigte Läufe; erhöht die Ausdauer, nicht die Berechtigung. Nutzen, wenn ausdrücklich ein längerer autonomer Lauf gewünscht ist.

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Builds one DRAFT message house for a product, service, programme or initiative from the source material the user provides: an umbrella statement, two to four pillars and graded proof points under each, with every proof point that lacks a source flagged, a claim sensitivity table, an audience coverage check and open questions. Use when the user asks to "build a message house", "write our messaging framework", "what are the key messages for this launch", "turn this research into messaging pillars" or "test our current messaging against the evidence". Do not use for a campaign one-pager, use campaign-brief-builder instead; to check whether a written document's claims are substantiated, use claims-evidence-map. Drafts for human review; never approves, authorises or signs off.

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。

Sweeps a SharePoint library listing (an export or a listing the agent can reach, with file name, link, review-date column and owner column) for documents past their review date and returns a dated DRAFT review sweep report (Overdue, Due soon, No review date, Summary) plus one ready-to-paste reminder per document owner for the user to send. Never changes metadata, sends a message or invents a document, date or owner. Use when the user asks to "find the documents past their review date", "run the review sweep on the policies library", "which documents are overdue for review", "audit the review dates in this library export" or "draft reminders to owners about stale documents". Do not use for duplicate, conflict and ownership checks across knowledge files, use knowledge-base-hygiene-review instead; for gaps in an engineering deliverables register, use master-document-register-check. Drafts for human review; never approves, authorises or signs off.

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Proposes the instrumentation and control content a P&ID adds to an accepted PFD process model: instruments drawn carried over as facts, measurement points and control loops the control philosophy requires, tag structure per the project instrument numbering procedure, system interfaces, and alarms, interlocks, trips and fail actions as quoted. Never assigns safety functions, ranges or setpoints. Use when the user asks to "run the instrumentation and control enrichment", "add the instrument section to the P&ID draft", "list the control loops the philosophy requires" or "carry the PFD instruments into the P&ID" after the piping section. Do not use for safety flags, SIL or trip classification, use process-safety-flags instead; do not use to assign tag numbers, use tagging-and-numbering. Drafts for human review; never approves, authorises or signs off.

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 review custom WordPress URL rewrites: add_rewrite_rule, add_rewrite_tag, query_vars, CPT/taxonomy rewrite slugs, add_rewrite_endpoint, soft vs hard flushes, rewrite_rules cache behavior, and the rule that flush_rewrite_rules() must not run on every request. Use for custom pretty URLs, CPT permalink 404s, endpoint rewrites, and code containing flush_rewrite_rules or add_rewrite_rule.

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。

Automate Appointo tasks via Rube MCP (Composio). Always search tools first for current schemas.

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。

Builds production-ready REST API endpoints with validation, error handling, authentication, and documentation. Follows best practices for security and scalability.

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 the user asks to "package our proof points", "build reusable stat cards and case snippets", or "put proof where each pillar makes its claim"; turns claims-ledger-approved proofs into reusable proof modules — stat cards, case snippets, testimonial blocks, comparison proofs — each pinned to a message-house pillar and the ledger claim ID it substantiates, and flags any pillar making a claim with no approved proof behind it. Never adjudicates a proof: unverified or ledger-absent proofs are marked '[needs source]' and routed to the claims candidates. Not for adjudicating or substantiating claims — use offer-claims-registry; not for fabricating a benchmark to fill a gap — a missing proof is flagged, not invented; not for scoring narrative quality — use narrative-quality-auditor. 证据模块/证据卡/客户案例/主张对齐

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 the user asks to "monitor my launch", "track our Product Hunt / Hacker News ranking", or "watch the launch window"; runs the T-0 to T+30 window watch — pre-launch instrumentation verification (UTM/event checks, the upstream of RAMP P1), HN rank/points/comments polling with a comments-over-points flamewar early-warning (Estimated heuristic), PH votes/featured status, store charts and reviews, news echo, D0/W1/M1 KPI snapshots vs targets, spike-vs-sustain and owned-capture reads, and alert thresholds against the launch-tier KPI targets. Not for launch-day go/rollback calls — use launch-day-conductor; not for metric deep-dives — use performance-analyzer; not for SEO rank tracking — use rank-tracker. 发布监控/排名轮询/火焰战比/spike-sustain

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差分に追加されたソースコードへ混入した不可視・危険な Unicode 文字（タグ文字・異体字セレクター・ゼロ幅文字・双方向制御/マーク・変則空白）を検出する。GlassWorm 型サプライチェーン攻撃・ASCII smuggling・Trojan Source（CVE-2021-42574）でコードを不可視化する手口を、決定論的な静的解析（列挙した code point 集合に限定）として捕捉し、canary テストで誤検出の再発を防ぐ

在授权渗透测试中挖掘 Web 缓存投毒与缓存欺骗（web cache poisoning / cache deception）。当目标前有缓存层（CDN/反代/Varnish）且缓存键未覆盖某些影响响应的输入（unkeyed header/参数/解析差异）时使用——典型场景：X-Forwarded-Host 反射进响应被缓存、unkeyed 参数、缓存键规范化差异、静态扩展名欺骗缓存私有页。适用目标类型 Web / CDN。触发场景包括用户说"测下缓存投毒""X-Forwarded-Host 能不能毒缓存""缓存欺骗看一下""unkeyed 输入有没有"。输出：投毒/欺骗可行性 + 被缓存证据的 finding（含 killed 记录）。

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Develops full-stack Dart backends using the Serverpod framework with PostgreSQL, Redis, and Docker. Use when building type-safe API endpoints, defining YAML data models, configuring Serverpod auth, writing server-side tests, running database migrations, deploying to Docker/AWS/GCP, or using Serverpod Mini for database-less BFF proxy endpoints.

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Use when working with Crowdstrike — crowdStrike Falcon endpoint detection and response, threat intelligence, host management, and incident investigation. Covers detection queries, host inventory, IOC searches, real-time response sessions, and vulnerability assessment. Use when investigating security incidents, reviewing endpoint health, analyzing threat detections, or managing CrowdStrike Falcon sensors.

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Use when working with Azure Cdn — azure CDN management covering profiles, endpoints, custom domains, caching rules, origin groups, and performance analytics. Supports Microsoft, Verizon, and Akamai CDN providers within Azure. Use when managing Azure CDN endpoints, analyzing cache performance, configuring delivery rules, or troubleshooting content delivery.

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Use when working with Alchemy — alchemy Web3 development platform management including app configuration, RPC endpoint health, webhook notifications, NFT API usage, Enhanced APIs, gas optimization, and usage analytics. Covers request volume monitoring, error rates, compute unit consumption, and multi-chain endpoint health.

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 working with Aws Backup — aWS Backup vault, plan, and job management. Covers backup vaults, backup plans, backup selections, recovery points, backup jobs, restore jobs, and compliance frameworks. Use when auditing backup coverage, checking backup job status, reviewing recovery points, or validating backup compliance.

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。

PowerPoint (.pptx) manipulation via MCP server. Use for creating slides, formatting presentations, managing placeholders, adding images, applying templates, or extracting text from .pptx files.

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Plan and coordinate the deployment of a model to Amazon SageMaker AI. Use this skill whenever the user wants to deploy, host, serve, or expose a model on SageMaker or AWS — including phrases like "deploy a model", "host this LLM on AWS", "serve this embedding model", "deploy a reranker", "deploy a text-to-image / diffusion model", "host this for async inference", "create an endpoint", "serve my fine-tuned model", or any request that involves making a model available for inference on AWS. Use this even when the user is vague (e.g. "I just want to get this running on AWS, you figure it out"). Works for text-generation LLMs, embedding models, rerankers, classifiers, text-to-image / diffusion models — picks the right serving stack and chooses between real-time and async inference. This is the entry-point skill for SageMaker deployment work — it asks clarifying questions, picks a deployment pathway, and coordinates the other deployment skills.

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Guide for MSBuild extensibility: CustomBefore/CustomAfter hooks, wildcard imports with alphabetic ordering, import gating with control properties, NuGet package build extension layout (build/buildTransitive), and the MicrosoftCommonPropsHasBeenImported guard. Only activate in MSBuild/.NET build context. USE FOR: diagnosing and fixing MSBuild import and hook patterns, reviewing and fixing extension point anti-patterns in Directory.Build files, fixing missing Exists() guards on imports that break fresh clones, fixing NuGet package hooks being silently dropped instead of appended, making build targets extensible for other projects, injecting custom logic into the build pipeline, creating NuGet packages that extend the build, conditionally disabling imports. DO NOT USE FOR: target authoring patterns (use target-authoring), props vs targets placement (use directory-build-organization), general anti-patterns (use msbuild-antipatterns), non-MSBuild build systems.

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。

Create, modify, and manage PowerPoint presentations.

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。

Turn a real document (PDF, PPTX, DOCX, Keynote export, slide deck, proposal, whitepaper, report) into a finished AI-generated video using the Ozor MCP. Use this skill whenever the user attaches, uploads, references, or points to a document file and wants a video from it — e.g. 'make a video from this pitch deck', 'turn this PDF into a video', 'video from my proposal.docx', 'generate a video from this PowerPoint', 'create a video from this report', 'this whitepaper → video'. This skill runs the document-to-video pipeline: analyze_document → present the plan to the user → update_plan if needed → generate_from_plan → export_video → wait_for_export → get_embed_code. It always uses the plan-based flow so slide visuals are preserved. Do NOT use this skill for plain-text creative briefs (use ozor-generate) or for URLs/landing pages (use ozor-url-to-video).

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。

Implement, review, or improve data visualizations using Swift Charts. Use when building bar, line, area, point, pie, or donut charts; when adding chart selection, scrolling, or annotations; when plotting functions with vectorized BarPlot, LinePlot, AreaPlot, or PointPlot; when customizing axes, scales, legends, or foregroundStyle grouping; or when creating specialized visualizations like heat maps, Gantt charts, stacked/grouped bars, sparklines, or threshold lines.

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。