421 件 ・ 関連度順
概要と使いどころ
OpenDesign's incident retro: the daemon-restart data bug, the root cause, the fix, and the systemic follow-ups. Built as a decision-grade product management deck for engineering, SRE, leadership.
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Searches 18 scholarly APIs for papers, preprints, citations, open-access full text, repository records, and journal OA status, and returns results with reproducible provenance. Covers PubMed, PMC, Europe PMC, bioRxiv, medRxiv, arXiv, OpenAlex, Crossref, Semantic Scholar, CORE, Unpaywall, OpenCitations, PubTator3, Zenodo, Figshare, ROR, BioStudies, and DOAJ. Use when searching for papers, citations, DOI/PMID/arXiv lookups, abstracts, full text, open-access PDFs, preprints, citation graphs, author publications, biomedical entity annotations, deposited records (Zenodo, Figshare, BioStudies), institution ROR IDs, or any scholarly literature query. Triggers on mentions of any supported database or requests like "find papers on X", "look up this DOI", "who cites this paper", or "get me the 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。
Define and implement Service Level Indicators (SLIs) and Service Level Objectives (SLOs) with error budgets and alerting. Use when establishing reliability targets, implementing SRE practices, or measuring service 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。
Comprehensive incident response framework from detection through resolution and post-incident review. Battle-tested SRE/DevOps practices: severity classification, timeline reconstruction, structured post-incident analysis. Use when declaring an incident, coordinating multi-team response during an outage, leading a post-mortem, or setting up on-call practices for a new service.
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 planning, running, or learning from chaos engineering experiments. Triggers on "chaos experiment", "fault injection", "gameday", "resilience test", "blast radius", "steady state", "abort criteria", "Chaos Toolkit", "Chaos Mesh", "Litmus", "Gremlin", "AWS FIS", or any deliberate failure-injection question. Ships experiment designer, blast-radius calculator, and postmortem generator (all stdlib Python), 4 references on chaos principles + experiment design + attack taxonomy + tooling landscape, and a /chaos-experiment slash command. Composes with feature-flags-architect (kill switches as abort triggers) and kubernetes-operator (common chaos targets).
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 a Head of Ops, Knowledge Manager, or TPM-Internal needs to author, validate, or clean up company SOPs and internal runbooks (procurement intake, vendor offboarding, incident-comms cascade, employee onboarding) — including 5W2H completeness checks (Who-What-When-Where-Why-How-HowMuch), cross-link and orphan-page validation across a sprawling Notion/Confluence/Obsidian wiki, KB ingestion + hygiene reporting, and runbook step verification (named owner, expected duration, observable success signal, rollback path, escalation contact). Pairs Ishikawa's 5W2H method, Gawande's *The Checklist Manifesto*, ISO 9001, ITIL v4, and Google SRE Workbook runbook discipline with deterministic stdlib-only Python tools that score completeness, detect anti-patterns, and emit prioritized cleanup lists (e.g., "validate this runbook before it goes into rotation", "audit our Confluence wiki for stale and orphaned SOPs").
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。
Diagnoses GKE HorizontalPodAutoscaler (HPA) failures — metrics showing as <unknown>, FailedGetResourceMetric / FailedGetScale / FailedComputeMetricsReplicas events, missing Pod resource requests, custom/external metrics-pipeline breakage (FailedGetExternalMetric / FailedGetCustomMetric, unavailable metrics adapter, control-plane firewall blocking the adapter), HPA that won't scale up or down (tolerance / stabilization window / unavailable rate metrics), scale-to/from-zero problems, and slow HPA reaction on large clusters. Use when an HPA isn't scaling a workload as expected or reports metric errors. Don't use for configuring or authoring new HPA/VPA objects or scaling best practices (see the gke-workload-scaling skill), or for Cluster Autoscaler / node-pool sizing.
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。
Configures best-practice, high-signal alerting policies for Cloud Run resources on Google Cloud (services, jobs, and worker pools) based on seasoned SRE practices. Use when analyzing, recommending, writing, or deploying Terraform PromQL alerting policies to monitor Cloud Run error rates (4xx/5xx), request latency, container instance saturation (warning/critical), container CPU/memory utilization and allocation, billable instance time, job execution status, and worker pool queue backlog. Don't use for GKE workloads (use gke-alert-configuration) or Compute Engine VMs.
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。
数学问题发现与证据检索。用于界定研究问题、查定义/定理谱系、检索 arXiv/Scholar/OpenAlex/Crossref、建立来源账本、证据图、查新或从证据缺口生成可证伪猜想。
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。
Defines service level objectives, creates error budget policies, designs incident response procedures, develops capacity models, and produces monitoring configurations and automation scripts for production systems. Use when defining SLIs/SLOs, managing error budgets, building reliable systems at scale, incident management, chaos engineering, toil reduction, or capacity 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。
服务概述 + alerts 表 + dashboards + 操作命令 + on-call + 事故清单
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 this skill whenever the user asks about NetExec (nxc) — a network exploitation and post-exploitation tool for Active Directory environments. Triggers include: any mention of 'nxc', 'netexec', 'crackmapexec' successor questions, AD enumeration, SMB/LDAP/WinRM/MSSQL/SSH/RDP/VNC/WMI/FTP/NFS protocol attacks, password spraying, credential dumping (SAM, NTDS, LSASS, DPAPI), Kerberoasting, ASREPRoasting, lateral movement, BloodHound collection, module usage, or any pentest workflow involving Windows domain environments. This skill covers ALL protocols, ALL modules, and ALL core features of NetExec. Always provide full command examples with correct flags and options.
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。
Active Directory attack methodology for internal network red team engagements. Covers reconnaissance (BloodHound, PowerView, ADExplorer), credential abuse (Kerberoasting, ASREProasting, NTLM relay, LLMNR/NBT-NS poisoning), privilege escalation (ACL abuse, GPO abuse, unconstrained/constrained delegation), lateral movement (Pass-the-Hash, Pass-the-Ticket, Overpass-the-Hash, WMI/WinRM/PsExec), persistence (Golden/Silver/Diamond Tickets, DCSync, DCShadow, AdminSDHolder, Skeleton Key), forest trust attacks, ADCS abuse (ESC1-ESC15), and modern MDI/Defender for Identity evasion. Use when assessing on-prem AD, hybrid AD/Entra ID environments, or ADCS deployments.
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。
Draws original design and coding scenes as hand-authored SVG cards (480x360) in a two-colour brush-marker style. Identifying traits: thick wobbly black marker lines with blobby ends, built as filled ribbons; one second ink, mint green, in flat blocks that slip 2-10 px off the line like a misregistered print; solid black hair, trousers and shoes with mint highlight dashes; and a crinkly squiggle camo on cream areas, all on warm cream paper. Characters are chunky, with profile heads, big noses, dot eyes, big hands and feet. It covers people coding, thinking, carrying and resting with laptops, mugs, chairs and rubber ducks. Use when someone asks for brush, marker, felt-tip, two-colour, duotone, riso-print, zine, mint-and-black or doodle illustrations, or for empty states, onboarding, 404 pages, blog headers, feature spots or marketing cards with a bold hand-made look.
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。
Draws original hand-written SVG spot illustrations in the One-line style, joyful action figures doing design and coding work. One continuous uniform black line (2.3 px at 480 wide) loops and doubles back to draw the whole figure. Flat coral, periwinkle and white patches sit behind the line, wobbly and deliberately knocked 2–6 px out of register like a misprinted riso. Tops carry coral stripe lines, and there is no ground plane, only a squiggle, a curl or a few speed strokes, all on warm beige paper. Covers the palette, a route-building toolkit (tube limbs, hand and shoe loops, wobble patches, masks), poses, composition and a render-critique loop. Use when asked for one-line, single-line, continuous-line, misregistered, riso-style or playful doodle illustrations, for empty states, onboarding, 404 pages, blog headers, feature spots, launch announcements or marketing cards.
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。
0G Compute Network guide for decentralized AI inference, fine-tuning, and GPU services. Covers chatbots, image generation, speech-to-text, SDK integration (0g-serving-broker), processResponse API, broker.inference methods, CLI commands (0g-compute-cli), and account management. Use this skill for any 0G compute, 0G AI, or decentralized GPU question.
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。
Trustpilot customer reviews scraper for any company listed on trustpilot.com — given a company domain (e.g. shopify.com, apple.com, shopwagandtail.com) plus optional filters (page number, single star rating 1-5, single language ISO code, verified-only flag, has-company-reply flag, date period last30days/last3months/last6months/last12months, free-text keyword search, and reviewer countryCode client-side filter), extracts paginated reviews with 20+ fields per review: reviewId, reviewUrl, reviewTitle, reviewDescription, reviewRatingScore (1-5), reviewDate (ISO publishedDate), reviewDateOfExperience, reviewLabel, isReviewVerified, reviewer (display name), reviewerId, reviewersCountry (ISO Alpha-2), reviewLanguage, reviewCompanyResponse (the company reply text), plus pagination metadata (currentPage, totalPages, totalCount). Optional flags add reviewer profile metadata (reviewerNumberOfReviews, reviewerProfileIsVerified), reply analysis dates (companyReplyPublishedDate, companyReplyUpdatedDate), extended metadata (reviewSource, reviewVerificationSource, reviewLikes), and review photos. Use when user mentions Trustpilot reviews, scrape Trustpilot, get reviews from Trustpilot, Trustpilot review scraper, Trustpilot customer reviews, extract Trustpilot reviews, Trustpilot review data, download Trustpilot reviews, paginate Trustpilot, paginated Trustpilot reviews, filter Trustpilot reviews by star, filter Trustpilot by language, verified reviews Trustpilot, has reply Trustpilot, company response Trustpilot, Trustpilot reply analysis, brand monitoring Trustpilot, sentiment analysis Trustpilot, competitor reviews Trustpilot, bulk reviews from a Trustpilot page, batch download reviews, trustpilot.com reviews scraping, fake review research Trustpilot, Trustpilot dataset, persona research from Trustpilot reviews, Trustpilot keyword search reviews, Trustpilot date range reviews, review export Trustpilot. Also applies to comparing review trends across competitors, training data for LLM sentiment classifiers, monitoring competitor response time, exporting reviews for BI dashboards, lead generation from active reviewers, ML / fake-review detection, and aggregator sites that display third-party reviews.
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。
Search 10 academic paper databases via REST APIs for research papers, preprints, and scholarly articles. Covers PubMed, PMC (full text), bioRxiv, medRxiv, arXiv, OpenAlex, Crossref, Semantic Scholar, CORE, Unpaywall. Use when searching for papers, citations, DOI/PMID lookups, abstracts, full text, open access, preprints, citation graphs, author search, or any scholarly literature query. Triggers on mentions of any supported database or requests like "find papers on X" or "look up this DOI".
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。
VS-Enhanced Journal Matcher with Journal Intelligence MCP — Real-time journal data pipeline with checkpoint-based human decisions. Uses OpenAlex + Crossref APIs for live metrics. Light VS applied: Avoids IF-centric recommendations + multi-dimensional matching strategy Use when: selecting target journals, planning submissions, comparing publication options Triggers: journal, submission, impact factor, academic journal, publication, submit
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 a complete academic literature survey from scratch using multi-agent orchestration. Searches academic databases (OpenAlex, CrossRef, Unpaywall), downloads PDFs, builds BibTeX, drafts a LaTeX review, compiles it, reviews for quality, and revises based on feedback — all automated. Use this skill whenever the user asks to "generate a literature review", "write a survey paper", "review recent papers on [topic]", "create a survey of [field]", "综述", "文献综述", "survey papers in top journals", or wants a multi-agent pipeline to produce a publishable-quality literature review. Also trigger when the user wants to search multiple journals for papers on a topic and synthesize findings into a structured document. Works for any academic field but optimized for economics journals.
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。
Recommend AND run open-source AI tools, agents, Claude Code / Codex skills, and MCP servers for any stage of a literature review — searching, reading, extracting, synthesizing, screening, citation-checking, and paper writing. Use when the user asks "what tool should I use to..." OR "install/run/use <tool> to ..." for research/lit-review work: automating a survey or related-work section, PDF→Markdown extraction for LLMs (MinerU/marker/docling), PRISMA / systematic review (ASReview), citation-backed Q&A over PDFs (PaperQA2), wiring papers into Claude/Cursor via MCP (arxiv/paper-search/zotero servers), or chatting with a Zotero library. Ships a launcher (scripts/litrun.py) that installs each tool in an isolated venv and runs it. Curated catalog of 70+ vetted projects. 支持中英文（用于「文献综述工具选型」与「一键安装/运行」）。
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。
Audit economic analysis outputs (fiscal briefings, macro briefings, market research, longlists, and other quantitative economic documents) against methodology standards, academic literature, and common errors. Runs structured checks across core categories including counterfactual, additionality, discounting, double counting, distributional analysis, Aqua Book RIGOUR, and Flyvbjerg-style strategic misrepresentation detection. Returns a RAG scorecard with issues ranked by severity.
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。
Verify academic citations against CrossRef, Semantic Scholar, and OpenAlex. Detects AI-hallucinated references, chimeric citations, and suspicious patterns.
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。
Write a blameless incident postmortem under postmortems/ following the Google SRE shape — evidence-based timeline, trigger vs root cause vs symptom, contributing factors, what went well, and owned+dated+verifiable action items. Read when asked to write a postmortem, do an incident review, run a root cause analysis, write up the outage, retro on the outage, or when the user says we had an incident and wants it documented. Do NOT read to frame a proposal (use frame-a-proposal), write a spec (use write-a-spec), record a decision (use record-a-decision), or review a design (use review-a-design) — a postmortem documents an incident that already happened, it does not propose, specify, decide, or critique future 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。