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概要と使いどころ
Comprehensive OpenTUI skill for building terminal user interfaces. Covers the core imperative API, React reconciler, and Solid reconciler. Use for any TUI development task including components, layout, keyboard handling, animations, and testing.
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-driven presentation workflow for generating editable PPTX decks and slides, reconstructing page visuals, creating reusable Brand/Style/Layout/Deck workspaces, filling native PPTX templates, and enhancing finished PPTX files. Use when the user asks to create, generate, reconstruct, regenerate, beautify, redesign, template, fill, or enhance a presentation, PPT, PPTX, slide deck, or courseware — including adding narration or animation to one — requests a presentation-authored narrated/self-running video, or mentions ppt-master.
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。
Research a topic to support a decision, three ways: draft a research prompt for the user to run in their own tool (ChatGPT, Gemini, Grok, Perplexity, …), turn a finished research report into a short summary with cited sources that other skills can use directly, or run the research here with parallel web searches. Built-in research types: market, domain, technical, competitive, user-voice, academic-lit; also supports choosing between candidates, and custom types via overrides. Use when the user says "deep recon", "research this", "draft a research prompt", "process this research report", "market research", "domain research", "technical research", "competitor research", "literature review", or "help me choose between"
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。
Reconstruct slide images, screenshots, scanned PDFs, or image-only PPTX files as object-level editable PowerPoint. Use for 图片转可编辑PPT、截图还原PPT and diagram reconstruction; not authoring a new deck from research notes.
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。
Reconstruct workflow behind a past coding-agent artifact using local ax sessions/commits/skills/tool traces. Use when asked how X was built.
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。
Internal downstream skill for ctf-sandbox-orchestrator. CTF-sandbox workflow for WebSocket and SSE handshakes, auth material, subscription state, realtime message schemas, reconnect behavior, and frame-driven runtime effects. Use when the user asks to inspect a WebSocket or SSE handshake, decode frames, trace subscriptions, follow reconnect logic, inspect auth material sent during realtime setup, or explain how live frames change rendered or persisted state. Use only after `$ctf-sandbox-orchestrator` has already established sandbox assumptions and routed here.
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。
Root-cause a reconciliation break to its source transaction or posting — follow the audit trail from the break row back to the originating entry on each side and state what differs and why. Use after gl-recon has classified a break.
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。
Detect network reconnaissance and port scanning using Suricata and Snort IDS signatures, threshold-based detection rules, and traffic anomaly analysis to identify Nmap, Masscan, and custom scanning activity.
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。
Hunt AADGraphActivityLogs and MicrosoftGraphActivityLogs in Microsoft Sentinel/Log Analytics using KQL to fingerprint offensive Entra ID enumeration tools such as ROADtools, AADInternals, and AzureHound, including User-Agent signatures, roadrecon endpoint sweeps, and sign-in correlation. Use when investigating suspicious Microsoft Graph API activity, Entra ID reconnaissance, or building Sentinel analytics rules to detect these tools.
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 collaborative forensic incident timelines using Timesketch to ingest, normalize, and analyze multi-source event data (including Plaso output) for attack chain reconstruction and investigation documentation. Use when reconstructing the sequence of events during an incident investigation or when multiple analysts need to jointly tag, annotate, and search a shared DFIR timeline.
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。
Examine NTFS slack space, MFT entries, the USN Change Journal, and Alternate Data Streams (ADS) to recover hidden or residual data, reconstruct deleted-file metadata, and reconstruct available file-system change activity from USN records. Use during deep forensic analysis of an NTFS image when standard file recovery is insufficient, such as hunting for data hidden in ADS.
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。
Parse Windows LNK shortcut files to extract target paths, MAC timestamps, volume serial numbers, and machine identifiers for forensic timeline reconstruction. Use when investigating recently-accessed files, tracking removable media or network paths referenced by shortcuts, or building a DFIR timeline from LNK artifacts.
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。
Analyze Windows Shellbag (BagMRU) registry artifacts with SBECmd and Shellbags Explorer to reconstruct folder browsing activity and prove user interaction with directories, including removable media and network shares, even after the folders are deleted. Use when reconstructing a user's folder access history or proving access to a since-removed directory in DFIR 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。
Wi-Fi reconnaissance methodology — adapter selection, monitor mode and packet injection setup, regulatory domain handling, multi-band airspace mapping, hidden SSID discovery, BSSID/ESSID/channel/PMF/encryption fingerprinting, client probe analysis, vendor OUI lookup, war-driving with Kismet/airodump-ng/Wigle, and structured airspace data capture for downstream attacks. Use at the start of any wireless engagement to build the target map before active attacks; covers 2.4 GHz, 5 GHz, and 6 GHz (Wi-Fi 6E) bands and adapter compatibility for each.
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。
Router for NVIDIA NuRec/NRE: USDZ rendering, NCore conversion, 3DGS, gRPC sensor sim, PhysicalAI HF datasets. Do NOT use for SimReady or infra setup.
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。
Reconcile bounded Stripe payment and payout records with supplied business records while preserving object IDs, currency, time zone, and discrepancy evidence.
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。
Template for commands that implement a structured recipe: validate preconditions, then execute numbered steps. Fork this and replace the placeholder content. The 'Context Validation Checkpoints' section is the key pattern, forcing Claude to verify preconditions before starting.
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。
Complete bug bounty workflow — recon (subdomain enumeration, asset discovery, fingerprinting, HackerOne scope, source code audit), pre-hunt learning (disclosed reports, tech stack research, mind maps, threat modeling), vulnerability hunting (IDOR, SSRF, XSS, auth bypass, CSRF, race conditions, SQLi, XXE, file upload, business logic, GraphQL, HTTP smuggling, cache poisoning, OAuth, timing side-channels, OIDC, SSTI, subdomain takeover, cloud misconfig, ATO chains, agentic AI), LLM/AI security testing (chatbot IDOR, prompt injection, indirect injection, ASCII smuggling, exfil channels, RCE via code tools, system prompt extraction, ASI01-ASI10), A-to-B bug chaining (IDOR→auth bypass, SSRF→cloud metadata, XSS→ATO, open redirect→OAuth theft, S3→bundle→secret→OAuth), bypass tables (SSRF IP bypass, open redirect bypass, file upload bypass), language-specific grep (JS prototype pollution, Python pickle, PHP type juggling, Go template.HTML, Ruby YAML.load, Rust unwrap), and reporting (7-Question Gate, 4 validation gates, human-tone writing, templates by vuln class, CVSS 3.1, PoC generation, always-rejected list, conditional chain table, submission checklist). Use for ANY bug bounty task — starting a new target, doing recon, hunting specific vulns, auditing source code, testing AI features, validating findings, or writing reports. 中文触发词：漏洞赏金、安全测试、渗透测试、漏洞挖掘、信息收集、子域名枚举、XSS测试、SQL注入、SSRF、安全审计、漏洞报告
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。
Complete bug bounty workflow — recon, pre-hunt learning, vulnerability hunting (IDOR, SSRF, XSS, auth bypass, CSRF, race conditions, SQLi, XXE, file upload, business logic, GraphQL, HTTP smuggling, cache poisoning, OAuth, OIDC, SSTI, subdomain takeover, cloud misconfig, ATO chains, agentic AI), LLM/AI security testing (ASI01-ASI10), A-to-B bug chaining, bypass tables, language-specific grep patterns, and reporting (7-Question Gate, 4 validation gates, CVSS 3.1, PoC generation, submission checklist). Use for ANY bug bounty task — recon, hunting specific vulns, auditing source code, testing AI features, validating findings, or writing reports.
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 OSINT methodology for external red-team operations and authorized attack-surface assessments. Covers the 5-stage recon pipeline (seed discovery, asset expansion, enrichment, exposure analysis, reporting), asset-graph discipline with 29 asset types, severity rubric (CRITICAL/HIGH/MEDIUM/LOW/INFO), confidence upgrade workflows, time budgeting, asset-level triage rules, scale-based tactics, identity-fabric mapping (Entra/Okta/ADFS/Google/SAML/M365 Teams+SharePoint+OAuth), API and auth-map methodology, JavaScript deep analysis, mobile attack surface, cloud attack surface, breach×identity correlation, detectability tagging, detection-aware probing (back-off, persona rotation), read-only validator discipline, WAF/CDN bypass + origin discovery, vulnerability prioritization (CVE/EPSS/KEV), phishing infrastructure planning + pretext development, bug bounty submission templates, client deliverable templates with risk translation, threat-actor investigation (incl. RU/CN pivots), cryptocurrency tracing, image/video forensics, chronolocation. Use when planning or executing reconnaissance against authorized targets, mapping an organization's external attack surface, investigating a person/entity, tracing crypto flows, geolocating media, or performing attribution 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。
Discover a single-page-app's hidden backend API from its public JS bundle, then test that API for broken access control / missing authentication. One of the highest-yield web plays in modern recon — SPAs ship their entire backend route map to the browser, and the API behind them is frequently missing the auth middleware the login page implies. Built from an authorized engagement where this play found an unauthenticated financial API that an ASM scan reporting hundreds of "Criticals" completely missed. Use whenever a target serves a JS-heavy SPA (React/Vue/Angular/Next), an "app"/"console"/"dashboard"/"portal" subdomain, or any `*api*` host shows up in recon. Leaked build artifacts (source maps / .env / .git / asset-manifest) are owned by hunt-source-leak; API version-inventory and behavioral diffing by hunt-shadow-api; this skill owns mapping a live SPA's backend routes from its JS bundle and testing them for broken access control / missing auth.
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。
Complete bug bounty workflow — recon (subdomain enumeration, asset discovery, fingerprinting, HackerOne scope, source code audit), pre-hunt learning (disclosed reports, tech stack research, mind maps, threat modeling), vulnerability hunting (IDOR, SSRF, XSS, auth bypass, CSRF, race conditions, SQLi, XXE, file upload, business logic, GraphQL, HTTP smuggling, cache poisoning, OAuth, timing side-channels, OIDC, SSTI, subdomain takeover, cloud misconfig, ATO chains, agentic AI), LLM/AI security testing (chatbot IDOR, prompt injection, indirect injection, ASCII smuggling, exfil channels, RCE via code tools, system prompt extraction, ASI01-ASI10), A-to-B bug chaining (IDOR→auth bypass, SSRF→cloud metadata, XSS→ATO, open redirect→OAuth theft, S3→bundle→secret→OAuth), bypass tables (SSRF IP bypass, open redirect bypass, file upload bypass), language-specific grep (JS prototype pollution, Python pickle, PHP type juggling, Go template.HTML, Ruby YAML.load, Rust unwrap), and reporting (7-Question Gate, 4 validation gates, human-tone writing, templates by vuln class, CVSS 3.1, PoC generation, always-rejected list, conditional chain table, submission checklist). Use for ANY bug bounty task — starting a new target, doing recon, hunting specific vulns, auditing source code, testing AI features, validating findings, or writing reports. 中文触发词：漏洞赏金、安全测试、渗透测试、漏洞挖掘、信息收集、子域名枚举、XSS测试、SQL注入、SSRF、安全审计、漏洞报告
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。
Router for NVIDIA NuRec/NRE: USDZ rendering, NCore conversion, 3DGS, gRPC sensor sim, carline adaptation, PhysicalAI HF datasets. Do NOT use for SimReady or infra setup.
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 "figure out where our direct traffic really comes from", "measure dark social", "add a how-did-you-hear-about-us field", or "show social drives signups without click data"; produces a share-link/UTM hygiene spec for owned share surfaces, a self-reported attribution field design that replaces an existing form field (free-text first, coded later), a GA4 direct-traffic decomposition read (deep-URL directs, mobile-app skew, private-push correlation) with every derived number hard-labeled Estimated/proxy, and a branded-search-lift proxy from GSC plus Wikipedia pageviews — the declared dark-social method behind ECHO O2. Not for paid-channel attribution reconciliation (platform-claimed vs analytics conversions) — use attribution-reconciler. 暗社交归因/直接流量分解/自报来源字段/分享链路UTM
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。