Generate structured weekly status reports covering initiatives, progress, blockers, risks, and KPIs.
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。
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概要と使いどころ
Generate structured weekly status reports covering initiatives, progress, blockers, risks, and KPIs.
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 session report with token usage estimates, work summary, and outcomes
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 SOC performance metrics and KPI tracking dashboards measuring Mean Time to Detect (MTTD), Mean Time to Respond (MTTR), alert quality ratios, analyst productivity, and detection coverage using SIEM data. Use when SOC leadership needs operational visibility, continuous improvement tracking, or executive-level reporting on security operations effectiveness.
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 dimension analysis and reporting for CJA. Use this skill whenever the user wants to analyze one or more dimensions — including cardinality, distribution/skew, trends, anomalies, data quality errors, comparisons, and forecasting. Also trigger when someone asks "what are the top values for...", "dimension health", "explore this dimension", "dimension dashboard", "dimension statistics", "data quality check on a dimension", "dimension cardinality", "dimension trends", "dimension skew", "dimension anomalies", "compare dimensions", or any similar request to understand what's inside a CJA dimension. Produces an interactive HTML dashboard or a markdown report. Works with the CJA MCP server.
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。
Companion to the generic report-writing skill. Use when working specifically on Bugcrowd submissions where VRT mapping, OOS-clause rebuttals, or per-program target selection matter.
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 ...
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 red team operations methodology covering full engagement lifecycle from planning through reporting. Addresses engagement scoping and rules of engagement negotiation, multi-tier C2 infrastructure design with redirectors and domain fronting, malleable traffic profiles and beacon tradecraft, OPSEC discipline including attribution avoidance and indicator management, EDR and AMSI evasion techniques using direct syscalls and unhooking, data collection with chain-of-custody controls, and structured reporting with purple team debrief workflows. Covers assumed-breach, external-to-internal, insider threat, and hybrid physical-cyber engagement scenarios with MITRE ATT&CK mapping throughout. Targets operators planning or executing adversary simulation engagements against mature defenders.
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。
Cross-cutting methodology for the CVE-hunting pipeline (ported from find-cve-agent): when a bug is design-vs-real, false-positive avoidance, version checking before reporting, responsible disclosure norms, acceptance-rate expectations per vuln class, vulnerability chaining playbook, known false-positive patterns, maintainer-response patterns, secure-pattern reference (what NOT to flag), and a self-criticism checklist to run before claiming a finding. Use this alongside the cve-hunter/cve-exploiter/cve-validator agents and the /cve-hunt pipeline — load it whenever judging if a finding is real, worth reporting, or already fixed.
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。
A set of resources to help me write all kinds of internal communications, using the formats that my company likes to use. Claude should use this skill whenever asked to write some sort of internal communications (status reports, leadership updates, 3P updates, company newsletters, FAQs, incident reports, project updates, etc.).
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。
Fast X Intelligence CLI (Rust) — search, analyze, and engage on X/Twitter from the terminal. Use when: (1) user says "x research", "search x for", "search twitter for", "what are people saying about", "what's twitter saying", "check x for", "x search", "search x", (2) user wants real-time monitoring with "watch", (3) user needs AI-powered analysis with Grok ("analyze", "sentiment"), (4) user needs intelligence reports ("report"), (5) user wants to track followers ("diff"), (6) user needs trending topics ("trends"). Also supports: bookmarks, likes, following (OAuth), x-search, collections, CSV/JSON/JSONL export. Non-goals: Not for posting tweets, not for DMs, not for enterprise features.
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。
A set of resources to help me write all kinds of internal communications, using the formats that my company likes to use. Claude should use this skill whenever asked to write some sort of internal communications (status reports, leadership updates, 3P updates, company newsletters, FAQs, incident reports, project updates, etc.).
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。
Conduct comprehensive AI-powered research with citations via the Tavily CLI. Use this skill when the user wants deep research, a detailed report, a comparison, market analysis, literature review, or says "research", "investigate", "analyze in depth", "compare X vs Y", "what does the market look like for", or needs multi-source synthesis with explicit citations. Returns a structured report grounded in web sources. Takes 30-120 seconds. For quick fact-finding, use tavily-search instead.
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。
Monday morning full pipeline review with metrics, channel performance, and forecast. Reads all CRM tabs, calculates deltas vs previous week, and generates actionable recommendations.
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。
Searches multiple web sources, synthesizes findings, and produces cited research reports using delegated subagents. Use when the user asks to research a topic online, search the web, look something up, find current information, compare options, or produce a research report.
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。
Plugin SDKのメソッドなどを参照する公開プラグイン数をClawHubで調べます。リリース時期や調査範囲の欠落も確認し、廃止や動作変更の影響判断を支援します。
運用者が設定したTeamサーバーの更新を、指定担当のNight Watchに引き継ぎ、既存の更新機構による検証・復旧・完了確認まで進めるスキル。
OpenClawのテストやプラグイン検証の遅さ・メモリ使用量を計測し、読み込みや起動処理の原因を調査。テストの検証範囲を保ちながら改善し、前後の数値を比較します。
ParallelsのmacOS仮想環境で、導入からDiscordへの送信、ホストの返信、ゲストでの読み取りまでを検証し、双方向通信の成否を確認するスキル。
GitHubのローカル保存データからIssueやPR、重複候補を調べ、同期状況や情報の不足を確認しながら、判断前に最新の状態を照合するスキル。
Notionのローカル保存データを検索し、ページやデータベースの一覧・件数・同期状況を確認して、必要に応じてMarkdownを書き出すスキル。
OpenClawの機能分類とQAの証拠を照合し、品質・機能の充足度・長期サポートの評価を見直して、成熟度のスコアカード文書を更新するスキルです。
OpenClawの課題やプルリクエストを、現在のソースとテスト結果に基づいて調査・レビューし、許可された範囲で修正からマージ完了の確認まで進めるスキル。
OpenClawのQAシナリオを模擬環境や実サービスで実行し、失敗原因の修正、結果レポートの確認、複数モデルの応答スタイル比較まで支援するスキル。
OpenClawのリリース候補を人が試すために、隔離コピーなどの検証環境を準備し、テストの進行とフィードバック整理を支援します。公開前の報告確認も扱います。