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概要と使いどころ
Load a skill profile to switch active plugin set. Use when user wants to focus on a specific workflow (web-app/data-eng/harness-dev/minimal) and reduce skill enumeration block size per
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。
Guide setup for and verify a reviewed, read-only Grafana Observability profile and its activated capability packs. Use when a user asks to set up Grafana access, verify profile readiness, discover available infrastructure, APM, log, IoT or business KPI packs, or troubleshoot why a Grafana pack cannot run.
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。
Operations, debugging, and optimization for DAG workflows. Performs root cause analysis on failures, profiles execution performance, aggregates results from parallel branches, bridges context between nodes, and learns patterns from execution history. Activate on "DAG failed", "why did it fail", "root cause", "performance profile", "aggregate results", "merge branches", "execution patterns", "optimize DAG". NOT for planning DAGs (use dag-planner), executing DAGs (use dag-runtime), or validating outputs (use dag-quality).
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。
Visualizes ChIP-seq data using deepTools (computeMatrix, plotHeatmap, plotProfile, bamCoverage, bamCompare), pyGenomeTracks (modern INI-driven track plots), Gviz (R browser-style), EnrichedHeatmap (ComplexHeatmap-based), ChIPseeker tag heatmaps, and IGV batch screenshots. Handles bigWig normalization choices (CPM, BPM, RPGC, spike-in scaled), bamCompare operations (log2 ratio, subtract) with SES scaling, k-means clustering of heatmaps for biological subgrouping, and spike-in-scaled tracks for global-shift experiments. Use when generating publication-quality ChIP-seq signal heatmaps, profile plots, genome-browser tracks, or comparing samples visually.
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。
Bilingual JD/CV/Resume tailoring and resume polish skill for job applications. Use when the user provides a job description, JD, role posting, existing CV/resume, LinkedIn profile, portfolio, or career notes and wants to optimize, rewrite, polish, or customize a resume/CV for ATS keywords, recruiter screening, interview-ready evidence, and role fit. 适用于根据招聘 JD、岗位描述、目标公司、现有简历/CV/LinkedIn/profile 进行简历优化、简历润色、岗位匹配、ATS 关键词映射、经历深挖、项目证据提炼和中英文求职简历定制。
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。
Learns a user's personal writing and speaking style through interactive writing prompts, then generates a reusable voice profile. Use when the user says "learn my writing style," "write like me," "capture my voice," "voice calibration," "mimic my tone," "my writing style," or wants AI to match their personal communication style. Also activates when a .voice-profile.md file exists and the user asks you to write something in their voice.
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 GenAI and agentic apps with genai-tk (tclatos/genai-tk), a YAML-driven IoC toolkit over LangChain, DeepAgents, DeerFlow, and Prefect. Use this skill whenever the user mentions genai-tk, genai_tk, `cli init`, `cli agents run`, `LangchainAgent`, `create_harness`, `get_llm`, `global_config()`, `model_id@provider`, `agents:`/`agent_defaults:` profiles, `RetrieverFactory`, `cli workflow`, or BAML extraction. Also trigger for app_conf.yaml, GENAITK_PROFILE, CodeAct, OpenSandbox, decision models, or "the toolkit".
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。
Systematically find and fix performance problems in applications, frontend and backend, by measuring first. Use this skill whenever the user reports slow endpoints, high latency, poor throughput, memory leaks, large bundles, or slow page loads; wants to profile with cProfile, py-spy, Chrome DevTools, Node --cpu-prof, or perf; run load tests with locust or k6; set performance budgets or SLOs; optimize database queries (EXPLAIN, indexes, N+1); add caching (Redis); improve frontend performance (code splitting, lazy loading, image optimization, memoization, virtualization); or tune the network (CDNs, gzip/br, HTTP/2/3). Also trigger for p50/p95/p99 latency, throughput, error rate, connection pooling, async vs threads, GIL, and memory leak investigations.
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。
Analyzes a dataset of companies or profiles to identify market patterns. Use when the user provides a larger dataset and wants segments, dominant categories, gaps, and emerging 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。
Evaluates potential channel, integration, affiliate, or strategic partners. Use when the user provides partner profiles plus partnership goals and wants fit scoring, partnership type, and outreach priority.
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。
Identifies likely duplicate profiles or companies using available record evidence. Use when the user provides a list and wants duplicate groups, match confidence, and merge recommendations. Describe records as likely duplicates unless there is an exact deterministic match.
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。
Qualifies and scores B2B prospects against a supplied ideal customer profile. Use when the user provides a lead list, company records, prospect data, or qualification criteria and wants prioritization, fit analysis, or disqualification reasons.
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 Lingzao creator-content tools for Xiaohongshu/XHS, Douyin, and WeChat official-account public content. Lingzao supports XHS SEO, Xiaohongshu account analysis, benchmark account discovery, viral note breakdown, keyword research, one-stop content packages from keyword/link/image/inspiration material, title and cover optimization, hand-drawn route-map cards, city food maps, travel itinerary maps, life checklist maps, workflow manual maps, creator content workflow, note search, creator search, profile lookup, recent posts, deep profile copy/subtitle analysis, note/article detail, post comments, article stats, related articles, short-video copy extraction, and prompt-based creator image generation.
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 comprehensive threat actor profiles using open-source intelligence (OSINT) techniques to document adversary motivations, capabilities, infrastructure, and TTPs for proactive defense.
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 and analyze Cobalt Strike Malleable C2 profiles using dissect.cobaltstrike and pyMalleableC2 to extract C2 indicators, detect evasion techniques, and generate network detection signatures.
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。
Web サーバ（nginx/apache、Linux 中心）の Phase 1 設定セキュリティレビュー。 target_profile.yaml で対象を確定し、MANIFEST.txt + manifest_attestation.txt で証跡 integrity を検証。 SSH 直接または証跡受領モードで 9 観点 (OS/リソース/ログ/ネットワーク/サービス/認証/監視/バックアップ/証明書) を read-only 走査。6 階層ガード (allowed/conditional/conditional_sensitive/ask-first/exceptional_sensitive_read/forbidden)、 3 軸補助 (Exploitability/Blast Radius/Service Criticality) の重大度判定、 observation_status による未確認の独立管理、evidence_dir/raw_evidence_store 分離、自己レビュー必須。 Windows/IIS は v1 hard fail。 Use when: Web サーバの設定セキュリティレビュー、Phase 1 監査、nginx/apache 構成監査、 EOL ランタイム調査、ログローテーション不備調査、ドキュメントルート漏えい調査。
Use when capturing or restoring a learner's persistent profile to personalize teaching across sessions.
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。
TDD 세션이 끝난 뒤 "어디서 시간·토큰이 많이 들었나"를 단계(Skill)·에이전트별로 집계하고 병목과 model/effort 조정안을 보고한다. 세션 transcript를 읽는 사후 분석이며 코드를 바꾸지 않는다. "이번 TDD 세션 병목 분석", "토큰 어디에 썼어", "어느 단계가 느렸어", "모델 조정 제안", "/tdd-profile" 요청 시 사용.
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。
Reads one spreadsheet, CSV export or pasted table together with the user's question and drafts an insight pack: a data profile, observations cited to named columns and values and framed as leads, caveats, and suggested charts and follow-up analyses. Every figure carries the label "as read, verify in source"; correlation is never stated as causation. Use when the user asks to "profile this spreadsheet", "what does this data say", "find anomalies in this extract", "give me a first read on this CSV" or "summarise this table". Do not use for a purchase order log or spend extract, use purchase-order-anomaly-review instead; for actuals versus budget, use budget-variance-explainer instead; for a report that arrives by email on a schedule, use report-attachment-analyzer instead. 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。
- Deep-dive a subject's social media presence — profile metadata, follower and mutual network, content analysis, and posting-time pattern of life across Instagram, Facebook, X/Twitter, TikTok, LinkedIn, Reddit, Telegram and… Use when profiling a social account, mapping someone's associates, inferring a subject's timezone or routine from their posts, or archiving a profile before it is deleted
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。
Sweep every external pointer to you (profiles, READMEs, bios, link pages) after a rename of a repo, org, domain, handle or account, and fix the dead ones. Use right after any public rename and once a quarter as hygiene. Triggers: /link-rot, /lr, check links, broken profile links, after the rename, link rot.
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。
- Investigator OPSEC — threat-model who might notice you, control your attribution surface across IP, ASN, browser and TLS fingerprint, timing and logged-in accounts, separate research identity from… Use when setting up a research account, avoiding tipping off a subject, worrying about LinkedIn profile-view leakage, needing a burner phone or email, or hardening a research VM or browser profile
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 a dossier on a person: recall everything the vault already knows, map their public profiles by web research, emit a deep-research prompt for external tools, and persist a well-linked person card. Triggers: "/portret <name>", "dossier on <name>", "profile <name>".
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 a sourced, corroborated profile of a named individual from public records, social platforms, professional networks, court and property filings, licensing boards, patents, papers and obituaries — anchoring the name to a… Use when asked to find, identify, background-check or profile a person, verify someone's claimed employment or credentials, or locate a missing or hard-to-reach individual
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。