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概要と使いどころ
- 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。
- Find leaked or mentioned selectors circulating in pastes, leak forums, Telegram channels and dump markets, and judge whether a claimed leak is genuine or a recycled combolist. Use when checking whether a name, email, domain or credential is circulating, verifying a breach claim made against your organisation, or setting up ongoing leak monitoring
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。
Check a Facebook wall for authored posts that have no teaser yet and draft the teasers for short-form channels. Runs as a daily routine or on demand, and stays draft-first. Triggers: "/fb-watch", "check facebook for un-teased posts", "catch up on teasers".
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。
Have the second brain ask the owner five hard questions about their own long-held beliefs and codex entries that have not been revisited, so assumptions stop fossilizing. Monthly or on demand. Triggers: "/five-hard", "challenge my beliefs", "pressure-test my views".
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 existing brand DNA, keywords.csv, and prompts.csv, then produces a plan.csv — a strictly-schema'd content architecture telling the next pipeline step which pages to create, for which keyword/prompt clusters, and in what build order.
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。
Researches what prompts people ask AI engines (ChatGPT, Gemini, Perplexity, Claude) about a product category and produces a prompts.csv artifact — a prioritized, strictly-schema'd list of the queries where the brand should be cited. Feeds the monitor workflow.
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。
- Craft advanced search-engine queries and Google dorks to surface hidden files, documents and mentions. Use when building a Google dork, hunting a leaked document, or searching paste sites and document repositories for a name, email or selector
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。
Find a person, lead, contact or company by name in any spelling: a deterministic search that catches transliteration across alphabets, wrong-keyboard-layout typing and typos. This is the exact-name lane (zero tokens), complementary to semantic vault search. Triggers: "/find <name>", "show everyone named <X>".
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。
Ask the second brain in plain words: semantic search over the curated vault with embeddings plus a reranker, returning the smallest relevant slice instead of a corpus dump. Token-cheap. Triggers: "/ask <question>", "what do I have on <topic>", "what did I write about X".
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 bold, value-adding follow-up when your own outbound message got silence: check the thread, pick a second channel, add new value instead of a bare bump. Use when an email, DM or PR comment went unanswered. Triggers: /bold-followup, /bump, follow up on silence, second channel.
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。
Pull fresh ChatGPT conversations into an Obsidian vault on demand, the manual twin of the nightly job. Incremental and idempotent by conversation id: never clobbers enriched notes, never duplicates. Triggers: "/chatgpt-sync", "pull chatgpt", "sync chatgpt chats".
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。
Rewrite machine-written text so it reads like a busy human wrote it: cut 50-70%, break the even rhythm, drop AI-tell words and filler, keep facts and protected terms. Use before publishing any post, reply or email drafted by a model. Triggers: /ai-slop, /slop, humanize, anti-slop, make it shorter and alive.
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。
This skill should be used when creating RFQ (Request for Quotation) documents for software development projects to send to vendors. Use this skill when you have received vague requirements from clients and need to structure them into clear, comprehensive RFQs that enable vendors to provide accurate estimates. Supports Japanese (default) and English, with systematic requirements elicitation, clarification, and markdown-formatted output.
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。
This skill should be used when creating cost estimates and quotations for software development projects. Use this skill when you have an RFQ (Request for Quotation), project requirements, or a project description and need to create a comprehensive estimate with WBS, effort calculations, cost breakdowns, and ROI analysis. Supports Japanese (default) and English, with systematic work breakdown, effort estimation, and markdown-formatted estimate documents.
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。
Track vendor support tickets and RMA cases across multiple vendors. Use when managing support ticket lifecycle, updating ticket status from vendor emails, generating status reports, or identifying tickets needing follow-up.
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。
Unified document optimization skill that chains docling-converter, imagemagick-expert, and markdown-to-pdf. Automatically detects input format, applies appropriate conversion pipeline, optimizes embedded images, and produces web/print-ready output with configurable quality presets. Use when converting documents through multi-step pipelines, optimizing PDF images, creating print-ready documents from various sources, or batch processing documents with image optimization.
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。
Professional contract review skill for business agreements including NDAs, MSAs, SLAs, SOWs, and software license agreements. Provides systematic clause-by-clause analysis, risk assessment with quantified scoring, red flag detection, and negotiation guidance. Use this skill when reviewing vendor contracts, partnership agreements, service agreements, or any business contract requiring risk evaluation and negotiation preparation. Triggers include "review this contract", "analyze this NDA", "check this agreement for risks", "prepare for contract negotiation", or when evaluating terms and conditions.
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 designing, implementing, reviewing, debugging, testing, profiling, or porting concurrent, parallel, distributed, high-performance, network dataplane, kernel-bypass, or real-time software, including locks, semaphores, monitors, MPI, CSP rendezvous, DPDK, VPP, eBPF, XDP, AF_XDP, SR-IOV, RSS, RoCEv2/RDMA, RMS/EDF, priority inversion, and environment selection from silicon to edge.
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 evaluating, designing, drafting, revising, stress-testing, or preparing academic articles, empirical research reports, literature reviews, systematic reviews, meta-analyses, journal submissions, reviewer responses, research methods, sampling, measurement, analysis, publication readiness, or citation/source audits.
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。
Architecture design and governance protocol for system structure, boundaries, contracts, APIs, schemas, migrations, rewrites, and long-lived codebase health. Use when designing or reviewing architecture, planning structural refactors or migrations, governing tech debt, or containing rewrite risk. Keeps the load-bearing spine small, owned, checked, and deletable over time.
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。
Author or expand browser-agent benchmark tasks in data/real_world_bench.json (Odysseys schema, per-rubric graded). Use when creating, adding, or expanding real-world browser tasks, writing rubrics, or picking bot-friendly sites — every task MUST be verified runnable through ego-browser before it is written.
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。
Add or improve canonical data catalog collections, fields, aliases, relations, evidence tags, docs, and tests.
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。
Load when configuring GitBook documentation sites, authoring GitBook-flavored markdown pages and custom blocks, integrating OpenAPI/Swagger specs, driving GitBook Change Request workflows (create, review, comment, resolve), or building GitBook platform integrations. Do not use for general repository code reviews, general .NET OpenAPI schema generation, or non-GitBook markdown.
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。
Load for EF Core entities/configurations, semantic value persistence, portable constraints, DbContext/query filters, repositories/specifications, migrations, model snapshots, transactions, or seeded lookup tables; use query-optimization specifically for N+1 or slow SQL diagnosis.
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。