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概要と使いどころ
Due diligence checklists for A-share investments and M&A transactions. Adapted from the original dd-checklist skill for Chinese market due diligence requirements, regulatory filings, and business practices. Triggers on "A股尽调清单", "尽调清单", "due diligence China", "DD checklist A-share", "尽调checklist [company]", or "due diligence questions [company]".
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。
Draft anonymous one-page company teasers for A-share sell-side M&A processes. Creates compelling blind profiles without revealing the company's identity, adapted for Chinese market conventions. Triggers on "A股Teaser", "盲审材料", "blind profile China", "anonymous teaser A-share", or "sell-side teaser".
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。
Structure and draft Confidential Information Memorandums (CIMs) for A-share sell-side M&A processes. Organizes company information into professional, investor-ready documents with Chinese market context. Triggers on "A股CIM", "保密信息备忘录", "CIM China", "confidential memorandum A-share", or "offering memorandum [company]".
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。
Create one-page company profile slides (strip profiles) for A-share targets in pitch books and deal materials. Adapted from the original strip-profile skill for Chinese companies, A-share market data, and Chinese business terminology. Triggers on "A股公司简介", "公司概况", "strip profile China", "one-pager A-share", or "target profile for [company]".
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 variance commentary for A-share financial results. Adapts the original variance-commentary skill for Chinese financial statements, CAS conventions, and Chinese business terminology. Triggers on "A股业绩点评", "财报点评", "variance commentary China", "业绩分析", "variances [company]", or "commentary on [company] results".
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 professional data packs for A-share investment banking deals — M&A due diligence, IC materials, company profiles. Adapted from the original datapack-builder skill for Chinese data sources (AkShare, 巨潮, exchange filings) and CAS accounting. Triggers on "A股数据包", "投行数据包", "datapack China", "due diligence pack A-share", or "IC data pack [company]".
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。
Survey any codebase as a senior advisor and produce prioritized, self-contained implementation plans for OTHER models/agents to execute. Strictly read-only on source code — never implements, fixes, or refactors anything itself. Use when asked to audit a codebase, find improvement opportunities (bugs, security, performance, test coverage, tech debt, migrations, DX), suggest features or where to take the project next (roadmap, product direction), or generate handoff plans for another agent to implement.
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。
Drive Codeman, the session manager this agent is running inside, over its HTTP API, from any agent CLI (Claude Code, Codex, Gemini CLI, OpenCode, Antigravity, Grok Build, DeepSeek Harness, OMP): list sessions, start worker sessions in any installed CLI, send them prompts, block until they finish (wait / wait-output / send-and-wait), read their output, and clean up; where available, message claude workers directly (Claude Code cross-session messaging). Use when asked to orchestrate or parallelize work across Codeman sessions, get a second opinion from another CLI or model, watch another session, or start and manage workers. Only usable inside a Codeman-managed session (CODEMAN_MUX=1); refuse to act otherwise.
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 package encapsulate many functions to conduct a differential topology analysis. It focuses on analyzing an 'omic dataset with multiple conditions. While the package is mostly geared toward scRNASeq, it does not place any restriction on the actual input format.
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。
Universal LaTeX document skill: create, compile, and convert any document to professional PDF with PNG previews. Supports resumes, reports, cover letters, invoices, academic papers, theses/dissertations, academic CVs, presentations (Beamer), scientific posters, formal letters, exams/quizzes, books, cheat sheets, reference cards, exam formula sheets, fillable PDF forms (hyperref form fields), conditional content (etoolbox toggles), mail merge from CSV/JSON (Jinja2 templates), version diffing (latexdiff), charts (pgfplots + matplotlib), tables (booktabs + CSV import), images (TikZ), Mermaid diagrams, AI-generated images, watermarks, landscape pages, bibliography/citations (BibTeX/biblatex), multi-language/CJK (auto XeLaTeX), algorithms/pseudocode, colored boxes (tcolorbox), SI units (siunitx), Pandoc format conversion (Markdown/DOCX/HTML ↔ LaTeX), and PDF-to-LaTeX conversion of handwritten or printed documents (math, business, legal, general). Compile script supports pdflatex, xelatex, lualatex with auto-detection, latexmk backend, texfot log filtering, PDF/A output, and verbosity control (--verbose/--quiet). Empirically optimized scaling: single agent 1-10 pages, split 11-20, batch-7 pipeline 21+. Use when user asks to: (1) create a resume/CV/cover letter, (2) write a LaTeX document, (3) create PDF with tables/charts/images, (4) compile a .tex file, (5) make a report/invoice/presentation, (6) anything involving LaTeX or pdflatex, (7) convert/OCR a PDF to LaTeX, (8) convert handwritten notes, (9) create charts/graphs/diagrams, (10) create slides, (11) write a thesis or dissertation, (12) create an academic CV, (13) create a poster, (14) create an exam/quiz, (15) create a book, (16) convert between document formats (Markdown, DOCX, HTML to/from LaTeX), (17) generate Mermaid diagrams for LaTeX, (18) create a formal business letter, (19) create a cheat sheet or reference card, (20) create an exam formula sheet or crib sheet, (21) condense lecture notes/PDFs into a cheat sheet, (22) create a fillable PDF form with text fields/checkboxes/dropdowns, (23) create a document with conditional content/toggles (show/hide sections), (24) generate batch/mail-merge documents from CSV/JSON data, (25) create a version diff PDF (latexdiff) highlighting changes between documents, (26) create a homework or assignment submission with problems and solutions, (27) create a lab report with data tables, graphs, and error analysis, (28) encrypt or password-protect a PDF, (29) merge multiple PDFs into one, (30) optimize/compress a PDF for web or email, (31) lint or check a LaTeX document for common issues, (32) count words in a LaTeX document, (33) analyze document statistics (figures, tables, citations), (34) fetch BibTeX from a DOI, (35) convert a Graphviz .dot file to PDF/PNG, (36) convert a PlantUML .puml file to PDF/PNG, (37) create a one-pager/fact sheet/executive summary, (38) create a datasheet or product specification sheet, (39) extract pages from a PDF (page ranges, odd/even), (40) check LaTeX package availability before compiling, (41) analyze citations and cross-reference with .bib files, (42) debug LaTeX compilation errors, (43) make a document accessible (PDF/A, tagged PDF), (44) create lecture notes or course handouts, (45) fill an existing PDF form (fillable fields or non-fillable with annotations), (46) extract text or tables from a PDF (pdfplumber, pypdf), (47) OCR a scanned PDF to text (pytesseract), (48) create a PDF programmatically with reportlab (Canvas, Platypus), (49) rotate or crop PDF pages (pypdf), (50) add a watermark to an existing PDF, (51) extract metadata from a PDF (title, author, subject).
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。
Browser automation CLI for AI agents. Use when the user needs to interact with websites, including navigating pages, filling forms, clicking buttons, taking screenshots, extracting data, testing web apps, or automating any browser task. Triggers include requests to "open a website", "fill out a form", "click a button", "take a screenshot", "scrape data from a page", "test this web app", "login to a site", "automate browser actions", or any task requiring programmatic web interaction.
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。
Autonomous cold email campaign launcher. Takes one target company domain, scrapes their website, generates an ICP with Claude, pulls matching leads via Prospeo, enriches emails + company descriptions, personalizes each lead with parallel Claude Code Task sub-agents (A/B/C variants), and uploads as a live Smartlead campaign. Uses local JSON files for state (no database required). Use for automated daily campaign launches after you have an initial `client-profile.yaml` from /icp-onboarding. Triggers on "auto-research", "launch an automated campaign", "daily campaign", "run the research loop".
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 the Blitz API to find decision-makers at specific companies when you already have a list of company domains. Best for SMB owner-finding, domain-to-people lookup, or supplementing Prospeo results. Outputs a CSV you can feed to the /list-builder Phase 5 or directly to /cold-email-starter-kit for Smartlead upload. Use when your targeting is company-first (not title-first).
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。
The 3-bullet creative ideas email. Produces three per-company bullets that each sit in a slot the operator defined up front, so the model fills in the company detail and never invents a new idea. Triggers on "creative ideas campaign", "three ideas email", "I had a few ideas for you", "3 bullets", "use cases for their business", "what could they build with us". Outputs creative_idea_1, creative_idea_2, creative_idea_3 plus a rendered bullet block.
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。
Expand a hard-to-build niche list from ~10 known-good seed companies into a full qualified TAM. Seed fingerprinting (how do good-fit companies ACTUALLY show up in the company database's filters) → lookalike generation (Prospeo company_lookalike, Exa findSimilar, Parallel.ai entity search) → filter mining with a precision/volume scorecard → wide pull with auto-sharding → cheap-AI qualification → live-website verification → client transparency report. Use when a vertical list feels "too small" (medical groups, hedge funds, Medicare brokerages), when known good-fit companies don't show up in keyword searches, or when someone says "expand this list", "the TAM should be bigger", "find more companies like these".
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。
Writes the one sentence that makes a generic offer feel written for this one company. Produces the tail of "I think we can help you ___". Triggers on "specificity line", "make it feel specific to them", "the specifically sentence", "why would they think this is for them", "personalize the offer not the intro". Outputs one lead-level merge field, blank when the company does not fit.
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。
Names 2 other right-fit people at the prospect's own company so an email can ask "is this you or them?" without ever naming the person being emailed. Triggers on "name two other people at the company", "who else works there", "should I be talking to someone else", "colleague name variable", "other prospects line", "wrong person CTA". Outputs other_prospects, a ready-to-drop phrase like "Jeff Barg or Rob Cook".
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。
Interactive loop that builds and tunes an AI prompt for evaluating whether a company fits a client's ICP. Run after any list-building skill (disco-like, blitz-list-builder, google-maps-list-builder, prospeo-full-export) to qualify companies before scaling. Iterates batches of 10 companies with user feedback, stops when 2 consecutive rounds have zero corrections, saves the final prompt for reuse. Always uses Claude Code Task sub-agents — never an external API key.
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。
META skill — build the largest possible qualified lead list for any request, end to end. Orchestrates discovery (Prospeo + GetLeads + Blitz + Google Maps + lookalike snowball from /list-expander), AI qualification with live-website verify, uncapped contact pull (GetLeads → Blitz → Prospeo), and provider emails (GetLeads/Blitz/Prospeo) validated with MillionVerifier before sending. Use for any "build me a list", "get me leads for X", "find everyone who...", client list request, or campaign list build. Starts with a 7-line intake brief; outputs to Postgres, Google Sheet, and/or CSV (asks which).
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。
Always-on spam and deliverability guardrails for cold email copy. Apply these rules whenever writing, reviewing, or QA-ing subject lines, openers, follow-ups, CTAs, or any cold outreach copy. Trigger on phrases like "check this for spam", "spam word check", "deliverability review", "QA this copy", "flag banned words", "check subject line", "is this safe to send", "scan for spam triggers", or any time cold email copy is being generated or reviewed. Also trigger automatically as a background rule whenever the campaign-copywriting or cold-email-copywriting skill is active -- these guardrails apply to EVERY piece of outbound copy generated, even if the user does not explicitly ask for a check.
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。
Amazon keyword research and market opportunity analysis for sellers. Retrieve autocomplete suggestions (long-tail keywords), analyze competitor landscape, and assess market opportunity for any keyword on 12 Amazon marketplaces (US/UK/DE/FR/IT/ES/JP/CA/AU/IN/MX/BR). No API key required. Make sure to use this skill whenever the user mentions Amazon product research, finding products to sell on Amazon, Amazon keyword ideas, niche analysis, competition analysis for Amazon, market opportunity on Amazon, comparing Amazon keywords, evaluating whether a product is worth selling, Amazon autocomplete data, seasonal demand for Amazon products, or anything related to researching what to sell on Amazon — even if they don't explicitly say 'keyword research'. Also trigger when the user asks vague questions like 'is this a good product to sell?', 'what's the competition like for X on Amazon?', 'should I sell X or Y?', or 'what are people searching for on Amazon?'.
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 starting any conversation in a loopkit-enabled project - establishes how to find and use loopkit's 49 skills, requiring skill invocation before ANY response including clarifying questions.
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。
Catch hardcoded secrets, keys, and tokens before they get committed. Use before any commit and on any file with credentials.
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。
Full brand naming workflow for founders, agencies, and businesses. Use this skill whenever the user says "help me name this brand", "brand naming", "I need a name for", "name ideas for", "what should I call my brand/company/product", "naming a startup", "brand name suggestions", "help with naming", or shares a brand brief and asks for name options. Also triggers when the user shares existing name options and asks for feedback, evaluation, ranking, or scoring of those names. Auto-detects whether to run the full generation workflow or the evaluation workflow based on what the user provides. Always use this skill for any brand or product naming task — even if the user just casually mentions needing a 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。