「open source」の検索結果

Research venture capital firms, angel investors, and funding sources for startup fundraising. Use when: "投资人调研", "找VC", "research investors", "VC list", "funding sources", "investor database", "天使投资人", "venture capital", "融资对象", "投资人画像". Generates a structured investor research report with firm profiles, investment thesis, portfolio companies, contact strategies, and warm introduction paths. Part of UniqueClub founder toolkit. Learn more: https://uniqueclub.ai Pairs with pitch-deck-creator for complete fundraising preparation.

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 exhaustive multi-source investigation with methodology tracking, source evaluation, and iterative depth.

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。

Design Azure infrastructure using natural language, or analyze existing Azure resources to auto-generate architecture diagrams, refine them through conversation, and deploy with Bicep. When to use this skill: - "Create X on Azure", "Set up a RAG architecture" (new design) - "Analyze my current Azure infrastructure", "Draw a diagram for rg-xxx" (existing analysis) - "Foundry is slow", "I want to reduce costs", "Strengthen security" (natural language modification) - Azure resource deployment, Bicep template generation, IaC code generation - Microsoft Foundry, AI Search, OpenAI, Fabric, ADLS Gen2, Databricks, and all Azure services

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。

Conducts external reconnaissance using Open Source Intelligence (OSINT) techniques to map an organization's external attack surface without directly interacting with target systems. The tester gathers information from public sources including DNS records, certificate transparency logs, search engines, social media, code repositories, and data breach databases to build a comprehensive target profile. Activates for requests involving OSINT reconnaissance, external footprinting, attack surface mapping, or passive information gathering.

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。

Review and fix OpenMetadata connector documentation against JSON schema and source code. Validates availableFeatures, permissions, yaml.mdx configuration, and overall completeness. Automatically fixes gaps.

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 full documentation for a new OpenMetadata connector from scratch — generates main page, yaml.mdx, troubleshooting page, and registers in docs.json navigation. Derives features, permissions, and YAML config from JSON schema and source code.

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 review of a PR, a file, or pasted text against the OpenMetadata Writing Style Guide checklist, plus checking every checkable claim for internal consistency against the diff/PR itself. One combined report, not separate passes. Does not fetch or verify against any external source repository. Link-checking is out of scope; a separate broken-links job covers that. Only runs on explicit /content-review invocation, never self-triggered.

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。

Expert in Langfuse - the open-source LLM observability platform. Covers tracing, prompt management, evaluation, datasets, and integration with LangChain, LlamaIndex, and OpenAI. Essential for debugging, monitoring, and improving LLM applications in production. Use when: langfuse, llm observability, llm tracing, prompt management, llm evaluation.

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 AI agents that interact with computers like humans do - viewing screens, moving cursors, clicking buttons, and typing text. Covers Anthropic's Computer Use, OpenAI's Operator/CUA, and open-source alternatives. Critical focus on sandboxing, security, and handling the unique challenges of vision-based control. Use when: computer use, desktop automation agent, screen control AI, vision-based agent, GUI automation.

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。

Intelligent search for agents. Multi-source retrieval with confidence scoring - web, academic, and Tavily in one unified API.

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。

Perform AI-powered web searches with real-time information using Perplexity models via LiteLLM and OpenRouter. This skill should be used when conducting web searches for current information, finding recent scientific literature, getting grounded answers with source citations, or accessing information beyond the model knowledge cutoff. Provides access to multiple Perplexity models including Sonar Pro, Sonar Pro Search (advanced agentic search), and Sonar Reasoning Pro through a single OpenRouter 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。

SF SymbolsやIconify APIからiOS・macOS向けのアイコンを選び、既存の配色やサイズに合わせてXcode用のPNG素材一式を生成するスキル。

• Xcode用のアイコン素材を作りたいとき
• 既存のデザインに合うアイコン探し
• 仮置きのアイコンを差し替えたいとき

GitHubの公開ソフトウェアに不正な変更がないか、履歴やアーカイブを照合して調査します。削除された情報の回収を試み、侵害の手がかりと根拠付きの報告書をまとめます。

• 不審なコミットやビルド手順の調査
• 履歴から消えたコミットの回収調査
• 認証情報の漏えい経緯を調べたいとき

将来のキャッシュフローを現在価値に換算し、企業価値と1株当たりの評価額を算出するExcelを作成します。前提を変えた再計算やシナリオ比較、感度分析も扱います。

• 企業評価用のExcelを作りたいとき
• 弱気・基本・強気のシナリオ比較
• 前提変更による評価額の変化確認

類似企業の売上・利益率・評価倍率を比較するExcelを作成します。計算式、中央値や四分位、データの出典をまとめ、投資や買収の検討に使う比較資料を整えます。

• 同業他社との企業価値比較
• 買収検討用の比較資料作成
• 業界の成長性・収益性比較

企業買収が一株当たり利益に与える影響をExcelで試算するスキル。買収価格、資金調達、相乗効果の前提を整理し、条件別の比較表と説明用の要約を作成します。

• 買収による一株当たり利益の試算
• 現金・株式の支払い条件の比較
• 買収価格と相乗効果の条件別比較

Use this skill any time a spreadsheet file is the primary input or output. This means any task where the user wants to: open, read, edit, or fix an existing .xlsx, .xlsm, .xltx, .csv, or .tsv file (e.g., adding columns, computing formulas, formatting, charting, cleaning messy data); create a new spreadsheet from scratch or from other data sources; or convert between tabular file formats. Trigger especially when the user references a spreadsheet file by name or path — even casually (like "the xlsx in my downloads") — and wants something done to it or produced from it. Also trigger for cleaning or restructuring messy tabular data files (malformed rows, misplaced headers, junk data) into proper spreadsheets. The deliverable must be a spreadsheet file. Do NOT trigger when the primary deliverable is a Word document, HTML report, standalone Python script, database pipeline, or Google Sheets API integration, even if tabular data is involved.

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 or update a Codex skill with appropriately scoped instructions and any needed supporting resources.

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。

Audit cloned or reimplemented websites for fidelity gaps, tracking scripts, source-brand and language residue, placeholders, and risky external dependencies. Use before handoff or deployment, or when asked to review a website clone for cleanup and readiness.

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。

Extract design tokens (color / typography / spacing) from imported source code, screenshots, or Figma exports into the canonical token bag token-map consumes.

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 humanities lecture: how Renaissance linear perspective reshaped early cartography — sources, argument, and evidence. Built as a decision-grade academic research deck for faculty, graduate seminar.

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。

YouTube clip generation and editing with automated workflows — pull source video, slice highlights, add captions, and export.

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。

Audit a python-pptx export against its source HTML deck, identify layout/content drift (footer overflow, cropped content, missing italic/em, lost styling, off-rhythm spacing), and re-export with strict footer-rail + cursor-flow layout discipline. Use this skill whenever the user has a .pptx that was generated from an HTML slide deck and asks to compare/audit/verify/fix the export — including phrases like "compare ppt with html", "fidelity audit", "fix the pptx", "ppt is cut off", "footer overlap", "italic missing in pptx", "re-export the deck", "pptx-html-fidelity-audit", or any case where a python-pptx → HTML round-trip needs verification or repair. Also trigger when the user shows you a deck.html and a deck.pptx side by side and is debugging visual differences.

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。