Coordinates multi-investor rounds with allocation, lead/follow dynamics, and information rights structuring. Use when syndicating rounds, managing co-investor relationships, or structuring investor groups.
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Coordinates multi-investor rounds with allocation, lead/follow dynamics, and information rights structuring. Use when syndicating rounds, managing co-investor relationships, or structuring investor groups.
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。
Creates sell-side CIMs with business description, financial overview, growth drivers, and investment highlights. Use when preparing sell-side marketing materials, writing CIMs, or positioning companies for sale.
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 market structure dynamics with order book analysis, spread decomposition, and information asymmetry assessment. Use when analyzing market structure, evaluating trading venues, or assessing execution 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。
Evaluates alternative trading systems with fill rate analysis, information leakage assessment, and venue toxicity measurement. Use when analyzing dark pools, evaluating ATS venues, or assessing execution venue 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。
Use when you need to auto-log all tool interactions into a self-organizing vector DB with instant recall. Intercepts interactions, extracts key information, generates embeddings, stores in LanceDB, auto-categorizes, and builds a retrieval index. Inspired by OpenClaw SQLite LCM + summary DAG pattern.
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。
Start and manage the full heartbeat ecosystem for agent-studio. Registers all 7 heartbeat loops plus auto-reschedule task via CronCreate to keep the agent ecosystem healthy, indexed, informed, and connected.
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Find the most valuable commercial insight and the monetization point closest to lawful revenue for a project, product, service, website, community, content account, open-source tool, or business idea. Use when a user asks how to monetize, who pays, why people do not buy, what to charge, whether to keep building, what to stop, what to do next, or asks to continue or deepen an earlier business analysis. Answer the user's actual question before asking for more information and carry the analysis forward without repeating it. When the buyer, purchased result, or delivery ability is unknown, do not select them from industry stereotypes; use explicit conditional candidates and an evidence-gathering next step. Not for investment advice, income forecasts, get-rich-quick schemes, or guaranteed 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。
Evaluate an interface from a UX perspective, assessing hierarchy, information architecture, emotional resonance, cognitive load, and overall quality with quantitative scoring and actionable feedback. Use when the user wants an overall design or UX review—not when the main need is measurable accessibility/performance diagnosis, or final micro-detail polish.
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。
Scaffold a new iOS app with SDLC and submission-safe defaults — diffable project files, app + test targets, deployment-target policy, a git-stamped build number, and the Info.plist keys the pre-flight checker wants so the project passes TestFlight from day one. Use when starting a new iOS project.
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 research with cross-verification and source tiering. Use when investigating technologies, comparing tools, fact-checking claims, evaluating architectures, or any task requiring verified information. Triggers on "조사해줘", "리서치", "research", "investigate", "fact-check", "비교 분석", "검증해줘".
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。
Automates browser interactions for web testing, form filling, screenshots, and data extraction. Use when the user needs to navigate websites, interact with web pages, fill forms, take screenshots, test web applications, or extract information from web pages.
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 web and social media search across 5 providers (Brave, Tavily, Xpoz, Exa, Firecrawl). Auto-routes queries to the best API, supports parallel multi-provider search with deduplication, AI-generated answers, and social media search. Triggers on web search, find news, search Twitter, search Reddit, social media search, multi-provider search, omnisearch, research news, OSINT, search for, look up, find information about.
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 and edit high-quality images using Google's Nano Banana Pro (Gemini 3 Pro Image) AI model. Use this skill when working with AI image generation or editing tasks including (1) Creating images from text prompts with professional quality, (2) Editing existing images with natural language instructions, (3) Multi-turn iterative image refinement, (4) Product photography and marketing visuals, (5) Creating infographics and diagrams with text, (6) Photorealistic and artistic image generation, (7) Batch image generation workflows, (8) Testing and troubleshooting Gemini image generation API. Supports up to 4K resolution, multiple aspect ratios, reference images, and advanced prompting techniques for cinema-quality 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 evidence-labeled semantic cores for SEO, LLM-readable architecture, and site information design. Use this skill when the user asks for semantic core, query clusters, search intents, audience segments, entity/topic maps, language or locale priorities, competitor/source evidence, pillar-topic planning, or a structured handoff before URL architecture and internal linking. It must mark unknown search volume, difficulty, and ranking data as unknown instead of inventing metrics.
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 intentional internal link graphs for SEO, UX, and LLM-readable sites. Use this skill when the user asks for links between short briefs, longform articles, topics, projects, author pages, breadcrumbs, source trails, related stories, orphan-page checks, overlink checks, anchor intent, or validation that a link graph reinforces the canonical content model without creating duplicate story bodies or hidden links.
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 a design needs pressure-testing for UX, information architecture, states, and accessibility.
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。
Audits and scores Claude Projects using a six-dimension Scorecard with anchored 1-5 rubrics and detects seven structural anti-patterns. When global layer info is provided, adds cross-layer alignment findings. Use when user says "audit my project," "review my custom instructions," "score my project," "evaluate my Claude project," "improve my system prompt," "what's wrong with my project," "why is my project underperforming." Also trigger on symptom-phrased: "my project doesn't work right," "Claude is inconsistent in my project," "my Project used to work and now doesn't." Also use when the user pastes Custom Instructions asking why output is poor or generic. Do NOT use when the user's primary request is a global-layer audit (use rootnode-global-audit if available), single-prompt evaluation (use rootnode-prompt-validation if available), or Memory-only optimization (use rootnode-memory-optimization if available). Run on Opus 5 or Sonnet 5 at `high` effort (both defaults); depth reduces on legacy models.
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。
Cheminformatics toolkit for fine-grained molecular control. Parse and write SMILES, SDF, MOL and InChI; compute descriptors (MW, LogP, TPSA, QED, Bertz); build fingerprints (Morgan/ECFP, RDKit, MACCS, atom pair, torsion) and score Tanimoto, Dice or cosine similarity; run SMARTS substructure search and reaction SMARTS; generate 2D depictions and ETKDG 3D conformers; extract Murcko scaffolds and canonical hashes; control sanitization and stereochemistry directly. Also trigger on rdkit, Chem.MolFromSmiles, rdFingerprintGenerator, SDMolSupplier, SMARTS query, ETKDG, or FilterCatalog. For standard workflows with a simpler interface use the datamol skill, which wraps RDKit; use rdkit for advanced control, custom sanitization, and specialized algorithms.
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 and analyze discrete or continuous Markov chains including transition matrix construction, state classification, stationary distribution computation, and mean first passage times. Use when modeling a memoryless system with observed transition counts or rates, computing long-run steady-state probabilities, determining expected hitting times or absorption probabilities, classifying states as transient or recurrent, or building a foundation for hidden Markov models or reinforcement learning MDPs.
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 themed Mermaid flowchart diagrams from putior workflow data. Covers theme selection (9 themes including 4 colorblind-safe), output modes (console, file, clipboard, raw), interactive features (clickable nodes, source info), and embedding in README, Quarto, and R Markdown. Use after annotating source files and ready to produce a visual diagram, when regenerating a diagram after workflow changes, or when switching themes or output formats for different audiences.
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。
Apply ant colony optimization and foraging theory to resource search, exploration-exploitation tradeoffs, and distributed discovery. Covers scout deployment, trail reinforcement, diminishing returns detection, and adaptive foraging strategy selection. Use when searching a large solution space where brute-force enumeration is impractical, balancing investment between exploring new approaches and deepening known good ones, optimizing resource allocation across uncertain opportunities, or diagnosing premature convergence on local optima.
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。
AI solution exploration using ant colony optimization — deploying scout hypotheses, reinforcing promising approaches, detecting diminishing returns, and knowing when to abandon a strategy. Use when facing a problem with multiple plausible approaches and no clear winner, when the first approach is not working but alternatives are unclear, when debugging with no obvious root cause requiring parallel hypothesis investigation, or when previous attempts have converged prematurely on a suboptimal approach.
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 a project charter that defines scope, stakeholders, success criteria, and initial risk register. Covers problem statement, RACI matrix, milestone planning, and scope boundaries for both agile and classic methodologies. Use when kicking off a new project or initiative, formalizing scope after an informal start, aligning stakeholders before detailed planning begins, or transitioning from discovery to active project work.
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。
Compose 2D graphics programmatically using SVG generation, diagram layout algorithms, image compositing, and batch processing workflows. Use when generating diagrams, flowcharts, or infographics programmatically, creating reproducible scientific figures, automating production of badges or visual assets, building custom chart types not in standard libraries, or batch generating graphics with parameter variations.
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。