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概要と使いどころ
Multi-factor cross-sectional stock ranking. Combines factor standardization, equal-weight or IC-weighted scoring, and TopN portfolio construction. Suitable for multi-instrument portfolio strategies.
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。
Volatility strategy. Trades mean reversion based on percentile ranking of historical volatility (HV). Suitable for any OHLCV data.
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。
Supply-chain bottleneck arbitrage. Given a super-trend (AI infra, energy transition, defense, semiconductor reshoring, space economy), decompose its physical supply chain down to Layer 2/3 choke points (optics, lasers, InP/SOI substrates, IC substrates, probe cards, specialty fiberglass...) and surface under-the-radar listed companies sitting on each bottleneck. Scores each link on 6 scarcity criteria, applies mandatory valuation gates (PS/PE/safety-margin) via the financial_rigor tool, and Munger-style reverse-validates. Outputs a ranked bottleneck opportunity board. Use when the user wants hidden beneficiaries of a structural trend rather than already-priced leaders.
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。
Run read-only deep repository analysis and return a ranked synthesis with explicit confidence, concrete file references, and clear evidence-vs-inference boundaries. Use when a user says 'analyze', 'investigate', 'why does', 'what's causing', or needs grounded cross-file explanation before any changes are proposed.
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。
Set up and run local web searches using Bright Data SERP API with the unfancy-search pipeline (query expansion, SERP retrieval, RRF reranking).
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。
When the user wants to audit, review, or diagnose SEO issues on their site. Also use when the user mentions "SEO audit," "technical SEO," "why am I not ranking," "SEO issues," "on-page SEO," "meta tags review," or "SEO health check." For building pages at scale to target keywords, see programmatic-seo. For adding structured data, see schema-markup.
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。
Parameter-efficient fine-tuning for LLMs using LoRA, QLoRA, and 25+ methods. Use when fine-tuning large models (7B-70B) with limited GPU memory, when you need to train <1% of parameters with minimal accuracy loss, or for multi-adapter serving. HuggingFace's official library integrated with transformers ecosystem.
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 for Vercel cost and performance optimization on deployed projects, especially Next.js, SvelteKit, Nuxt, and limited Astro apps. Collect Vercel metrics, usage, project config, and code scan results first; investigate only metric-backed candidates; produce ranked recommendations grounded in verified files and version-aware Vercel/framework docs. Trigger for Vercel bill reduction, slow or expensive routes, caching opportunities, Function Invocations, Build Minutes, Fast Data Transfer, Core Web Vitals, Bot Management, Fluid compute, or cost breakdown requests.
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。
Token-hygiene audit of the always-loaded context stack — CLAUDE.md, AGENTS.md, auto-memory MEMORY.md, and the bootstrap-rendered identity files (SOUL.md, USER.md, ACCESS_POLICY.md, HEARTBEAT.md) or their harness equivalents. Finds redundancy, contradictions, stale content, compression candidates, and skill-extraction candidates; produces a ranked action list sorted by token savings with a risk class per finding. REPORT-ONLY: this skill never edits any audited file. Recommendations for bootstrap-rendered files target the interview answer bank / templates, never the rendered output. Judging routes through `gbrain eval cross-modal` (single cheap model by default; full multi-model panel is explicit opt-in).
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。
Poll and rank open GitHub issues, RFCs, and pull requests for maintainer work, or start one explicitly selected item. Use when a user asks what to work on, requests backlog priorities, says "poll work," wants actionable issues or pull requests, or says "start
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Debug a broken Zoom integration by isolating the failure point and routing into the right Zoom references. Use when auth, API, webhook, SDK, or MCP behavior is failing and you need a ranked hypothesis list plus verification steps.
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。
Builds a ranked list of prospects worth contacting. Works out the owner's ideal customer profile from the customers they already have, finds look-alike companies and the right contact at each, enriches them with firmographics and buying signals, scores them, and delivers the list as an XLSX, with an offer to also create the records in the CRM. Runs on Apollo when connected and falls back to web research plus an uploaded customer list when it isn't. Use this whenever the owner wants new prospects, a target list, or help finding customers — including phrasings like "who should I be calling," "find me more customers like my best ones," "build me a prospect list," "I need leads," "who else looks like Acme," or "help me find companies in this area that need what we do." Reach for it even when the owner describes the customer they want rather than asking for a list.
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。
Turns a full inbox into a short, ranked list of what actually needs the owner. Reads the mail, sorts it into needs-you, drafted-and-waiting, and handled, writes replies in the owner's own voice, pulls out the action items and deadlines buried in long threads, files what is finished, and hands bills, leads, and scheduling requests to the skills that own them. Works from pasted or forwarded email text when no mailbox is connected. Use this whenever the owner mentions email at all — including "drowning in email," "I have 300 unread," "what emails need me," "go through my inbox," "clean up my email," "did I miss anything," "who am I supposed to get back to," "draft a reply to this," or "catch me up on my mail." Reach for it for one forwarded message as readily as for a whole morning's backlog.
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。
Runs the payroll-confidence chain end to end — forecasts cash across the payroll window with cash-flow-snapshot, ranks and drafts overdue-invoice reminders with invoice-chase to close any gap, then assembles timesheets, flags every anomaly, and stages the run with payroll-prep. On Gusto the run is staged for the owner to submit; on QuickBooks Payroll, or with no payroll system, the last step is a validated run sheet the owner keys in. This chain never presses the payroll button. Builds on the ledger (MYOB, NetSuite, QuickBooks, Xero, or Zoho Books), with Gmail or M365, PayPal, Square, Stripe, and either Gusto or QuickBooks Payroll adding detail, and falls back to CSV and timesheet uploads. Use it whenever payroll is the worry, including "can I make payroll," "payroll is due Friday," "plan payroll," "will I have enough to pay the crew," or "I need to run payroll but money is tight." Accepts optional horizon and payroll-date arguments.
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。
Takes a pile of applications and turns it into a ranked shortlist, scored only against the job's stated rubric, with drafted replies to every candidate, scheduled interviews, and an onboarding checklist for whoever gets hired. Picks up where job-post-builder leaves off and carries the funnel through to first day, including the payroll setup handoff. Runs on Gmail and Google Calendar, deepens with Gusto, DocuSign, and Drive or M365, and works entirely from uploaded resumes with drafted replies the owner sends by hand. Use this whenever the owner has applicants to deal with — including phrasings like "I've got 40 resumes and no time," "who should I interview," "screen these applications," "help me narrow this down," "set up interviews for the top three," or "I need to tell the rest no." Reach for it when the owner mentions applicants, resumes, candidates, or being buried in a hiring inbox.
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。
Fills the funnel end to end without the owner babysitting it — reads the market and the competition for context, builds a ranked list of named prospects with a reason attached to each, writes personalized outreach in the owner's own voice, and logs every touch to the CRM. Chains lead-finder, outreach-composer, and crm-autopilot behind a web-native market read, with an owner approval at every handoff. Use this whenever the owner wants more pipeline rather than one specific piece of it, including phrasings like "I need more leads," "fill my funnel," "who should I be calling and what do I say," "find me customers like my best ones and reach out," "build me a prospect list and write the emails," or "sales has gone quiet, get something moving." Reach for it when the owner describes wanting new business generally rather than asking for a list or a single email.
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。
Builds end-to-end hiring packets — job post, structured interview guide with scoring rubric, and offer letter template — from a hiring brief. Triggers on: "help me hire", "we're hiring for", "write a job post", "job description", "JD", "open role", "create a job ad", "interview questions", "scoring rubric", "draft an offer letter", "send an offer", "make a hiring packet", or any request to recruit for a position. When in doubt, trigger — covers the full hiring workflow from job post through DocuSign envelope creation via browser. Does NOT screen or rank applicants.
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 ICP-to-leads pipeline. Describe your ideal customer in plain English and get a ranked table of enriched decision-maker leads with emails and phone numbers.
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。
Wins back customers who have quietly stopped buying — finds the ones whose gap has stretched past their own normal rhythm or who are showing churn signals, ranks them by what the relationship was worth, drafts a win-back message per customer in the owner's voice, and sends and logs only what the owner approves. Chains review-reputation, outreach-composer, and crm-autopilot, and keeps the rule that the first touch acknowledges the gap without pitching. Use this whenever the owner is worried about customers drifting away, including phrasings like "who hasn't ordered in a while," "win back my old customers," "which customers have gone quiet," "we lost some regulars," "reach out to the people who stopped calling," or "how do I get them back." Reach for it when the owner names a customer they have not heard from, as readily as for a full win-back campaign.
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。
Synthesize user research from interviews, surveys, and feedback into structured insights. Use when you have a pile of interview notes, survey responses, or support tickets to make sense of, need to extract themes and rank findings by frequency and impact, or want to turn raw feedback into roadmap recommendations.
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。
Query decomposition and multi-source search orchestration. Breaks natural language questions into targeted searches per source, translates queries into source-specific syntax, ranks results by relevance, and handles ambiguity and fallback strategies.
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。
When the user wants to audit, review, or diagnose SEO issues on their site. Also use when the user mentions "SEO audit," "technical SEO," "why am I not ranking," "SEO issues," "on-page SEO," "meta tags review," or "SEO health check." For building pages at scale to target keywords, see programmatic-seo. For adding structured data, see schema-markup.
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。
Manage local SEO for service-area businesses — appliance repair, HVAC, plumbing, cleaning, and any business that serves customers at their location. Use when the user wants to: audit Google Business Profile, generate neighborhood service area pages, check NAP consistency across directories, create LocalBusiness schema, or write review responses. Triggers: 'local SEO', 'Google Business Profile', 'GBP', 'service area page', 'NAP consistency', 'local citations', 'LocalBusiness schema', 'review responses', 'Google Maps ranking'. NOT for national SEO (use seo-audit). NOT for general schema (use schema-markup). NOT for AI answer-engine visibility (use aeo).
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。
Answer Engine Optimization (AEO) skill — optimize content to be cited by AI language models (ChatGPT, Perplexity, Claude, Gemini, Mistral) as authoritative sources. Distinct from SEO — AEO optimizes for citation in LLM-generated responses, not search rankings. Use when planning content for AI-first search audiences, auditing existing content for E-E-A-T signals, tracking which pages get cited by which LLMs, or building a citation-friendly content strategy. Triggers — 'AEO audit', 'optimize for ChatGPT', 'get cited by Perplexity', 'LLM citation strategy', 'answer engine optimization', 'content for AI search', 'E-E-A-T audit'. Output is a markdown audit report (default) or JSON for pipeline integration. Stdlib-only Python tools.
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。