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概要と使いどころ
Optimize content for search engines with keyword analysis, readability scoring, meta descriptions, and competitor comparison. Use this when users want to improve SEO, optimize blog posts, or analyze content for search performance.
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 pre-call research briefs with company news, stakeholder backgrounds, and custom discovery question sets.
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 working session is ending, the context window is nearly full, work needs to pass to a teammate or a fresh session, or the user says "hand this off", "write this up before we lose it", "I'm starting a new session", or "summarize where we are". Produces a handoff document that lets the next session resume without re-reading the transcript.
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。
Convert content between platforms (blog to Twitter thread, article to LinkedIn post, etc.). Optimize for each platform's format, tone, and best practices. Use when user wants to adapt content for different social media platforms.
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。
Pulls financial statement numbers for US public companies straight from SEC EDGAR's free official XBRL APIs (companyfacts, companyconcept, frames, submissions) into a cited table. Every value carries its accession number, form, fiscal period, filed date, XBRL tag and a link to the filing, and the tool handles fiscal-year ends, quarterly vs YTD vs TTM, derived Q4, restatements and units. Use this whenever the user wants 10-K numbers or 10-Q numbers, says "pull financials for", asks for public company revenue, net income, EPS, cash, debt or capex, wants comps or a competitor side-by-side, a credit check, prospect research, or model inputs, or mentions SEC filings or EDGAR, even if they never say XBRL. Free and primary-source, no paid data terminal needed. Do not use it for private companies, stock prices or valuation multiples.
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 realistic play-by-play commentary. Multiple announcer styles: traditional, hyped, analytical, homer. Color commentary included.
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。
Plans security penetration tests for web applications. Analyzes codebase, API routes, auth implementation, and infrastructure config to generate comprehensive pentest plans. For authorized testing only.
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 realistic coach/player interview responses for wins, losses, controversies, injuries. Authentic coachspeak and player personalities.
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 30+ LinkedIn posts that attract your target prospects. Creates industry insights, thought leadership, engagement prompts, and comment strategies. Use when building personal brand to attract inbound leads through social selling.
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。
30/60/90/120 day ramp milestones. Activity expectations by week, certification progress, early warning indicators.
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。
Analyzes current conversation context to recommend the best skills and subagents for the task at hand. Use proactively when unsure which tool, skill, or agent to use.
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 conversion-focused landing page copy - headlines, subheads, value propositions, feature and benefit blocks, social proof, FAQs, and CTA button text - using PAS, AIDA, or StoryBrand. Use when the user wants words for a landing page, sales page, product or pricing page, waitlist page, homepage hero, or ad-to-page flow, including rewriting weak copy, generating headline or CTA variants for A/B tests, or turning a product description into page sections. Use landing-page-optimizer instead for auditing an existing page's performance, and a frontend skill for building the page itself.
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。
FAQ identification from support tickets, step-by-step tutorial creation, screenshot/video script guidance, search optimization, and self-service deflection tracking.
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 promo videos for local businesses in HyperFrames -- the new-menu drop, the seasonal offer, the event announcement, the "we're hiring" post, the Google Business Profile clip. Restaurant, salon, gym, trades: 15-30 seconds, brand-clean, captioned, sized for Instagram, Facebook, and the 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。
What-if scenario analyzer for sports. Play-calling recommendations, clock management, substitution patterns, risk/reward calculations.
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。
Generates monthly/quarterly investor updates. Takes KPIs, milestones, challenges, financials. Writes professional investor-update.md with highlights, metrics dashboard, product updates, team news, financial summary, upcoming milestones, asks. Multiple tones from seed-stage casual to Series B formal. Use when founders need to communicate progress to investors.
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。
Mine lost deal notes to identify recurring objection patterns. Create objection response playbooks from won deals.
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 pull requests for code quality, security issues, and best practices. Use when reviewing PRs, checking code changes, or analyzing diffs before merge.
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。
Efficiently route multi-stop trips with time management. Include transportation, restaurant/activity reservations timeline, and buffer time for spontaneity.
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。
Monitor buyer intent signals across the web including job postings, tech changes, funding rounds, and leadership changes. Alerts when prospects show buying signals and prioritizes "hot" accounts. Use for timing-based prospecting.
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。
Monitor injury news across leagues. Fantasy impact analysis, backup player analysis, return timeline estimates.
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 before building anything from a vague request — a feature, an app, an agent, an automation, a page. Trigger when the user says "build me X" without specifics, when a brief could be read two ways, or when the user asks to be challenged, interrogated, or pushed on requirements before code gets 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。
Audit a codebase for LLM calls that are really classifications in disguise, then produce a costed swap plan for a System One model. Use when asked to cut AI inference cost or latency, when scoping a performance engagement for a client, when reviewing an agent loop that feels slow, or when asked "where could we use Jev here". Produces a ranked table of candidates with measured latency and dollar deltas.
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。
Construct statistical arguments for MVP/awards. Narrative framing, comparison to past winners, advanced metrics, counter-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。