515 件 ・ 関連度順
概要と使いどころ
Expert sales proposal and pricing presentation strategist. Use when writing proposals, executive summaries, ROI business cases, pricing presentations, SOWs (Statement of Work), RFP responses, or competitive positioning documents. Covers proposal structure, terms positioning, design formatting, follow-up strategy, and win-rate optimization.
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 customer health scoring and analytics guidance. Use when designing health scores, building churn prediction models, analyzing usage metrics, identifying at-risk accounts, creating executive dashboards, or performing cohort analysis. Use for leading indicator development, customer data enrichment, risk escalation frameworks, and retention analytics.
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 product marketing guidance for SaaS growth - trial acquisition, user activation to first value, and freemium-to-paid conversion. Use when writing landing pages, onboarding flows, email sequences, pricing pages, upgrade prompts, or any growth/conversion copy.
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 renewal management guidance for maximizing retention and expansion revenue. Use when building renewal playbooks, forecasting renewal pipeline, structuring multi-year deals, developing pricing strategies, mitigating churn risk, defending against competitive displacement, negotiating contracts, attaching expansion to renewals, or optimizing renewal operations. Covers high-touch and tech-touch renewal motions, early renewal strategies, and save plays.
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 go-to-market strategist for SaaS applications. Use when planning GTM strategy, content strategy, social media strategy, personal brand development, business brand positioning, or channel selection. Covers LinkedIn, X/Twitter, TikTok, YouTube, and multi-channel distribution. Use for launch planning, audience building, founder-led marketing, and growth strategy.
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 partnership marketing guidance for building and scaling partner programs, co-marketing campaigns, and channel ecosystems. Use when developing partner strategy, creating co-marketing content, designing partner tiers, building affiliate programs, positioning in integration marketplaces, enabling channel partners, planning joint webinars, or structuring revenue sharing. Use for technology partnerships, reseller programs, strategic alliances, and partner relationship management.
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。
Babel internal issue protocol — list open handoffs by label. Scans designs/*/.handoff/*.md (filtered by label) and best-effort merge with gh issue list. Used by all guru/architect agents at startup to pick up 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。
Use when the user wants a research-paper figure Skill Factory: build, patch, package, or use reusable specialized paper-figure-making skills from lawful literature/corpus evidence. Generated skills must use a specialized-skill-first workflow, full-feasible local PDF coverage where available, startup-plan-only first replies, target-paper candidate/final image isolation, mandatory image-embedded visual-structure explanation, mandatory non-target concept/modeling example display for abstract visual decisions, saved subtype/style illustration atlases, ChatGPT web Create image / ChatGPT Images 2.0 rendering, Codex $imagegen-first rendering, sample-image transfer rules, all-step/current-position state footers, and a mandatory first-round diverse candidate board followed by P6b/P6c paper-local best-practice optimization before final prompt construction.
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。
운영 중인 소상공인(가게·점포·자영업자)을 위한 지원사업 조사 스킬. 소상공인24·기업마당 공고를 전수 수집하고 가게 프로필(업종·지역·업력·직원수·매출)로 자격을 판정해 "오늘 신청할 것"부터 보고한다. 보조금·바우처, 정책자금(대출·보증), 교육·컨설팅 전 범위. 사용자가 "우리 가게 지원사업", "소상공인 지원금", "정책자금 알아봐줘", "가게 시설개선 지원", "사장님 지원 뭐 있어", "소상공인24 조사", "폐업/재기 지원" 등을 요청하면 이 스킬을 사용한다. 재조사("새로 나온 거 있나", "지난번 이후 뭐 올라왔나")는 diff 모드로 사용. 반대로 "우리 아이템", "창업지원", "예비창업", "K-Startup", "TIPS", "R&D 과제", "입주공간", "액셀러레이팅" 등 아이템·프로젝트 기반 창업지원 탐색은 이 스킬이 아니라 ir-search를 사용한다. 신호가 섞이면(예: "온라인 셀러 지원금") 어느 쪽인지 한 번 묻는다. 사용자 신분보다 요청 목적이 우선이다 — 가게 사장이라도 신규 기술 아이템 R&D를 찾으면 ir-search. 한국 전용.
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。
Turn a raw product idea into build-ready docs — one doc per EPIC with locked decisions, exact API contracts, a story-by-story priority plan, and an execute.md handoff Claude can build from across sessions. Gets the clarity by interrogating the user through a roster of expert personas that grill, counter, and refuse to flatter. Use to ideate, validate, scope, architect, or plan a product, feature, startup, or app before any code is written. Invoke by persona name or acronym to summon one expert, or with no argument to run the full lifecycle end to end.
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。
Structures technology diligence with architecture review, code quality assessment, scalability analysis, and technical debt evaluation. Use when evaluating startup technology, assessing engineering teams, or reviewing technical infrastructure.
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。
Deconstructs unit economics with CAC, LTV, payback period, gross margin, and contribution margin analysis. Use when analyzing unit economics, validating SaaS metrics, or assessing business model efficiency.
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。
Maps competitive dynamics with market positioning, feature comparison, funding histories, and differentiation assessment. Use when analyzing startup competition, mapping market landscapes, or identifying competitive threats.
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。
Scores and strengthens startup pitch decks (pre-seed through Series A) against 35 investor-grade criteria grounded in Sequoia, DocSend, YC, a16z, and Carta data. Use when the user has shared a pitch deck (PDF, PPTX, markdown, pasted slide text, or a link to one) and asks for a review, score, feedback, or critique. A full review takes about 15–25 minutes, 40 or more for a long investor deck, so for a general pitch question with no deck, answer briefly in chat and offer the review instead of starting it. When it runs, score with the rubric, never with deck advice from memory.
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。
Reviews startup financial models for investor readiness: validates unit economics, stress-tests runway scenarios, and benchmarks metrics against stage-appropriate targets. Use the full review, about 10–15 minutes, when the user provides a financial model (Excel, CSV, or a model pasted as text) and asks for review, validation, runway analysis, or unit-economics scoring. For a single money question with figures to compute, such as 'how long do I have?' or 'is a 4x burn multiple bad?', use its shorter quick check, so the answer comes from the calculator and dated benchmarks, not mental arithmetic.
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 credible TAM/SAM/SOM analysis with external validation and sensitivity testing for startup fundraising: top-down, bottom-up, or both. Use when the user asks to size a market or check market claims and gives something to size: a product or service description, a market segment, or a deck with TAM/SAM/SOM claims. A full run takes about 15–20 minutes and searches the web, 30 or more with a large data room or a revision round, so for a passing question about market size, answer briefly in chat and offer the analysis instead of starting it. When it runs, every figure is externally sourced and stress-tested, never estimated from memory.
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。
診斷並清理 macOS 磁碟空間，特別是「系統資料 / System Data」這類看不出內容的用量。涵蓋開發者工具殘骸（Xcode iOS DeviceSupport、Simulator runtime、DerivedData）、套件管理器快取（Homebrew、pnpm、pip、npm、cargo、go、uv）、容器與 VM 磁碟（Docker、podman、lima）、瀏覽器 profile、以及已移除 app 的孤兒 container。使用時機：(1) 使用者說磁碟快滿了、System Data 佔太多、想清空間 (2) 詢問某個資料夾或快取能不能刪 (3) 移除 app 後想清乾淨殘留檔案、完整解除安裝 (4) 想知道 Docker.raw、Group Containers、Library/Caches 這些是什麼、佔了多少。Also triggers in English — disk full, startup disk almost full, free up disk space, clean up Mac storage, what is System Data on my Mac, what is taking up space, safe to delete this cache, uninstall app leftovers, reclaim disk space, Docker.raw huge, Xcode taking too much space
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 the user wants to get found in Google or AI engines (ChatGPT, Perplexity, AI Overviews) — keyword and content strategy, technical or content SEO audits, schema markup, link building, topical clustering, E-E-A-T, AI citation (AEO), or deciding whether SEO is even the right channel for their startup. Calibrated for early-stage, low-authority sites. Not for paid acquisition or channel-mix/CAC analysis (use channel-expert), or writing the page copy itself (use copywriter-skill).
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 writing a GNU ld script for a bare-metal target, placing code in a flash or RAM region, wiring .data and .bss startup, or fixing a region overflowed error. Not for LTO: use linkers-lto.
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 writing Cortex-M NVIC ISRs, configuring priorities, handling HardFault, tail-chaining, or measuring interrupt latency. Not for the vector table itself: use baremetal-startup.
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 writing a custom bootloader, jumping to application code, relocating VTOR, or implementing DFU/USB firmware update on Cortex-M. Not for reset-to-main: use baremetal-startup.
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 the repo-local Odylith startup contract first, before context/search fan out.
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 first, before context/search fan out, when a task needs repo-local Odylith startup grounding.
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。
Fix docker exec hanging when starting background processes (servers, daemons) inside containers. Use when: (1) docker exec never returns despite using & or nohup, (2) background server started in container causes docker exec to hang indefinitely, (3) env_startup_command in SWE-bench or similar frameworks times out, (4) setsid/disown needed for proper process detachment in Docker. Root cause: docker exec tracks ALL processes in the exec session, not just the top-level PID.
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。