「quick」の検索結果

Develop positioning strategy with anchor, differentiators, status-quo alternatives, and a positioning statement. Reads from marketing/icp/ICP.md + marketing/competitors/aggregate.md. Writes to marketing/positioning/positioning.md as the canonical positioning every downstream skill reads. Triggers - "positioning", "category definition", "how do we position", "positioning strategy", "anchor + differentiators"

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Build structured ICP documentation by scraping case studies, testimonials, and solutions pages from your website. Produces firmographics, champion + economic buyer personas, pain points, decision criteria, anti-ICP, customer proof points, and voice-of-customer synthesis. Writes to marketing/icp/ICP.md as the canonical ICP every downstream skill reads. Triggers - "icp research", "ideal customer profile", "persona research", "customer segments", "who are our customers", "build ICP"

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Maps your company's GTM motion (PLG, SLG, or Hybrid) to concrete funnel stages with inputs, outputs, and qualification criteria per stage. Detects motion type from website + Exa research, then produces pre-close + post-close stage definitions, the FETE mapping (Fit / Engagement / Tier / Eligibility), and closed-lost re-entry paths. Triggers - "funnel strategy", "funnel stages", "pipeline stages", "sales process", "lead qualification", "GTM motion mapping", or any work defining how leads flow through the business. Upstream - recommended company-context, icp-research. Downstream - feeds lifecycle-marketing, outreach-emails, content-strategy. NOT for lead scoring logic (use /lead-scoring) or lifecycle email campaigns (use /lifecycle-marketing).

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Extract a founder's or expert's point of view — core beliefs, contrarian takes, origin stories, taste — and synthesize a recommended "one big idea" (OBI) that anchors thought leadership and brand voice. Writes to marketing/expert-pov/expert-pov.md. Triggers - "expert pov", "founder point of view", "thought leadership angle", "one big idea", "OBI", "founder beliefs", "founder narrative"

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Use whenever the user wants to find, shortlist, vet, or enrich US accounting and tax firms (CPA firms) — financial-statement audit, SOC 1/2 audit, corporate tax, bookkeeping for businesses, advisory/fractional CFO, M&A diligence, 409A valuations, R&D tax credits, IPO readiness, sales-and-use tax. Triggers on "find me a CPA firm for our delaware c-corp series A audit", "shortlist three audit firms with SaaS experience", "we need a tax advisor for our M&A", or "pull contact info for these 10 accounting firm domains", even when described indirectly (audit our books, fractional CFO support, file our 1120). Drives the ServiceGraph API (api.servicegraph.co) — a 100k+ US firm catalog filterable by industry, services, location, size, ratings. Skip personal/consumer tax preparation (1040, individual estate, retirement planning), in-house controller/CFO hires, "how do I file my taxes" DIY questions, accounting-software comparisons (QuickBooks vs Xero), non-US firms, individual freelance bookkeepers.

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Use this skill when selecting or running Biome test fixtures, quick tests, `insta` snapshot workflows, expectation comments, orphan checks, or required code generators. Do not use for subsystem implementation design.

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Systematically QA test a web application and fix bugs found. Runs QA testing, then iteratively fixes bugs in source code, committing each fix atomically and re-verifying. Use when asked to "qa", "QA", "test this site", "find bugs", "test and fix", or "fix what's broken". Three tiers: Quick (critical/high only), Standard (+ medium), Exhaustive (+ cosmetic). Produces before/after health scores, fix evidence, and a ship-readiness summary. For report-only mode, use /qa-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。

View a quick progress summary of current tasks.

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。

Index local coding-agent sessions into a searchable SQLite-backed view so you can inspect usage, compare failures, and recover prior context quickly.

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Uses Lynis to run an on-host security audit and turn the findings into a prioritized hardening checklist for an agent or operator. Invoke it when a machine is about to become internet-facing, after base image changes, or whenever you need a quick read on hardening drift instead of a generic vulnerability scan.

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Indexes and searches API documentation from OpenAPI 3.0 specs using swagger-parser and lunr.js. Builds searchable indexes of endpoints, parameters, and response schemas for quick reference.

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Professional content generation system with a GSD-style phased workflow, integrated SEO optimization (claude-seo), and anti-AI auditing (humanizer). USE THIS SKILL whenever the user asks to write, draft, create, generate, or produce ANY content — including blog posts, articles, LinkedIn posts, Facebook posts, Twitter/X tweets or threads, Instagram captions, email newsletters, email campaigns or sequences, landing pages, product pages, web pages, sales pages, sales funnels, case studies, testimonials, product descriptions, or SEO metadata. Also triggers on: "/writer:discuss", "/writer:plan", "/writer:execute", "/writer:verify", "/writer:ship", "/writer:next", "/writer:profile-create", "/writer:profile-view", "/writer:profile-edit", "/writer:status", "/writer:help", "/writer:update" — or any request to manage a writer profile or create marketing materials. ALWAYS use this skill even for quick, casual content requests like "write me a LinkedIn post about X" or "draft a tweet thread." The profile and phased workflow produce significantly better output than ad-hoc generation.

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Interactive code simulation engine that spawns ghost personas to review your code before it ships. Each ghost walks through your code line-by-line from a different failure perspective: The Adversary (race conditions, double-submit, idempotency), The Enterprise Edge (business logic gaps, multi-currency, B2B tax exemptions, locale), Chaos Monkey (timeouts, partial failures, network partitions, OOM). Produces a chaos timeline, structured bug report with severity ratings, and three resolution tiers (quick fix, robust architecture, generated test suite). Use this skill whenever the user mentions code review, PR review, "find bugs", "what could go wrong", "will this break", "is this safe", "stress test", "edge cases", design review, pre-merge check, dry run, chaos test, or wants a second opinion on any code — even if they don't explicitly ask for "ghost personas" or "simulation". Also trigger when someone pastes a code snippet with any question about its correctness or safety.

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Use for any cap-table number, mechanic, or date before a founder signs, from a single SAFE, note or warrant described in chat or a quick 'is this dilution reasonable?' check to any draft or signed SAFE, note, term sheet, option plan, AoA, Carta XLSX, or spreadsheet. A single question gets a short cited answer in about 2–3 minutes; the full report, about 5–10 minutes, runs only when the founder shares documents or asks for it. Source-cited deterministic math (YC, NVCA, Cooley GO) for SAFE/note conversion, priced-round dilution, anti-dilution, option pools, warrants, MFN chains, dual-class voting, QSBS and Israeli §102 dates, and Israeli ↔ Delaware flips. NOT for waterfall modeling, cumulative dividends, RSUs, 83(b), 409A, SPAC, warrant repricing, or pure term definitions.

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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.

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Design onboarding and activation flows that help users reach value quickly. Use when the user mentions onboarding, getting started, first-time users, activation, aha moments, or new user flows—not when the work is only the empty-state surface itself.

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Research what's genuinely new about a topic in a recent time window. Use when the user asks what's new, recent, or trending on a subject and wants a source-grounded brief rather than a quick lookup.

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Validate a bug bounty finding before writing a report — the 7-Question Gate, 4 pre-submission gates, always-rejected list, conditional chain table, CVSS 3.1 quick reference, and severity decision guide. Use BEFORE writing any report to avoid N/A and low quality submissions.

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Rewrite text so it reads like a real person wrote it, not an AI. Auto-detects Russian vs English and applies the matching rule set. Use when the user asks to humanize text, remove the "AI smell", de-AI, or make AI output sound natural - especially for Russian. Russian requests count too - очеловечь, перепиши как человек, оживи текст, убери запах ИИ, сделай живее, звучит как робот, убери канцелярит. Also use when asked whether a text was written by AI - нейросеть писала?, похоже на ChatGPT?, видно ли, что это ИИ, человек или бот писал, did AI write this? - then check and report findings without rewriting. While installed, also keep your own Russian and English writing free of the quick-list stock phrases, silently; never edit the user's text unless asked.

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。

Validated commit — runs quick checks before committing. Use when ready to commit changes.

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。

Exposes Claude's reasoning chain as an auditable, decomposable artifact. Quick mode (default) gives assumption inventory + weakest-link in 2 stages. Full mode (--full) adds decision branching, confidence decomposition, and falsification conditions. Triggers on "왜 그렇게 생각해", "reasoning", "근거", "show your work", "어떻게 그 결론이", "trace", "판단 근거", "why do you think that".

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。

Search the web with Exa AI — neural search, content extraction, similar page discovery, quick research with citations, and async pro research with structured output. Covers all Exa endpoints (/search, /contents, /findSimilar, /answer, /research/v0/tasks). Triggers on web search, find pages, similar pages, research with citations, Exa, neural search.

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Deep, iterative, multi-source research that explores a topic from multiple perspectives, detects contradictions, and produces a comprehensive vault note with fact-level citations and a confidence map. Use this skill whenever the user says /deep-research, "deep research X", "research X thoroughly", "investigate X deeply", "I need to really understand X", or wants research that goes beyond a quick web search. Also use when the user wants to understand a complex, contested, or multi-faceted topic, compare competing approaches with evidence, or build a comprehensive mental model they can trust for decisions. This is heavier than /research — it searches web, academic papers, Reddit, and the vault, then loops through exploration and critique rounds until the evidence base is solid. When in doubt between /research and /deep-research, prefer this one if the topic is complex, contested, or the user wants depth over speed.

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Analyzes Claude Project context budget under the automatic-RAG-by-window model: knowledge files vs. threshold-exempt overhead (Skills, MCPs, CI, Memory). Two modes: Quick Diagnostic and Full Budget Audit. Use when user says "check my context budget," "how much context am I using," "is my project too big," "optimize my token usage," "tier my files," "optimize for RAG," "improve retrieval quality," "should I keep compressing," "am I over-compressing," "should I accept RAG mode." Also trigger on context pressure symptoms: "Claude forgets my instructions," "responses getting generic," "content not found in my knowledge files." Also use when a project audit scores Knowledge Architecture ≤ 3. Do NOT use for content placement decisions (use rootnode-memory-optimization if available), full project audits (use rootnode-project-audit if available), or behavioral tuning (use rootnode-behavioral-tuning 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。