「insights」の検索結果

Organize, extract, prune, and verify Claude Code persistent memory files. Covers MEMORY.md as a concise index, topic extraction to dedicated files, staleness detection, accuracy verification against project state, the dual 200-line / 25KB load cap, and reachability of topic files from the index. Use when MEMORY.md is approaching either load cap, after a session produces durable insights worth preserving, when a topic section has grown beyond 10-15 lines and should be extracted, when project state has changed and memory entries may be stale, or before and after rewriting the index so that no topic file loses its only pointer.

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。

Guide a person in developing active listening skills. AI coaches receptive mindset preparation, full-presence attending, reflective paraphrasing, clarifying questioning, synthesis of understanding, and integration of insights into communication practice. Use when a person wants to improve communication, when someone keeps misunderstanding others or feels misunderstood, when preparing for a difficult conversation such as a feedback session or conflict resolution, or when a person notices they talk more than they listen.

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。

Communicate an integrated insight in a way that is accessible, actionable, and preserves the multi-domain nature of the understanding. Integrated insights are multi-dimensional — linearizing them risks losing the relationships that make them valuable. This skill provides a structured procedure for choosing the right form, expressing the gestalt with honest attribution, and inviting productive challenge. Use after integrate-gestalt has formed a cross-domain understanding that needs to be communicated to an audience — domain specialists, generalists, or decision-makers.

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Analyze datasets and extract insights. Use when user needs to understand data patterns, statistics, or trends.

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 accumulate and retrieve competition knowledge in the knowledge/ stock layer (atomic pages + INDEX). Distill reusable insights from the daily-report flow and promote them, deduplicating and keeping things current. Use when an insight emerges, for weekly cleanup, or to recall past knowledge.

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 operating Inngest API resources from the terminal with `npx inngest-cli@latest api`: Cloud/local run debugging, event-run lookup, function traces, function invocation, app syncs, webhooks, environments, keys, account checks, and Insights queries. Provides prescriptive command routing for agents: which CLI command to run for a run ID, event ID, app ID, function ID, Cloud environment, API key, missing ID, or potentially mutating operation. Use `inngest-cli` for dev server setup/general CLI workflows and `inngest-api` only when raw REST API v2 docs or OpenAPI fallback are needed.

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Use when building, migrating, or debugging Agent Evals on Inngest: scoring AI agent or workflow outcomes, deferred scorers, sessions, traces, step experiments, experiment variant attribution, Insights queries, or production eval loops for prompts, models, tools, providers, and agent behavior. Covers TypeScript SDK v4 scoring beta APIs, `scoreMiddleware`, `step.score`, `inngest.score`, `createScorer`, `defer`, `group.experiment`, `experimentRef`, `meta.sessions`, and when to use durable workflow primitives for outcome-based evaluation.

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Inspect and operate Inngest Cloud through its OAuth MCP connection. Use for deployed apps and functions, failed or slow runs, traces, events, environments, sessions, experiments, and Insights. Prefer this for Cloud operations when MCP tools are available; use CLI or REST skills for explicit terminal or HTTP 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。

Comprehensive, data-backed email marketing knowledge base. 908 sources, 4,798 insights. Use when reviewing email setups, building automation flows, diagnosing deliverability, writing email copy, selecting platforms, or pulling Standards. Covers strategy, flows, deliverability, copywriting, segmentation, compliance, cold email, and 19 industry playbooks.

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 a sprint or milestone retrospective by analyzing completed work, velocity, blockers, and patterns. Produces actionable insights for the next iteration.

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。

Marketing analytics and data-driven optimization for B2B SaaS campaigns. Use this skill when analyzing marketing performance, optimizing conversion rates, running A/B tests, conducting customer research, creating marketing dashboards, building attribution models, analyzing funnel metrics, or storytelling with data. Also triggers on: marketing ops, performance analytics, CRO, A/B testing, data storytelling, customer insights, tracking plan, event taxonomy, UTM taxonomy, GA4 audit, consent mode, instrumentation contract, sample size calculation, minimum detectable effect, test duration, not enough traffic to A/B test, statistical significance, Bayesian vs frequentist, sample ratio mismatch, experiment feasibility, martech stack, marketing tech stack audit, tool consolidation, build vs buy, vendor evaluation, shadow IT tools, ESP/CRM/platform migration, switching cost, cutover plan, suppression list migration, data portability, customer interviews, survey design, sampling frame, non-response bias, how many people should I interview, thematic saturation, voice of customer, jobs-to-be-done, buyer persona research, is this finding real, data enrichment, which enrichment provider should we buy, waterfall enrichment, contact data quality, match rate, our list data is bad, email verification, catch-all domain, accept-all, bounce rate from bad data, B2B data decay, how often should we re-verify contacts, ZoomInfo vs Apollo vs Clearbit evaluation, cost per usable record, where did this list come from, GDPR Article 14 notice, purchased list compliance, suppression screening, TAM list building, demand planning, marketing plan, how many leads do we need, what pipeline target should marketing carry, funnel model, top-down vs bottom-up plan, plan of record, annual marketing planning, quarterly planning, pipeline coverage we have to create, sales cycle lag, our leads cannot close this quarter, carry-in pipeline, scenario planning, conservative moderate aggressive forecast, stretch target, reforecast, re-forecast triggers, assumption register, capacity ceiling, addressable audience ceiling, marginal cost per lead, blended CPL is wrong, we missed plan and nobody knows why, AI policy for the marketing team, AI governance, AI acceptable use policy, which AI tools are we allowed to use, can I paste customer data into ChatGPT, shadow AI, AI use register, human review of AI output, when can we stop reviewing every AI draft, can the agent send on its own, the AI made a mistake now what, pull back AI autonomy, AI evals, our AI vendor changed the model, AI output went out wrong, prompt injection, can our AI read prospect replies safely, lethal trifecta, the AI leaked internal notes, turn off auto-generated ad assets, auto-applied recommendations, AI literacy training, EU AI Act Article 4, duplicate records in the CRM, dedupe before import, which value wins in a merge, CRM cleanup.

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Dedicated Core Web Vitals deep-dive: pull field data (CrUX / PageSpeed Insights), fall back to Lighthouse lab data, score LCP, INP, and CLS against Google's thresholds at the 75th percentile, and run per-metric diagnosis playbooks with concrete fixes. Use when user says "core web vitals", "CWV", "LCP", "INP", "CLS", "page speed metrics", or "field 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。

Run a Lighthouse audit against any URL via the local Lighthouse CLI or the PageSpeed Insights API fallback, parse category scores and failed audits, and map every failed audit ID to its official Chrome docs page plus a one-line fix. Use when user says "lighthouse", "lighthouse audit", "run lighthouse", "lighthouse score", or "pagespeed".

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Analyze server log files for crawl budget insights. Reads Apache Combined/Common or Nginx access logs locally (no external calls). Classifies bot vs user traffic, identifies top crawled URLs, crawl frequency by path, and crawl budget concerns. Use when user says "log analysis", "crawl budget", "server logs", "bot traffic", "crawl frequency", "access log", "analyze logs".

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Read and manage the user's Threads account: profile, posts, feed, saved posts, activity, insights, social graph, search, trends, and a specific post by URL or ID. Can tune feed ranking and publish posts on request.

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。

Read Instagram profiles, followers, posts, comments, likes, stories, feed, saved content, and account insights. Answer questions about posts, reels, and Instagram links. Manage interests and profile details, and publish stories, reels, posts, or carousels on request.

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Use when the user provides a Facebook URL or asks to read personal posts, comments, reactions, friends, timelines, profiles, stories, feeds, groups, events, or saved items, or to publish personal text posts, comments, and replies, or to discover public events happening near a place, nearby, or in a local area on a date, or to create, edit, publish, or delete their own Marketplace listings. To find, browse, or buy Marketplace listings, use shopping instead. Use pages commands for managed Facebook Page discovery, insights, native draft editing/deletion, same-draft publication, approved posts and native scheduling.

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Autonomous competitive analysis and feature discovery pipeline. Runs /compete and /new-features on each project, produces actionable market positioning insights. Schedule daily or weekly.

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Reconstructs the development cycle from git history, distills sequential/parallel patterns, and produces actionable insights for improving future iterations. Triggers: recall, retrospective, development analysis, what happened, dev cycle analysis.

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。

Capture learnings from a campaign, launch, sprint, or initiative using Five Whys (Taiichi Ohno, Toyota Production System) for root cause analysis and Start-Stop-Continue for action planning. Append reusable insights to knowledge/learnings.md so future runs of the OS get smarter. Use when the user asks for a retro, retrospective, post-mortem, "what did we learn", "campaign wrap-up", "lessons learned", or after a campaign or launch ends. Critical feedback loop that makes the OS compound over time. For the numbers review itself, see kpi-review. For planning the next campaign, see campaign-brief.

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。

Plan a monthly content calendar across channels using the Content Marketing Matrix (Dave Chaffey, Smart Insights) - Entertain/Inspire/Educate/Convince. Every post gets a quadrant label. The monthly calendar must hit 40% Educate, 40% Inspire+Convince, 20% Entertain. Produces a week-by-week posting schedule with topics, formats, channels, and asset links. Use when the user says "content calendar", "social calendar", "plan next month's content", "what should we post", "content plan", "editorial calendar", "schedule posts for the month", or wants a structured posting plan for LinkedIn, Twitter, email, or blog. Reads brand voice, ICP, and past learnings from knowledge/. For writing the individual posts, see linkedin-post, newsletter-writer or content-writer. For the campaign this sits inside, see campaign-brief. For the end-of-month review, see retro.

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 marketing KPIs and produce an executive summary with insights, anomalies, and recommended actions using the Storytelling with Data framework (Cole Nussbaumer Knaflic). Every review starts with a Big Idea - one sentence capturing the insight, its implication, and why it matters. Use when the user asks for a KPI review, monthly metrics review, marketing dashboard review, "review last month's numbers", quarterly review, performance review, or wants to analyze marketing data. Reads kpis.md and any uploaded data files. For planning a campaign against these numbers, see campaign-brief. For the post-campaign learning loop, see retro. For setting the baseline itself, see brand-context.

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。

Communicate data insights to non-technical stakeholders in a structured, persuasive format. Use when the user says "present these findings", "explain this analysis to leadership", "make a data presentation", "tell the story behind the data", "translate this into a business narrative", "make this insight actionable", "stakeholder readout", "executive summary of results", or needs to turn analysis output into a decision-ready document or slide deck.

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。

Google SEO APIs: Search Console (Search Analytics, URL Inspection, Sitemaps), PageSpeed Insights v5, CrUX field data with 25-week history, Indexing API v3, and GA4 organic traffic. Provides real Google field data for Core Web Vitals, indexation status, search performance, and organic traffic trends. Use when user says "search console", "GSC", "PageSpeed", "CrUX", "field data", "indexing API", "GA4 organic", "URL inspection", or "real CWV 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。