“cta”的搜索结果

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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Systematic fuzzing across two dimensions: (1) content discovery — hidden directories, files, backup/source leaks, HTTP verb enumeration, 401/403 bypass via path manipulation; (2) input validation — auth/token stripping, type confusion, boundary value analysis, HTTP parameter pollution, header fuzzing, cookie fuzzing, mass assignment discovery, and entropy/predictability analysis of any generated value. Works on any domain. Chains from /web-exploit or /pentester; chains into /business-logic when boundary violations, predictable IDs, or mass assignment are confirmed.

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Designs the first screen visitors see — the hero section. Layout patterns (split, centered, asymmetric, full-bleed), navbar design, headline typography, CTAs, background treatments (gradients, video, particles, 3D), scroll cues, and above-the-fold conversion strategy. Activate on 'hero section', 'landing page hero', 'above the fold', 'first impression', 'homepage header', 'navbar design', 'hero layout', 'landing page design'. NOT for full multi-page site architecture (use web-design-expert), not for SEO content strategy (use seo-visibility-expert).

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Systematic methodology for eliciting, representing, and operationalizing expert cognitive skills—pattern recognition, situation assessment, mental simulation—from practitioners without requiring research training. Bridges academic rigor and practical usability.

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Redacta un pull request para la rama actual rellenando la plantilla de PR del repositorio en función de los cambios de la rama. Úsalo cuando la persona pida abrir/crear un PR, preparar un pull request o escribir la descripción de un PR (p. ej. "abre un PR", "redacta el pull request de esta rama"). No hace merge.

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Suggests CSII with good adherence to monitoring and dosing for adults with type 2 diabetes mellitus who have poor glycemic control despite intensive insulin therapy, oral agents, other injectable therapy, and lifestyle modifications. Trigger phrases include 'T2DM on multiple injectables still uncontrolled' and 'Consider pump for insulin-requiring T2DM failing other therapies'.

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Chicago CTA L train arrivals, bus predictions, and service alerts.

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Use when turning expert materials, execution traces, repository evidence, or long-form documents into an inspectable, correctable, and empirically verified agent skill. Covers source governance, capability-vs-behavior separation, contrastive induction from successes and failures, intervention testing, versioning, rollback, and task-conditioned vs. reusable-library evaluation.

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テストは存在するがアサーションが実質何も検証しておらず、実装が壊れても落ちない（常に PASS する）構造を diff-time で検出する。Check 1 missing assertion（テスト本体にアサーションが無い）、Check 2 tautological assertion（定数同士・入力自身・mock の戻り値自身を assert し SUT に依存しない）、Check 3 nonexistent expected literal（assertDontSee / assertNotContains 等の期待文字列が対象ファイルに実在しない）、Check 4 stale expected value（同一 diff で対象の出力が変わったのに期待値が据え置き）、Check 5 unscoped expectation（汎用的な属性・クラスを応答全体に対して assert し対象要素にスコープされていない）、Check 6 swallowed failure（例外の握り潰しや到達しない位置のアサーションで判定が成立しない）、の 6 Check を対象とする report-only。テストの有無は test-existence、未テスト経路の量は coverage-gap、非決定性は flaky-test、命名は test-naming、JS/TS の un-awaited resolves / rejects は vitest-mock-isolation、tdd-ledger artifact ベースの RED/GREEN 検証は plangate-tdd-evidence、.only / .skip / xit / @ts-ignore と空の catch は heuristic-review.mjs の決定論検出器へ委譲する

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解释火山 AI 音视频互动的产品能力、适用边界与最新官方文档；生成或修改 VoiceChat/Aibot 配置；并帮助用户搭建、运行和分阶段排查最小 InteractAI VoiceChat Web Demo。

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Exhaustive idea extraction through recursive breadth-before-depth exploration with Deep Think protocol and fractal structure. Use during /ideate to transform raw ideas into comprehensive, structured ideation output. Writes to a fractal folder hierarchy — every node has an index, CX file, and children.

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Data Quality Specialist IA — Expert en qualité des données (profiling, cleaning, déduplication, validation de schéma, Great Expectations)

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claude-org-runtime のリリース (release-* タスク / vX.Y.Z タグ発行) を、 同 PyPI 発行を受ける claude-org-ja 側の expectation 同期と ペアで設計・委譲・完了させるためのワークフロー。 DEFAULT_NOTIFY 値・classifier vocabulary・role_configs_schema (ja 側ミラー: org_extension_schema)・attention.example.json テンプレ等が 変わるリリースで発動する。 CI cascade を予測・予防し、ja-side の red を回避することを目的とする。

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Fractal geometry and self-similarity skill; use when working on recursive geometric or visual systems.

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Android アプリ開発 (Kotlin) の推奨アーキテクチャリファレンス。 Jetpack, androidx, UI layer, Domain layer, Data layer, state holder, UDF, SSOT, オフラインファースト, モジュール化, ViewModel, viewModelScope, SavedStateHandle, Lifecycle, repeatOnLifecycle, collectAsStateWithLifecycle, LiveData, Hilt による DI, Paging 3 によるページング処理。

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Operação de aplicação Laravel em produção — Horizon, queue, scheduler, Octane, Redis, Supervisor, PHP-FPM, cache e deploy. Use quando o usuário disser "laravel", "horizon", "queue", "fila travada", "job falhando", "octane", "artisan", "php-fpm", "supervisor", "scheduler não roda".

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Systematic methodology for eliciting, representing, and operationalizing expert cognitive skills—pattern recognition, situation assessment, mental simulation—from practitioners without requiring research training. Bridges academic rigor and practical usability.

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Systematic methodology for eliciting, representing, and operationalizing expert cognitive skills—pattern recognition, situation assessment, mental simulation—from practitioners without requiring research training. Bridges academic rigor and practical usability.

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Apply AlphaGo-style patterns: learned priors plus search, mixed evaluators, self-play, and asynchronous fast/slow loops. Use for intractable search and compute allocation. NOT for basic supervised learning, tractable optimization, or domains without search bottlenecks.

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Align explicit requirements, implicit expectations, non-goals, observable acceptance, evidence, and decision authority before OpenSpec specs and executable tasks finalize. Use when authoring or updating a proposal, design, specs, or tasks, or when a request hides a material product choice. Do not use for routine implementation of an already-authorized task, unrelated conversation, or facts the repository can answer.

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[20] UNDERSTAND. Achieve complete clarity on goals, expectations, and success criteria. Use when starting new tasks, when requirements seem unclear, when scope is ambiguous, or anytime you need full understanding of what success looks like. Triggers on "clarify goal", "understand requirements", "what exactly needed", "define success", or when facing unclear expectations.

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将工作状态和决策依据保存为本地Markdown记录，供Claude、Codex等代理交接或日后继续使用，并指导搜索已有上下文、编写交接文档和诊断记录不一致的问题。

• 将Claude的工作交接给Codex
• 为下次工作保存上下文
• 查找以往决策及其依据

搜索Polymarket预测市场，将市场价格换算为事件发生可能性的百分比，并获取成交量、买卖挂单和价格历史，以查看市场预期及其变化。

• 通过市场价格了解事件发生的可能性
• 寻找特定主题的预测市场
• 查看当前价格和买卖挂单

将系统结构和数据流整理成交互式立体 HTML 地图，点击即可查看细节。还能从同一份数据生成说明文档，记录设计决策并跟踪尚未解决的问题。

• 说明系统结构和数据流
• 与团队讨论新设计
• 跟踪评审中尚未解决的问题