热门 Agent Skills
2094 个技能在您自己的基础设施上部署自托管漏斗构建器，将漏斗从空安装到发布，并通过 MCP 由代理驱动。
通过为每个任务分派独立的实现子代理，并在每个任务后进行审查，最后进行整体分支审查，从而高效执行实现计划。
使用 liarjs CLI 审计浏览器指纹的内部矛盾，涵盖 canvas、WebGL、WebGL2、WebGPU、音频、220 种字体、WebRTC 和时区探测，并与同一请求的 TLS/HTTP/ASN 视图进行评分比较。
解读 liarjs 指纹报告，将每个失败的检查归因于产生它的组件，并识别哪些失败是 headless 或数据中心环境固有的。
使用 liarjs 库检查 Playwright、Puppeteer、Selenium 或 CDP 驱动的浏览器是否呈现一致的指纹。
根据生产最佳实践审查和编写 Cloudflare Workers 代码，涵盖配置、请求处理、架构、可观测性、代码模式和安全性。
Designs the tier layer downstream of an existing account fit score - where the cutoffs sit, tier names, rep-to-account capacity caps, the coverage model per tier (touch cadence, channel mix, QBR frequency, executive involvement), coverage-ratio health metrics, and the recalibration cadence.
用于使用 Playwright 与本地 Web 应用交互和测试的工具包，支持验证前端功能、调试 UI 行为、捕获浏览器截图和查看浏览器日志。
Models how much pipeline a team needs relative to quota - coverage ratios derived from win rates (raw multiplier, stage-weighted, conversion-inversion), segment-level coverage targets, in-quarter timing and the point of no return, seasonality indexing, and pipeline-gap math that turns a ratio into new-pipeline-required.
Generate AI images with GPT-Image-2, FLUX, Gemini, Grok, Seedream, Reve and 50+ models via inference.sh CLI.
Defines the company's ideal customer profile (ICP) at sales-leadership altitude - the firmographic, technographic, behavioral and intent criteria, a weighted scoring rubric with explicit disqualifiers, and the refresh cadence that targeting keys off.
Estimates TAM, SAM, and SOM for a market or sub-segment to ground sales capacity, territory, and quota planning - top-down, bottom-up on named accounts or population math, value theory, triangulation, a capacity-based SOM ceiling, and a per-layer refresh cadence.
为 Linear Release 生成 CI/CD 配置，支持 GitHub Actions、GitLab CI、CircleCI 等平台。
Employer-side hiring workflow for SDR/BDR and AE roles, producing an outcome-based scorecard, a structured interview loop with question bank, a scored mock-call work sample, and a 30-60-90 ramp plan with certification gates.
Coach one person through landing and growing a sales career - SDR/BDR entry, SDR-to-AE promotion, and beyond - across B2B SaaS and commission-heavy B2C (real estate, insurance, solar, auto).
Automate Twitter/X with posting, engagement, and user management via inference.sh CLI.
Generate AI videos with Google Veo, Seedance 2.0, HappyHorse, Wan, Grok and 40+ models via inference.sh CLI.
Plans a touch-by-touch outbound cadence - which channel on which day, touch count, spacing, channel mix, multi-threading, exit and stop rules, recycle and re-entry, and the capacity math behind it, with pre-committed metric thresholds.
Builds and maintains a personalized watch list of sales information sources - podcasts, newsletters, communities, benchmark reports, and sales people to follow - matched to the user's role, market, and time budget, shipped as a dated verified-source snapshot with per-source status and a freshness check that catches rebranded or dead sources.
Builds a sequenced sales discovery question set - pain, root cause, impact, urgency - for a specific deal or persona, sized to the call length, with follow-up ladders, branch triggers, and a do-not-ask list.
Before starting any sales project, and before answering a sales request that spans more than one sales topic or names no skill at all, run this router first.
Designs the account segmentation model between ICP and tier structure - which firmographic, technographic, intent and jobs-to-be-done signal layers define account fit, the weighted fit score calibrated from 12 months of closed-won deals, fit and readiness as separate axes, whitespace and expansion mapping, and how the model is encoded, routed and re-scored in the CRM.
Diagnoses what a sales objection really means and writes rebuttal scripts a rep can say out loud, or calls the deal dead when the objection is a real constraint.
Reviews a cold email draft and its sending setup for deliverability - SPF/DKIM/DMARC alignment, sender reputation and complaint risk, body mechanics (length, links, images, tracking pixels, HTML vs plain text, opt-out), and legal compliance by region.
Chooses and designs the company-level sales motion at VP Sales / CRO altitude - product-led growth (PLG), sales-led, hybrid product-led sales, developer-led/open-source, or channel/partner-led - plus the transitions between them (exiting founder-led sales, layering sales onto self-serve, moving upmarket, adding channel), mapped to ACV, time-to-value, buyer-vs-user separation, TAM shape and procurement friction.
Designs a sales organization's structure for its current stage - role mix (SDR, AE, AM/CS), topology (island, assembly line, pod, hybrid), SDR-to-AE ratio, hunter/farmer split, span of control, and specialization by segment.
Writes the opening 5-30 seconds of a live outbound cold call - a tailored opener for a named persona and pain point, with 2-3 testable variants, delivery notes, and a measurement plan.
参考指南，涵盖9种优先级排序框架，包含公式、适用场景和模板，如RICE、ICE、Kano、MoSCoW等。
Turns prospect signals into 2-3 ranked personalization angles for outreach, each pairing a dated, sourced signal with the problem it implies, a one-line hook, the ask it justifies, and a confidence/recency label.
Scores one sales call transcript against an anchored rubric - opener, discovery, objection handling, close - quoting the transcript for every judgement and naming one focus behaviour.
教授 AI 如何像高端代理机构一样进行设计，定义精确的字体、间距、阴影、卡片结构和动画，使网站显得昂贵，同时阻止常见的默认设置。
Turns raw sales call notes into a structured recap email with agreed next steps - every action item carrying an owner, a date, and a deliverable - plus mutual close plan (mutual action plan) items when the deal warrants one.
Designs how sales quotas are derived for a team or company - top-down vs bottom-up reconciliation, ramp-adjusted capacity modeling (Ramped Rep Equivalents), over-assignment cushion, territory-weighted fair-share allocation, ramp relief policy, and validation against current attainment benchmarks.
Scores one deal against the eight MEDDPICC elements on an evidence ladder - unknown, assumed, stated, validated - with a scorecard, a verdict band, and the single next action that closes the biggest gap.
Review Archify issues, PRs, or code through value, cost, and impact to support evidence-based maintenance decisions.
Generates, scores, and split-tests email subject lines, producing angle-distinct variants, a numeric scorecard, and a test plan with sample size and decision metric.
Reviews one deal's free-text notes - call notes, opportunity fields, CRM activity log, email threads - for qualification red flags such as single-threaded deal, no champion, no compelling event, unverified budget, no agreed next step, or fading engagement, each graded on severity and confidence with the quoted note fragment behind it.
Builds an evidence-graded stakeholder map for one active deal from titles, call notes, email and meeting activity, and CRM contact roles, naming the likely champion, economic buyer, and blockers, each with a confidence level tied to observed behaviour rather than title.