熱門 Agent Skills
2094 個技能design-taste-frontend-v1 is the original v1 taste-skill, preserved for projects depending on its exact behavior; the current default is v2 experimental.
Build, migrate, and deploy Next.js apps on Cloudflare Workers with vinext.
Score and force-rank the openings of candidate video ads - from a script, transcript, storyboard, shot list, or a description of a finished cut - to decide which hooks deserve test budget, returning a ranked shortlist within the batch rather than an absolute performance prediction.
Aggregates meeting minutes within a specified time range and generates a structured report, suitable for organizing meeting notes, generating weekly summaries, or reviewing past meetings.
Create, run, and maintain Momentic mobile E2E tests and modules for Android and iOS.
Design a multi-stage retargeting sequence from a site's own funnel data - recency windows and behavioural-depth tiers per stage, a message and offer ladder for each stage, mutually exclusive audiences with exclusion logic, and per-stage frequency caps.
Lark OKR skill: manage objectives and key results, supporting viewing and editing OKR cycles, objectives, key results, alignments, quantitative indicators, and progress records.
Classify or explain Momentic test run results using Momentic MCP tools to understand failures and triage test outcomes.
Create custom skills for lark-cli to wrap Feishu API operations into reusable capabilities.
Improve code correctness using Momentic specs in the feature development process.
Build, debug, or review Cloudflare Workers invoked by the Forward action in Gateway HTTP policies, including the GatewayMiddleware entrypoint, Gateway types, context, and continuation.
Diagnose, classify, triage, and repair failing Momentic tests with MCP run tools, the Momentic CLI, and manual run artifacts.
Create, run, and maintain Momentic browser E2E tests and modules stored as *.test.yaml and *.module.yaml files.
Use when starting any conversation - establishes how to find and use skills, requiring skill invocation before ANY response including clarifying questions.
Evaluate a fragmented paid-ads account and recommend which campaigns and ad sets to merge, which splits to preserve, and how to migrate without resetting learning across the account - it plans the consolidation, it never executes it.
Design the org-wide revenue KPI framework at the macro level - which metrics matter at each org level from board to IC, how they roll up through a reconciling metric tree with explicit math, who owns each branch, which guardrail counter-metrics ride alongside each owned number, and how the set is gated by company stage and business model.
Turn a product brief and target audience into UGC-style short-form video ad scripts a creator can film - hook, body, CTA - with 3-5 hook variants per concept written as spoken line plus on-screen text plus opening visual, with delivery notes and disclosure lines.
Whole-repo audit for over-engineering, listing what to delete, simplify, or replace with stdlib/native equivalents.
Guides stable API and interface design for REST, GraphQL, module boundaries, and any public interface.
Flag ad formats that are a poor fit or commonly misused for a given objective and platform - formats the objective does not even expose, formats built for a different funnel stage, formats the team cannot produce - then, post-launch, separate a format problem from a creative or targeting problem.
Run a periodic, checklist-based hygiene audit over an active pipeline snapshot - stale deals (no stage, close date, or amount change, not logged touches) flagged against segment-specific stage medians, close-date push-count anomalies, and missing forecast-critical fields - producing an exception list with a disposition per flagged deal, a remediation plan, and a pass threshold.
Build and troubleshoot Cloudflare Basin analytics workflows with Basin Pipelines, Basin Catalog, and Basin SQL.
Adapt ad messaging for conversational and AI-answer ad surfaces - the one-shot, context-aware ad occupying a single response slot inside an AI assistant reply or answer-engine result, where the copy is either rendered verbatim or rewritten by a model from the landing page and feed.
Turn one core value proposition into genuinely distinct ad copy variants - headline, primary text, description, and CTA combinations - each labelled with angle, awareness stage, formula, and version so test results stay attributable.
Build a personalised, time-budgeted watch list of RevOps / Sales Ops information sources - revops podcasts, revops newsletters, revops communities, industry events, and revops people to follow - every source verified still active, with a periodic refresh routine that keeps the list fresh.
Before starting any RevOps or Sales Ops task, and at the start of every session on an ongoing RevOps project, run this first - it routes the task to exactly one skill of the revops-skills collection or says plainly that none fits, and bootstraps or resumes the project's shared, versioned context artifact so the next session starts warm instead of cold, ending in a short-list plus an ordered skill chain.
Optimizes application performance across frontend, backend, queries, and databases, with a focus on measurement-driven improvements.
Diagnose why an existing sales forecast is unreliable and recommend fixes - stage inflation and happy ears, sandbagging, deals without verifiable buyer evidence, stale or mass-pushed close dates, wrong forecast-category assignment, zombie and duplicate opportunities, late-created deals, manager roll-up overrides, and comp incentives that reward bias - separating data-quality from behavioral from genuine demand problems.
Design a company's revenue funnel model from scratch, at the macro level - the stage set, the unit of analysis (lead, buying group, account), the model purpose (process vs planning vs forecast), the cohort-based conversion assumptions behind the plan, and the ownership handoffs between marketing, sales, and CS.
Build the complete hiring packet for a RevOps or Sales Ops role - archetype and level decision, outcome scorecard, interview stage map with a competency question bank and anchored rating scales, a work-sample exercise with rubric and debrief, and a 30-60-90 ramp plan branched on seniority and archetype.
Plan a campaign that promotes an executive's or founder's existing organic posts as paid person-fronted ads - post selection, sequencing, audience and exclusions, permission and governance, budget, and measurement.
Set org-wide revenue data governance policy - which system is source of truth per object class (account, contact, opportunity, subscription, usage event, revenue metrics), how cross-team data contracts bind producers to consumers, where revenue metric definitions live, and who arbitrates disputes.
Design and operate CRM field-level governance - who owns each CRM field, which system is authoritative for it, how often it must be refreshed, and how the rules are enforced.
Audit existing sales pipeline stage definitions against buyer-verifiable milestones and flag the ones built on rep activity instead.
Trace where deals and revenue silently exit one specific funnel and size the loss in recoverable (never gross) dollars - untracked steps, unworked leads, manual handoffs, mid-funnel stalls, paper-process drops, billing and renewal misses - separating real leaks from healthy disqualification and data-capture gaps.
Build and advance a RevOps or Sales Ops career from the candidate's side - place the candidate on the ladder by scope rather than title, close competency gaps, build defensible evidence of structurally invisible work, and prepare the four exercises RevOps interview loops actually run.
Design the sales-to-CS handoff process after a deal closes - what data transfers, when, in what artifact, and who is accountable - producing a handoff spec with a gated closed-won trigger, a required handoff packet, timing SLAs, a kickoff meeting pattern, and a CS acceptance/rejection step.
Run a macro, periodic review of the full RevOps/GTM tool stack against the revenue workflows it serves and decide, tool by tool, what to keep, consolidate, replace, or cut - four-channel inventory, function-level overlap map, TIME scoring, a renewal-triggered action calendar, and re-sprawl governance.
Harvest every `ponytail:` comment in the codebase into a debt ledger, so deliberate shortcuts and deferrals get tracked instead of rotting into permanent debt.
The ponytail-help skill provides a quick-reference card for all ponytail modes, skills, and commands, displayed once without changing the current mode.
Design the deal desk approval chain and exception-handling process for non-standard B2B SaaS deals - a tiered discount approval matrix and delegation of authority across five concession levers (price, payment terms, services, contract risk, security), margin floor policy, exception intake, two SLA clocks with a sales escalation path, and precedent control.
Wind financial capability discovery and installation router that identifies and installs required data and workflow skills for tasks like market data, analysis, and decision-making.
Design, validate, and recalibrate a lead scoring model - fit and engagement signals, weighting, negative scoring and exclusions, decay, MQL/PQL threshold and tier setting, backtesting against closed-won/closed-lost outcomes, and governance; also diagnoses an existing broken model.
Design the assignment logic that routes inbound leads to sales reps - rule precedence and waterfall ordering, lead-to-account matching, territory assignment rules (geography, segment, industry, named accounts), round-robin variants (straight, weighted, capacity-based, availability-aware), fallback catch-all queues, SLA escalation and reassignment, and safe rollout of routing changes.
Simplify code for clarity while preserving exact behavior.
Show ponytail's measured impact as a compact scoreboard: less code, less cost, more speed, from the benchmark medians.
Design, validate, and govern a composite customer health score - product usage and engagement signals combined into one weighted, normalized, decayed, banded account score that flags both churn risk and expansion readiness, backtested against real churn outcomes and recalibrated.