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ads-plan

依据业务配置档、经济学指标与账户现状,从第一原则规划广告目标、渠道角色与排除、活动架构、受众、预算与节奏、创意系统、测量、实验、政策控制与运营节奏,并按上线前、学习期、优化、扩量分阶段为每个动作指定负责人、时间、依赖、护栏、成功度量与回滚条件,最终给出结构化 JSON 和人类可读计划;计划仅为建议,需经启动或优化变更门控才能成为账户改动。

AgriciDaniel
热度 0.00
最近更新 2026-10-19 00:59:30
分类:营销依赖:内部调用大模型 / 读写文件应用场景:市场分析 / 报告撰写

安装技能

复制下面的话术发给你的 Agent,它会通过 secure-skills 检索并安装该技能。

执行命令安装此 skill: npx secure-skills-cli add agricidaniel/claude-ads/ads-plan
Metadata
name
ads-plan
description
Create a professional paid-advertising strategy covering objectives, economics, platform selection, campaign architecture, audiences, budget, creative, measurement, experiments, governance, rollout, and reporting. Use for ad plan, media plan, PPC strategy, paid-social strategy, campaign architecture, advertising roadmap, or channel planning.

Paid Media Plan

  1. Read the setup profile, business economics, evidence, current account state, and relevant industry template as optional input.
  2. Define objective, customer, offer, conversion, value, constraints, geography, regulated category, time horizon, and success criteria.
  3. Evaluate channel roles and exclusions from first principles; do not require every supported platform. For a channel outside the twelve-platform contract, load ads/references/additional-platforms.md (resolve it from the plugin root, the directory that holds ads/ and skills/, or from the skills directory in a standalone install) and return a research lead unless its current buying, eligibility, measurement, and creative evidence is present.
  4. Before proposing Meta budgets, learning-phase expectations, bidding, consolidation, or performance forecasts, collect the account, Pixel, and conversion cold-start dimensions per the contract in skills/ads-meta/SKILL.md. When any dimension is cold or unknown, plan for measurement validation, explicit creative hypotheses, staged reversible tests, and confidence labels; do not apply mature-account benchmarks to missing history.
  5. Specify campaign architecture, audience strategy, creative system, budget and pacing, measurement, experiments, policy controls, and operating cadence.
  6. Phase prerequisites before launch, learning, optimization, and scale.
  7. Assign every action an owner, timing, dependency, guardrail, evidence, success measure, and rollback or exit condition.
  8. Return canonical JSON and render the requested human plan.

A plan is advisory. It becomes an account change only through launch or optimize mutation gates.