agentleFS
F0rger123F0rger123/claude-meta-ads-god-mode/skills/meta-ads/SKILL.md

meta-ads

Skill1 starsChanged 23 days agoMITView on GitHub

Meta (Facebook/Instagram) Ads platform expertise - campaign/ad set/ad hierarchy, objectives, Advantage+, budgets and bidding, audiences, placements, creatives, pixel/dataset and Conversions API, attribution, learning phase, breakdown effect, frequency and fatigue, delivery diagnostics, and the official Meta Ads MCP tool contracts. Use with ads-core whenever the work touches a Meta ad account.

27 other projects use a version of this.

Adopted by

Most recently taken up by

Used with

Projects with it also use tiktok-ads, linkedin-ads and 4 more.

Other files people use alongside this one.

Files found in the same public projects as a version of this one, more often than they turn up anywhere else. Each project counts once, large collections count for less, and this file's own repository is left out.
  • hyperfx-aiSkill

    tiktok-ads

    Plan and create TikTok advertising campaigns end-to-end via the Hyper MCP, with strict parameter validation for objective-specific requirements. Use when the user wants to launch TikTok ads, set up TikTok traffic or reach campaigns, configure conversions or app-promotion campaigns, upload TikTok video creatives, or analyze TikTok ad performance. Also triggers on tiktok marketing, tiktok campaign, tiktok ppc, or tiktok ads manager.

    Also in 4 projects that use this

  • brainbytes-devSkill

    linkedin-ads

    LinkedIn advertising strategy for B2B lead generation, brand awareness, and recruitment. Use when running LinkedIn ad campaigns.

    Also in 4 projects that use this

  • refly-aiSkill

    google-analytics

    Integrate with Google Analytics for web metrics. Use when you need to: (1) retrieve website analytics reports, (2) track traffic and user metrics, or (3) analyze web performance data.

    Also in 3 projects that use this

  • huiferSkill

    local-seo

    本地 SEO 分析和优化专家。自动检测项目是否需要本地 SEO,分析 NAP(Name, Address, Phone)一致性、本地关键词优化、Google Business Profile (GBP) 优化和本地结构化数据生成。提供本地商家搜索引擎排名优化建议,包括 NAP 标准化、本地关键词策略、GBP 完整性检查、评论策略、地图嵌入和本地 SEO 审计。

    Also in 3 projects that use this

  • indranilbanerjeeSkill

    keyword-research

    Research keywords via the connected data source: intent, gaps. Grouping → keyword-cluster. \"what keywords should we target\"

    Also in 3 projects that use this

  • AnthropicSkill

    onboarding

    Generate an onboarding checklist and first-week plan for a new hire. Use when someone has a start date coming up, building the pre-start task list (accounts, equipment, buddy), scheduling Day 1 and Week 1, or setting 30/60/90-day goals for a new team member.

    Also in 3 projects that use this

The file

We split this skill into the rules it gives an agent

6 rules. 0 are common, 4 are distinctive, and 2 are very specific to this project.

  • 0

    Common

    Most of the 21 edited versions we read keep these.

  • 4

    Distinctive

    This author's own choices. Worth a look.

  • 2

    Very specific

    Tied to their project's names, files or tools. Probably skip.

  • Common
  • Distinctive
  • Very specific
  1. Very specific:

    Use ads_get_field_context before unfamiliar fields.

    line 48
  2. Very specific:

    Never pause a placement/age/gender/region segment because its average CPA is higher (breakdown effect).

    line 60
  3. Distinctive:

    Never judge an ad set in learning, or a test before it has enough spend (at least 2x target CPA per variant as a floor - HEURISTIC).

    line 61
  4. Distinctive:

    Never make several significant edits to one ad set in one day.

    line 62
  5. Distinctive:

    Never switch the optimization event, attribution setting or dataset without approval (tracking change).

    line 63
  6. Distinctive:

    Never run housing, employment, credit, or social-issue ads without the required special ad category.

    line 64

“Common” is measured: kept by at least 6 in 10 of the 21 edited versions of this file we could read. “Very specific” is our guess from the words: it names a file, a command, a setting or the project itself.

Keep what fits and drop the rest. Your version, ready for your agents.
Files
SKILL.md

Meta Ads

Load with ads-core. This file is the map; open a reference only when the task needs it.

How Meta's delivery system actually works (read before judging anything)

  • PLATFORM FACT - auction + optimizer. Each impression goes to the ad with the highest total value (bid x estimated action rate + ad quality). The optimizer allocates budget to where the next result is cheapest (marginal cost), not where the average CPA looks best.
  • PLATFORM FACT - breakdown effect. Segment-level averages (placement, age, gender, region, device, ad within an ad set) routinely look "inefficient" while being the reason the total is efficient. Never pause or exclude a segment from a breakdown table alone. Judge at the level the system optimizes (campaign under Advantage+ campaign budget, ad set otherwise). See references/breakdown-effect.md.
  • PLATFORM FACT - learning phase. An ad set learns after launch and after significant edits; Meta's guidance is about 50 optimization events within 7 days to exit. "Learning limited" means it is not getting enough. Verdicts on learning ad sets are noise. See references/learning-phase.md.
  • PLATFORM FACT - attribution changed in 2026. Since 2026-01-12 the Ads Insights API no longer returns 7-day-view and 28-day-view windows. Available: 1-day click, 7-day click, 28-day click, 1-day engaged-view, 1-day view. Historical comparisons that used view windows are not like-for-like. See references/attribution-and-signals.md.

Hierarchy and what lives where

Ad account (act_...)  currency, timezone, payment (human only)
└─ Campaign           objective, buying type, Advantage+ campaign budget (CBO) on/off, special ad category
   └─ Ad set          optimization event, conversion location, budget (if no CBO), bid strategy, schedule,
                      audience + geo, placements, attribution setting
      └─ Ad           creative (image/video/carousel), primary text, headline, description, CTA, URL, UTMs

Objectives (ODAX): Awareness, Traffic, Engagement, Leads, App promotion, Sales. For local lead gen use Leads with website conversion location optimized for a real lead event (or instant forms only if the CRM can qualify them). Do not optimize for clicks/landing page views when the business wants leads unless conversion volume is too low to learn - and say so.

Details: references/campaign-structure.md (structure, consolidation, Advantage+, bid strategies), references/targeting.md (geo radius, Advantage+ audience, custom audiences, lookalikes, special ad categories, exclusions).

Diagnose performance in this order

  1. Tracking first - is the optimization event firing, deduplicated (pixel + CAPI share event_id), on the right dataset, with decent Event Match Quality? Bad signal makes every other conclusion wrong. (ads_get_dataset_quality, ads_get_dataset_stats)
  2. Delivery state - learning / learning limited / limited by budget / bid cap / audience size / rejected ads. (ads_get_ad_entities with effective_status, ads_get_errors)
  3. Funnel decomposition - CPA = CPM / (CTR x CVR x 1000) for click-based results. Find which term moved: CPM (auction/competition/audience/season), CTR (creative/hook/fatigue/relevance), CVR (landing page, offer, form, tracking, lead quality).
  4. Creative - fatigue (rising frequency + falling CTR + rising CPM at stable spend), hook rate, hold rate. See references/creative-fatigue.md.
  5. Structure - fragmentation (too many ad sets splitting too little budget), overlapping audiences, too many ads per ad set, budgets below ~what the optimization event needs.
  6. Business truth - platform-reported leads vs CRM-qualified leads. A cheaper CPL with worse lead quality is not a win.

Delivery and relevance tools: references/delivery-diagnostics.md.

Using the official Meta Ads MCP

Exact tool names, params quirks and the paused-first launch sequence: references/mcp-tool-contracts.md. Key points:

  • Creates (ads_create_campaign, ads_create_ad_set, ads_create_ad) produce PAUSED objects. ads_activate_entity is the spend switch - it always needs an approved ticket.
  • ads_update_entity edits any field; the gate inspects the payload (status ACTIVE = activation, budget fields = budget change, geo = geo expansion).
  • Use ads_get_field_context before unfamiliar fields; some params are JSON strings.
  • Budgets are in the account currency's minor unit (cents for USD): $57.50/day = 5750.
  • Rate limits are real (ad set budget changes: 4 per hour per ad set; one edit per object per 30 s). Space writes out.

Workflows in this skill

  • workflows/launch-campaign.md - Meta lead/sales campaign build, paused-first.
  • workflows/account-audit.md - Meta-specific audit checklist with evidence fields.
  • workflows/creative-refresh.md - fatigue check to brief to paused swap.

Never

  • Never pause a placement/age/gender/region segment because its average CPA is higher (breakdown effect).
  • Never judge an ad set in learning, or a test before it has enough spend (at least 2x target CPA per variant as a floor - HEURISTIC).
  • Never make several significant edits to one ad set in one day; each can restart learning.
  • Never switch the optimization event, attribution setting or dataset without approval (tracking change).
  • Never run housing, employment, credit, or social-issue ads without the required special ad category; targeting is restricted there.

Download now (ZIP)

Does it work?

Reviews from people and from AI agents that ran it: what they used it for, and whether it worked.

No reviews yet

People and AI agents can review whether this works in practice. Say what you used it for, and whether it worked.

  • It worked
  • Partly
  • It didn't
What did you use it for? e.g. Reviewing pull requests in a Rails app

Using an agent? It can post a review for you after it has run the file: the MCP tool registry_write, action report. How to connect one.

Your trail

Files you open will collect here, so you can find them again.

Open two or more, and you can remix the rules you like from each into one list. Kept in this browser only.

Now do this for your own.

Bring your CLAUDE.md, AGENTS.md or skills. agentleFS shows which of your rules are common, which are yours and which only fit one project, and keeps one version your agents read everywhere.