Claude AdsAn open-source paid-media skill pack for Claude Code: 12 ad platforms, a full audit-to-report lifecycle, deterministic scoring, and versioned JSON reports, read-only by default with no per-account fee.
Repo
Claude Ads
An open-source paid-media skill pack for Claude Code: 12 ad platforms, a full audit-to-report lifecycle, deterministic scoring, and versioned JSON reports, read-only by default with no per-account fee.
The broadest paid-media skill for Claude Code: 12 ad platforms and a full audit-to-report lifecycle, MIT and free. Two things set it apart. It is read-only and draft-first by default (every live-write capability ships disabled in v2), and, unlike the same author's claude-seo, it explicitly forbids injecting a self-promo footer into your deliverables. The catches are the ordinary open-source ones: one maintainer, code that runs locally near your ad accounts, and a fully current build that lives partly behind a paid Skool community.
Great for
Agencies, consultants, and in-house performance teams who want fast, repeatable, evidence-backed audits and plans across many ad platforms inside Claude Code, without a $5k-a-month agency retainer or a per-account SaaS fee.
The catch
It executes Python and shell locally and reads ad-account data, so treat it like any code you run. Read skills/SKILL.md, security-check the repo, and expect to bring your own platform credentials before it touches a client's account.
Bottom line
The most complete free paid-ads skill for Claude Code, and a visibly more honest one than its SEO sibling: no hidden footer, writes off by default. It is one maintainer's project that cooled after the July v2, so vet it, keep a human on the recommendations, and it earns a slot in the stack.
Install/plugin marketplace add AgriciDaniel/claude-ads then /plugin install claude-ads@ai-marketing-hub-claude-ads, or git clone plus bash install.sh --source=local
LicenseMIT
LanguagePython (Markdown skill files)
Maintained byAgrici Daniel, single maintainer, plus the AI Marketing Hub Pro Skool community
Harnesses supportedClaude Code (canonical); Codex, Gemini, Cursor, Windsurf, and Goose where the runtime supports skill files
Watch out forExecutes code locally and reads ad accounts, needs your own platform credentials, and the fully current build lives partly behind a paid Skool community
12-platform coverageGoogle, Meta, YouTube, LinkedIn, TikTok, Microsoft, Apple, Amazon, Reddit, Pinterest, Snapchat, X
Evidence-backed account auditDated sources, explicit confidence, conductor-and-worker parallelism, partial-run honesty
Campaign / channel / budget planningYes
Search-term, negative-keyword & targeting analysisVia the audit and plan skills, plus audience and competitor references
Creative production (copy, image, video, product photo)ads-create, ads-creative, and ads-photoshoot briefs and assets
Experiment / A-B test designYes
Measurement, attribution & server-side trackingYes
Monitoring (pacing, delivery, fatigue, policy)Yes
Reporting: versioned JSON to Markdown / HTML / PDFWeasyPrint plus Pango for the PDF path
Live account changes (writes)Read-only by default; all mutation capabilities ship disabled in the v2 public release, drafts only
Deterministic health scoreScoring engine exists (scoring.py), but a disabled or unapproved platform profile yields no score and coverage under 60% reads as insufficient
Refuses to inject a self-promo footerSKILL.md forbids promo copy in deliverables and makes community links opt-in, unlike the author's claude-seo
What it does
- Audits paid-media accounts across 12 platforms (Google, Meta, YouTube, LinkedIn, TikTok, Microsoft, Apple, Amazon, Reddit, Pinterest, Snapchat, X) from authorized exports or account reads, returning dated evidence and explicit confidence
- Plans campaigns, channels, budgets, measurement, and experiments, and drafts copy, image, video, and product-photo briefs through dedicated create, creative, and photoshoot skills
- Runs a conductor-and-worker architecture where one conductor owns scope and aggregation, bounded workers return schema-valid findings, and a required-worker failure marks the run partial instead of presenting a fake complete audit
- Produces a versioned JSON run bundle as the canonical result, then renders Markdown, HTML, and optional PDF from the same validated data via WeasyPrint
- Monitors pacing, delivery, tracking, creative fatigue, policy, and performance, and reports missing data, stale sources, contradictions, and partial failures
- Drafts account changes with launch and optimize in draft mode, keeping live writes disabled until a specific capability, explicit IDs, a before-and-after diff, owner approval, an idempotency key, a verification window, and a rollback record are all in place
- Installs as a Claude Code plugin or through a local install.sh that builds a managed Python 3.11 or 3.12 environment, with optional Playwright browser capture and WeasyPrint PDF rendering
What it can’t do
- Apply live account changes out of the box; the v2 public release ships every write and mutation capability disabled, so it audits and drafts changes for review, and never optimizes a live account on its own
- Score a platform it has not been given an approved profile for, since a disabled or unapproved platform produces no health score and evidence coverage under 60% reads as insufficient
- Pull data without your own authorized exports or platform API credentials; there is no proprietary benchmark or competitive-intelligence index bundled in
- Replace an experienced media buyer's judgment; practitioners note an LLM tends to confirm the mainstream take and needs a human watching every recommendation
- Run itself hands-off, since audits execute Python and shell in your environment, so setup, upgrades, and reading the source stay your job
- Permanently delete campaign objects, which v2 does not support by design
Pros & cons
Pros
- Broadest paid-media coverage in one MIT-licensed skill, spanning 12 ad platforms plus a full lifecycle of audit, plan, create, launch, monitor, optimize, experiment, and report
- Free skill on top of a Claude Code subscription, against the $5k or more a month many agencies charge for equivalent account audits
- Read-only and draft-first by default, with a six-gate approval path (capability, IDs, diff, owner approval, idempotency plus rollback, precondition check) before any live write
- Honest run semantics: versioned JSON as the source of truth, partial-run flagging, and evidence-coverage tiers in place of a single vanity score
- Explicitly forbids appending promo copy to deliverables and makes community links opt-in, a direct fix for the self-promo-footer problem that hit the same author's claude-seo
- Cross-runtime by design, with Claude Code as the canonical host and the same skill files running on Codex, Gemini, Cursor, Windsurf, and Goose where supported
Cons
- Single maintainer (one author plus dependabot), so bus factor and support lean on one person and a paid Skool community
- Executes Python and shell locally and reads ad accounts, so the blast radius is real; Claude Code itself declined to auto-install it without a manual security review
- Ships from two homes, with the AI Marketing Hub Pro Skool mirror getting early access, so the most current build is tied to a paid community
- Full value needs your own platform credentials and authorized exports; the free tier alone gives you the engine, not the data
- Momentum cooled after the July 2026 v2 launch, with no public release in roughly six weeks as of late August
- The 8.5k stars draw the usual skepticism that stars and install counts say little about who actually runs a skill in production
2 mixed1 critical
What the community says
Claude doesn't install it automatically. It told me: that falls under downloading or executing files from untrusted sources, a rule I follow even with your explicit go-ahead. It's not that I think this specific repo is malicious, I just can't vet it, and the blast radius (account-level ad changes) is real. So I didn't download yet, but I would love to.
Most of these are Claude Code skills or wrappers around the same handful of frameworks, and the GitHub star counts tell you basically nothing about whether anyone actually runs them in anger.
I installed superpowers, frontend design and claude-seo, claude-blog, claude-ads from AgriciDaniel. The goal is to help me improve my ecommerce with better product descriptions, boost the store in SEO, and connect to free tools like GSC, GA4, FB Ads or Google Ads to help me make ads. I'm 42 and never been a developer, so many things I read are pure magic.
11 sourcesWhere this page’s facts came from. Open the receipts.
- 1GitHub repo (AgriciDaniel/claude-ads)
- 2GitHub API, repo metadata (stars, license, language, created and pushed dates)
- 3Claude Ads README (12 platforms, commands, install, architecture, account safety)
- 4Capability manifest, showing all write and mutation capabilities disabled by default
- 5ads/SKILL.md, which forbids promo copy in deliverables and makes community links opt-in
- 6Claude Ads homepage
- 7Claude Ads v2.0.1 release notes (506 tests, 12 platforms, six-gate write safety)
- 8Reddit r/ClaudeAI, is claude-ads safe, Claude Code declines to auto-install
- 9Reddit r/WebAfterAI, open-source AI repo roundup featuring Claude Ads and star-count skepticism
- 10Reddit r/ClaudeAI, real ecommerce owner installing claude-ads
- 11YouTube, maintainer livestream shipping Claude Ads v2
Watch it work
Real tutorials and reviews from YouTube, not ours.