Paid Ads Audit

What it does

When your agent uses it

• Auditing Google and Meta ad accounts from exported campaign data
• Reviewing paid media tracking and attribution gaps across channels
• Producing a partial audit when one platform's authentication or worker failed
• Finding prioritized spend opportunities and risks across ad platforms

Example prompts

• “Audit our Google Ads and Meta accounts using the CSV exports in ./ads-exports.”
• “Run a tracking and attribution audit for our LinkedIn and TikTok campaigns.”
• “The Reddit worker failed. Give me a partial ad audit covering the platforms that finished.”

Requirements

• Ad account exports, screenshots or authenticated access for each platform to audit

Workflow steps

11 steps, taken from the first numbered list in SKILL.md.

1. 1Read the main ads operating contract and thinking framework.
2. 2Create a run manifest with business context, date window, currency, timezone,
3. 3Normalize exports, screenshots, manual metrics, or authenticated reads into an
4. 4Discover active platforms. Confirm requested inactive or data-less platforms
5. 5Load each selected platform capability manifest, control registry, dated source
6. 6Dispatch independent platform workers and cross-platform workers in parallel.
7. 7Validate every result against the common finding schema. Retry one transient
8. 8Run deterministic scoring. Do not calculate or repair scores in the prompt.
9. 9Synthesize systemic findings across measurement, budget, creative, landing
10. 10Write one atomic run bundle and render the requested reports.
11. 11Verify bundle completeness, citations, privacy, and render integrity.

What it can do on your machine

Read from SKILL.md and the folder at commit ac21644. It shows what the files ask for, not the result of running them.

• Tool permissions

  Pre-approves nothing: there is no allowed-tools line, so your agent's usual permission prompts apply.

  From allowed-tools in the SKILL.md frontmatter.

• Runs code

  No scripts in the folder and no shell commands in SKILL.md (its code samples are json).

  From the folder's file list and the shell code blocks in SKILL.md.

• Network

  No URLs in SKILL.md.

  From URLs in SKILL.md, links to its own repository left out.

• Credentials

  Names no API keys, tokens, secrets or passwords.

  From names ending in _API_KEY, _TOKEN, _SECRET, _KEY or _PASSWORD in SKILL.md.

Context cost

Paid Ads Audit loads about 1.5k tokens when it runs. Until then it costs about 110 tokens; SKILL.md has 625 words of instructions outside code blocks.

Always · name and description, kept in context so the agent knows when to use it

~110

When it runs · the whole SKILL.md, loaded when a task matches

~1.5k

Estimates: characters ÷ 4, the usual rule of thumb; real counts depend on the model's tokenizer. Scripts and assets cost tokens only if the agent reads them.

Safety

Automated static check — not a guarantee. Review scripts before installing. It scans the text of SKILL.md for risky patterns (piping downloads into a shell, reading credential files, hidden Unicode, destructive commands); files beside SKILL.md are not scanned.

SKILL.md

The full file from AgriciDaniel/claude-ads at commit ac21644, republished under its MIT licence (© AgriciDaniel). 625 words, ~1,506 tokens.

name

ads-audit

description

Run a source-grounded paid-advertising audit for one or more of Google, Meta, YouTube, LinkedIn, TikTok, Microsoft, Apple, Amazon, Reddit, Pinterest, Snapchat, and X. Use for full ad checks, account health reviews, paid-media diagnostics, partial audits after authentication or worker failure, missing-platform weighting, beta-feature eligibility and scoring, spend audits, tracking audits, or prioritized opportunities and risks.

{
  "status": "ok",
  "platform": "google",
  "findings": [
    {
      "control_id": "G-EXAMPLE",
      "result": "pass|fail|unknown|not_applicable",
      "severity": "critical|high|medium|info",
      "confidence": "high|medium|low|none",
      "source_classification": "evidence_based|practitioner|contested|folklore",
      "observation": "What the supplied data demonstrates",
      "evidence_refs": ["input:...", "source:..."],
      "recommendation": "Decision-complete next action or null"
    }
  ],
  "contradictions": [],
  "missing_inputs": [],
  "recovery_hints": []
}

© AgriciDaniel, MIT. Rendered from Markdown: HTML in the file is shown as text, images as links, and headings moved down two levels. Raw file

Files

Just SKILL.md in skills/ads-audit of AgriciDaniel/claude-ads.

Open the folder on GitHubat commit ac21644