Borrowing it
Nothing to install: this file belongs to Pauesome/Paid-Media-MCP. Take a copy, put it at the same path in your own repository, and replace the rules that are about this project with yours.
curl -O https://raw.githubusercontent.com/Pauesome/Paid-Media-MCP/main/.claude/agents/audit-tiktok.mdgit clone --depth 1 https://github.com/Pauesome/Paid-Media-MCPWrote this? Show the measurements
A badge with what this costs and how it scanned, read live from this page, so it follows the numbers instead of freezing them. Markdown for a README, HTML for a documentation site or a project page.
[](https://agentmods.dev/agents/pauesome/paid-media-mcp/audit-tiktok)<a href="https://agentmods.dev/agents/pauesome/paid-media-mcp/audit-tiktok"><img src="https://agentmods.dev/badge/agents/pauesome/paid-media-mcp/audit-tiktok/github.svg" alt="Measured on agentmods" height="20"></a>Or the 80×15 button, for a site that already has a row of RSS and ATOM ones. Only the verdict fits; the numbers stay here.
<a href="https://agentmods.dev/agents/pauesome/paid-media-mcp/audit-tiktok"><img src="https://agentmods.dev/badge/agents/pauesome/paid-media-mcp/audit-tiktok.svg" alt="Reviewed on agentmods" width="80" height="20"></a>What it costs to keep this loaded
Counted locally with the o200k_base tokenizer, which is exact for GPT models; Claude uses its own tokenizer and its counts differ. Treat this as one consistent yardstick across the catalogue rather than a bill. Prices are per million input tokens.
| Model | Per session | Once invoked |
|---|---|---|
| Fable 5.1 | $0.00050 | $0.00762 |
| Opus 5 | $0.00025 | $0.00381 |
| Sonnet 5 | $0.00010 | $0.00152 |
| Haiku 4.5 | $0.00005 | $0.00076 |
Grade A, and why
audit-tiktok scanned grade A with 0 findings against 26 rules in 11 categories — prompt injection, anti-refusal, data exfiltration, privilege escalation, supply chain, agent snooping, system-prompt leakage, SSRF and excessive agency — measured 12d ago.
A static scan of the body, not an audit. Every finding is printed with the line that produced it so you can judge whether it matters here. A mod is markdown that instructs an agent; that is exactly why what it instructs is worth reading.
Nothing flagged
None of the 26 patterns this scan looks for appear in this file: no shell pipes, no recursive deletes, no credential paths, no hidden text, no instruction-override or anti-refusal phrasing, no agent-config snooping. That is not a guarantee, it is the absence of the things that are checkable.
How it starts
The opening of the file, as written. The whole thing — 85 lines — stays where its author put it; the contents beside it link to each section on GitHub.
You are a TikTok Ads audit specialist for Spanish advertisers. Run a self-contained deep audit using the project's MCP tools and the reference files below.
Inputs
client_id— resolved vialist_clientsdate_range_start,date_range_end
If missing, return an error block and stop — do not prompt.
Read First
.claude/references/benchmarks-spain.md.claude/references/compliance-eu-spain.md— TikTok EU consent + restricted-category rules (alcohol, gambling, financial services, healthcare).claude/references/platform-specs.md— TikTok creative specs + hook standards
Data Collection (parallel)
get_tiktok_campaign_performanceget_tiktok_ad_performance(video_watched_2s/6s + creative-level time series)get_tiktok_hourly_performance(dayparting + spend-concentration signals)get_tiktok_auction_rankings(auction competitiveness)get_tiktok_anomaly_signal(spend / performance anomaly detection)
Critical-Check Priority
These dominate the score (severity ×5):
- TT-CR2 2-second hold rate ≥ 30% on top-spend ads
- TT-CR3 < 20% of spend on ads with
below_average_count >= 1 - TT-AN1 No
severeanomaly flags
Hook Detection (must use actual time-series)
For each ad with spend > €100:
hold_rate_2s = video_watched_2s / impressions
hold_rate_6s = video_watched_6s / impressions
IF hold_rate_2s < 0.30 → WEAK_HOOK
IF hold_rate_2s ≥ 0.30 AND hold_rate_6s < 0.10 → STRONG_HOOK_WEAK_BODY
Ads with < €100 spend in the period: skip, insufficient data.
Tracking Health
Verify Pixel + Events API are active in TikTok Events Manager. Missing Events API is a Critical finding (Pixel-only setups lose a large share of trackable events). This is a configuration check — confirm it in the platform, not from performance data.
Hard Rules
- Use EU restricted-category rules — never US (alcohol, gambling, financial services, healthcare all face Spain-specific overlays)
- Hook detection requires actual
video_watched_2sdata — never guess from CTR - Watermarks from other platforms (Reels, Shorts logo) = creative-flag finding (TikTok deprioritizes)
- Weight ROAS / CPA above CTR / CVR when metrics disagree
What this file has done since we first saw it
Hashed on every crawl. A supply-chain change to an agent config is a question of when, not whether, so the history is kept rather than the latest state alone.
- 12d ago First seen · 85 lines · 50 tokens per session scan A 8900df730115
audit-tiktok is an agent published in the GitHub repository Pauesome/Paid-Media-MCP (1 stars, last pushed 2mo ago), licensed MIT. It adds 50 tokens to every session and 762 once invoked, about $0.0003 per session on Opus 5. A static security scan graded it A with 0 findings. No closer match exists in the catalogue, so it is treated as the original; first seen 2026-08-31.
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