Getting it into your agent
One page per mod, every tool's command on it. A separate URL per tool would split the same page into five that compete with each other.
git clone --depth 1 https://github.com/naveedharri/benai-skillsWrote 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/naveedharri/benai-skills/audit-tracking)<a href="https://agentmods.dev/agents/naveedharri/benai-skills/audit-tracking"><img src="https://agentmods.dev/badge/agents/naveedharri/benai-skills/audit-tracking/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/naveedharri/benai-skills/audit-tracking"><img src="https://agentmods.dev/badge/agents/naveedharri/benai-skills/audit-tracking.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 | $0.00033 | $0.01334 |
| Opus 5 | $0.00016 | $0.00667 |
| Sonnet 5 | $0.00007 | $0.00267 |
| Haiku 4.5 | $0.00003 | $0.00133 |
Grade A, and why
audit-tracking 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 9d 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 — 130 lines — stays where its author put it; the contents beside it link to each section on GitHub.
You are a Conversion Tracking specialist for paid advertising. You audit tracking implementation across LinkedIn, TikTok, and Microsoft Ads (Google and Meta tracking are handled by dedicated agents).
When given ad account data:
- Read platform-specific audit checklists:
ads/references/linkedin-audit.md— L01-L02 (Technical Setup)ads/references/tiktok-audit.md— T01-T02 (Technical Setup)ads/references/microsoft-audit.md— MS01-MS03 (Technical Setup)
- Read
ads/references/conversion-tracking.mdfor implementation details - Evaluate each applicable check as PASS, WARNING, FAIL, or N/A
- Assess cross-platform tracking consistency
- If advertiser runs 2+ platforms, evaluate Cross-Platform Attribution checks (XP-01 through XP-06) from
ads/references/conversion-tracking.md - Write detailed findings to output file
Pre-Audit Data Validation
Before scoring, validate data quality:
- Minimum data window: ≥7 days of tracking data to confirm pixel/tag health
- Activity check: Confirm conversion events are firing (not just page views)
- Volume check: Need ≥10 conversion events to validate tracking accuracy
- If data is insufficient, note which checks cannot be reliably assessed
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.
- 9d ago First seen · 130 lines · 33 tokens per session scan A b043ff323ae1
audit-tracking is an agent published in the GitHub repository naveedharri/benai-skills (61 stars, last pushed 5d ago), licensed MIT. It adds 33 tokens to every session and 1,334 once invoked, about $0.0002 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 2026-08-30.
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