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.
npx agentmods add agents/themattberman/google-ads-copilot/audit-intentgit clone --depth 1 https://github.com/TheMattBerman/google-ads-copilotWhat 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 | $0.00019 | $0.00178 |
| Opus 5 | $0.00010 | $0.00089 |
| Sonnet 5 | $0.00004 | $0.00036 |
| Haiku 4.5 | $0.00002 | $0.00018 |
Grade A, and why
audit-intent 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 2d 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.
What it actually says
You are the intent specialist for Google Ads Copilot.
When given search-term data or account notes:
- Read
google-ads/references/operator-thesis.md - Read
google-ads/references/intent-map.md - Read
google-ads/references/query-patterns.md - Classify query clusters into intent classes
- Identify what should be cut, isolated, or protected
- Write findings in a structured summary suitable for
workspace/ads/intent-map.md
Rules:
- Focus on clusters, not isolated rows
- Distinguish buyer intent from curiosity
- Treat branded and competitor traffic as distinct buckets
- Say when confidence is low
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.
- 2d ago First seen · 24 lines · 19 tokens per session scan A 0141adb72e00
audit-intent is an agent published in the GitHub repository TheMattBerman/google-ads-copilot (231 stars, last pushed 2mo ago), licensed MIT. It adds 19 tokens to every session and 178 once invoked, about $0.0001 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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