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 skills add TheMattBerman/google-ads-copilot --skill google-ads-plangit clone --depth 1 https://github.com/TheMattBerman/google-ads-copilotWrote 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/skills/themattberman/google-ads-copilot/google-ads-plan)<a href="https://agentmods.dev/skills/themattberman/google-ads-copilot/google-ads-plan"><img src="https://agentmods.dev/badge/skills/themattberman/google-ads-copilot/google-ads-plan.svg" alt="Measured on agentmods" 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 | $0.00047 | $0.00854 |
| Opus 5 | $0.00023 | $0.00427 |
| Sonnet 5 | $0.00009 | $0.00171 |
| Haiku 4.5 | $0.00005 | $0.00085 |
Grade A, and why
google-ads-plan 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 8d 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 — 102 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Google Ads Plan
This skill is for building from scratch or cleaning up a messy account before the mess compounds.
Read first:
google-ads/references/operator-thesis.mdgoogle-ads/references/intent-map.mdgoogle-ads/references/query-patterns.mdgoogle-ads/references/structure-playbook.mdgoogle-ads/references/rsa-playbook.mdgoogle-ads/references/budget-playbook.mdgoogle-ads/references/deliverable-templates.mdgoogle-ads/references/benchmarks.md
Read workspace if available:
workspace/ads/account.mdworkspace/ads/goals.mdworkspace/ads/intent-map.mdworkspace/ads/learnings.md
Data Acquisition
Connected Mode (for rebuilds)
If the account already exists and has data, pull audit-level queries to understand current state before planning the rebuild. Use the same queries as the audit skill.
Export Mode / New Account
If building from scratch:
- No account data needed
- Gather: business model, offer, target audience, budget, geographic targets, existing keyword research
- Optionally: competitor URLs, existing landing pages, previous performance data
Planning Mode (no existing account)
For brand-new accounts, this skill runs without MCP at all. The intelligence comes from:
- Business context gathered from the user
- Intent Map framework (hypothesized, validated later)
- Reference playbooks for structure, copy, and budget
Process
- Announce mode (connected rebuild / new account planning).
- Clarify business model, offer, KPI, and budget reality.
- Identify the most important intent buckets.
- Design campaign architecture around commercial meaning, not cosmetic neatness.
- Define what should be split, merged, or excluded from the start.
- Recommend:
- Campaign structure
- Ad group logic
- Negative logic (day-one exclusions)
- RSA/message direction
- Budget posture
- Write planning notes to workspace memory.
Core Planning Questions
- What search intents matter enough to deserve their own buckets?
- Which intents should never share one bid/copy/LP bucket?
- What should be excluded from day one?
- What does the budget realistically support?
- Where should simplicity beat ideal segmentation?
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.
- 8d ago First seen · 102 lines · 47 tokens per session scan A fa20b40c88f5
google-ads-plan is a skill published in the GitHub repository TheMattBerman/google-ads-copilot (231 stars, last pushed 2mo ago), licensed MIT. It adds 47 tokens to every session and 854 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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