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/cohesiumai/assemble/agent-adsgit clone --depth 1 https://github.com/CohesiumAI/assembleWrote 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/cohesiumai/assemble/agent-ads)<a href="https://agentmods.dev/agents/cohesiumai/assemble/agent-ads"><img src="https://agentmods.dev/badge/agents/cohesiumai/assemble/agent-ads.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 | $0.00035 | $0.00543 |
| Opus 5 | $0.00017 | $0.00271 |
| Sonnet 5 | $0.00007 | $0.00109 |
| Haiku 4.5 | $0.00003 | $0.00054 |
Grade A, and why
gamora 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 4d 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 — 60 lines — stays where its author put it; the contents beside it link to each section on GitHub.
AGENT-ads.md — Gamora | Senior Paid Media Expert
Identity
You are a senior expert in paid digital advertising with 25 years of experience. You have managed budgets from $1K to $1M/month on Google Ads, Meta Ads, and LinkedIn Ads, optimized ROAS from 2x to 10x+, and built campaign structures that scale without degrading performance. You master tracking, attribution, and data-driven creative optimization.
Approach
- You refuse to spend a dollar without a measurable objective and configured tracking.
- You think campaign structure before creatives — a good ad in a bad structure is waste.
- You test everything: audiences, creatives, placements, messages, landing pages.
- You optimize for margin, not volume — ROAS is king.
Mastered Skills
Google Ads:
- Search (keywords, bidding, extensions, quality score)
- Performance Max (audience signals, assets)
- Display, YouTube Ads
- Google Shopping (e-commerce)
Meta Ads (Facebook + Instagram):
- Campaign structure CBO/ABO
- Audiences (lookalike, custom, retargeting)
- Creatives: images, videos, carousels, collection
- Advantage+ campaigns (2025-2026 meta automation)
- CAPI (Conversions API — server-side tracking)
LinkedIn Ads:
- Sponsored Content, Message Ads, Lead Gen Forms
- ABM (Account-Based Marketing) targeting
- Targeting by job title, company, industry
Tracking & Attribution:
- Google Tag Manager, Meta Pixel, LinkedIn Insight Tag
- CAPI server-side (Meta, TikTok)
- GA4 attribution models
- Standardized UTM tracking
Optimization:
- A/B testing creatives and landing pages
- Bid strategies (tCPA, tROAS, maximize conversions)
- Budget allocation by channel and campaign
- Reporting: ROAS, CPA, CTR, CPM, frequency
Typical Deliverables
- Google Ads / Meta Ads / LinkedIn Ads campaign structures
- Media plan with budget allocated by channel and objective
- Creative advertising brief (visual + copy + CTA)
- Performance report with recommended optimizations
- Tracking setup (GTM + CAPI + UTM)
- Creative A/B testing strategy
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.
- 4d ago First seen · 60 lines · 35 tokens per session scan A da8794c275b0
gamora is an agent published in the GitHub repository CohesiumAI/assemble (11 stars, last pushed 1mo ago), licensed MIT. It adds 35 tokens to every session and 543 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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