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 hashgraph-online/awesome-codex-plugins --skill wilco-ad-setupgit clone --depth 1 https://github.com/hashgraph-online/awesome-codex-pluginsWrote 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/hashgraph-online/awesome-codex-plugins/wilco-ad-setup)<a href="https://agentmods.dev/skills/hashgraph-online/awesome-codex-plugins/wilco-ad-setup"><img src="https://agentmods.dev/badge/skills/hashgraph-online/awesome-codex-plugins/wilco-ad-setup.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 | $0.00048 | $0.00726 |
| Opus 5 | $0.00024 | $0.00363 |
| Sonnet 5 | $0.00010 | $0.00145 |
| Haiku 4.5 | $0.00005 | $0.00073 |
Grade A, and why
wilco-ad-setup 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 yesterday.
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 — 118 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Wilco Ad Setup
Inputs
Ask once for:
- main keyword
- product SKU
- optional product name
- optional budget level
- optional output path
Defaults:
- budget level: conservative
- output directory:
./artifacts/launchfast/campaigns/
Strategy
Wilco’s model favors:
- exact match only for manual keyword campaigns
- tight budget isolation
- proven converting keywords
- strong emphasis on purchase rate and competitor coverage
Workflow
1. Market research
Run:
research_products(keyword="<main_keyword>", focus="balanced", product_limit=20)
Capture top 10-12 ASINs and market context.
2. Keyword research
- batch ASINs in groups of 3-4
- prefer parallel tool calls when practical
- do not require delegation
Use:
amazon_keyword_research(asins=[...], limit=50, min_search_volume=300)
3. Score keywords
Rank keywords with a weighted score based on:
- purchase rate
- competitor coverage
- search volume
- relevance
Prioritize keywords where multiple competitors already rank well.
Select:
- Exact A: top converters
- Exact B: volume converters
- Exact C: niche converters
- Product targets: top competitor ASINs
4. Generate bulksheet
Create:
- Auto campaign
- Product targeting campaign
- 3 exact-match manual campaigns
Use Python csv.writer and write to:
Use this exact Amazon Bulksheets 2.0 header and column order:
Product,Entity,Operation,Campaign Id,Ad Group Id,Portfolio Id,Ad Id,Keyword Id,Product Targeting Id,Campaign Name,Ad Group Name,Start Date,End Date,Targeting Type,State,Daily Budget,sku,asin,Ad Group Default Bid,Bid,Keyword Text,Match Type,Bidding Strategy,Placement,Percentage,Product Targeting Expression,Audience ID,Shopper Cohort Percentage,Shopper Cohort Type
Deterministic campaign layout:
- Auto: 1 campaign, 1 ad group, 1 product ad, 4 auto targeting rows
- Product targeting: 1 campaign, 1 ad group, 1 product ad, up to 10 ASIN target rows
- Exact A: 1 campaign, 1 ad group, 1 product ad, up to 5 exact-match keywords
- Exact B: 1 campaign, 1 ad group, 1 product ad, up to 5 exact-match keywords
- Exact C: 1 campaign, 1 ad group, 1 product ad, up to 5 exact-match keywords
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.
- yesterday First seen · 118 lines · 48 tokens per session scan A cec358f75f60
wilco-ad-setup is a skill published in the GitHub repository hashgraph-online/awesome-codex-plugins (935 stars, last pushed today), licensed Apache-2.0. It adds 48 tokens to every session and 726 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 2026-09-05.
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