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 launchfast-ppc-researchgit 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/launchfast-ppc-research)<a href="https://agentmods.dev/skills/hashgraph-online/awesome-codex-plugins/launchfast-ppc-research"><img src="https://agentmods.dev/badge/skills/hashgraph-online/awesome-codex-plugins/launchfast-ppc-research.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 | $0.00066 | $0.00808 |
| Opus 5 | $0.00033 | $0.00404 |
| Sonnet 5 | $0.00013 | $0.00162 |
| Haiku 4.5 | $0.00007 | $0.00081 |
Grade A, and why
launchfast-ppc-research 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 — 129 lines — stays where its author put it; the contents beside it link to each section on GitHub.
LaunchFast PPC Research
Inputs
If needed, ask once for:
- 1-15 ASINs
- optional campaign name
- optional default CPC bid
- optional daily budget
- optional output path
Defaults:
- campaign name:
LaunchFast-PPC-[YYYY-MM-DD] - default bid:
0.75 - daily budget:
25 - output path:
./artifacts/launchfast/ppc/launchfast-ppc-[YYYY-MM-DD].tsv
Workflow
1. Run keyword research
Run one keyword-research call across all ASINs when possible:
amazon_keyword_research(asins=[...], limit=50)
If the ASIN set is too large or results are unwieldy, batch them, but do not require delegation.
2. Normalize and tier keywords
For each keyword:
- deduplicate across ASIN overlaps
- keep overlap count
- capture search volume, CPC, purchase rate, relevance, and ranking coverage
Tiering:
- Tier 1: high-value terms with strong overlap or standout volume and conversion
- Tier 2: mid-volume growth terms
- Tier 3: discovery and long-tail terms
Match mapping:
- Exact: Tier 1
- Phrase: Tier 1 and Tier 2
- Broad: Tier 2 and Tier 3
Bid guidance:
- Exact: default bid * 1.2
- Phrase: default bid * 1.0
- Broad: default bid * 0.7
3. Present a preview
Show:
- ASINs analyzed
- unique keywords found
- tier breakdown
- top 15 keywords preview
- negative keywords or exclusions if obvious
4. Generate the bulk file
If the user wants the export, create the parent directory and write a TSV.
Use a deterministic writer such as Python csv.writer with a tab delimiter.
Required output:
- one campaign
- ad groups split by tier and match type
- keyword rows with bids
Default to this exact tab-separated 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 Custom Text Campaign Type Targeting Expression
Deterministic campaign structure:
Tier1-Exact: Tier 1 keywords as ExactTier1-Phrase: Tier 1 keywords as PhraseTier2-Phrase: Tier 2 keywords as PhraseTier3-Broad: Tier 2 and Tier 3 keywords as Broad
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 · 129 lines · 66 tokens per session scan A 52ed58cc2ef5
launchfast-ppc-research is a skill published in the GitHub repository hashgraph-online/awesome-codex-plugins (935 stars, last pushed today), licensed Apache-2.0. It adds 66 tokens to every session and 808 once invoked, about $0.0003 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.
Other skills, from other repositories
search
Search 2500+ curated ChatGPT and LLM open-source repositories. Use when the user asks to find tools, libraries, or repos related to ChatGPT, LLMs, RAG, agents, langchain, NLP, AI development, or any open-source AI tooling.
hunt-business-logic
Hunting skill for business logic vulnerabilities. Built from 7 public bug bounty reports. Use when hunting business logic on any target.
ecommerce-product-manager
Expert E-commerce Product Manager with deep knowledge of online retail strategy, conversion optimization, marketplace operations, and platform-specific tactics for Amazon, Shopify, and Alibaba. Use when: ecommerce-strategy, product-launch, conversion-optimization, marketplace-management, pricing-strategy.
ecommerce-livestream-trainer
Expert-level E-commerce Livestream Trainer with deep knowledge of live selling techniques, platform operations (TikTok Shop, Taobao Live, JD Live), audience engagement, and sales conversion.
bprr
Bulk PR reviewer for awesome-quant. Use when the user asks to review all open PRs, review unreviewed PRs, bulk review, or mentions "bprr". Reviews open PRs lacking the reviewed label and presents a summary before any merge/comment/label action.
tiktok-shop-webhooks
Receive and verify TikTok Shop webhooks. Use when setting up TikTok Shop webhook handlers, debugging Authorization-header signature verification, or handling events like ORDERSTATUSCHANGE, PACKAGEUPDATE, RECIPIENTADDRESSUPDATE, PRODUCTSTATUSCHANGE, or SELLERDEAUTHORIZATION.