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 product-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/product-research)<a href="https://agentmods.dev/skills/hashgraph-online/awesome-codex-plugins/product-research"><img src="https://agentmods.dev/badge/skills/hashgraph-online/awesome-codex-plugins/product-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 | $0.00045 | $0.00666 |
| Opus 5 | $0.00023 | $0.00333 |
| Sonnet 5 | $0.00009 | $0.00133 |
| Haiku 4.5 | $0.00005 | $0.00067 |
Grade A, and why
product-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 — 138 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Amazon FBA Product Research
This skill is the deeper, criteria-driven version of launchfast-product-research.
Core criteria
Evaluate every market against these baselines:
| Criteria | Threshold |
|---|---|
| Total niche revenue | > $200,000/month |
| Average price | >= $25, ideally >= $40 |
| Average reviews | <= 500 |
| Revenue per seller | >= $5,000/month |
| Top-seller dominance | top 2-3 sellers < 50% of revenue |
| Search volume | must exist |
| Estimated margin | >= 30% before ad costs |
Large-market exception:
- If niche revenue is above $1M, higher review counts can still be acceptable when multiple sellers under 200 reviews are doing strong revenue.
Workflow
1. Initial scan
Run:
research_products(keyword="<keyword>", focus="balanced", product_limit=20)
Extract:
- search volume
- average price
- average reviews
- opportunity score
- market grade
- brand concentration
- dominant brand
- total niche revenue
- average revenue per seller
- top-seller share
2. Financial trend check
Run:
research_products(keyword="<keyword>", focus="financial", product_limit=20)
Look for:
- growing vs stable vs declining products
- average MoM growth
- short-term momentum using 7d trend fields
3. Listing quality check
Run:
research_products(keyword="<keyword>", focus="titles", product_limit=10)
Look for:
- low listing quality scores with high revenue
- listing quality gaps
- weak copy or obvious differentiation openings
4. Keyword validation
Pick 2-3 relevant ASINs and run:
amazon_keyword_research(asins=["ASIN1", "ASIN2", "ASIN3"], limit=20)
Evaluate:
- keyword diversity
- CPC and sponsored density
- purchase rate
- obvious ranking gaps
5. Profitability estimate
Present a conservative estimate:
Selling Price
- Amazon Fees (~15%)
- Manufacturing
- Shipping
= Estimated Profit per Unit
= Estimated Margin %
If manufacturing cost is unknown, say so and state the assumption used.
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 · 138 lines · 45 tokens per session scan A eeaef583c912
product-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 45 tokens to every session and 666 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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