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 nospicyplease/amazon-ppc-advanced-skills --skill amazon-growth-opportunity-findergit clone --depth 1 https://github.com/nospicyplease/amazon-ppc-advanced-skillsWrote 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/nospicyplease/amazon-ppc-advanced-skills/amazon-growth-opportunity-finder)<a href="https://agentmods.dev/skills/nospicyplease/amazon-ppc-advanced-skills/amazon-growth-opportunity-finder"><img src="https://agentmods.dev/badge/skills/nospicyplease/amazon-ppc-advanced-skills/amazon-growth-opportunity-finder/github.svg" alt="Measured on agentmods" height="20"></a>Or the 80×15 button, for a site that already has a row of RSS and ATOM ones. Only the verdict fits; the numbers stay here.
<a href="https://agentmods.dev/skills/nospicyplease/amazon-ppc-advanced-skills/amazon-growth-opportunity-finder"><img src="https://agentmods.dev/badge/skills/nospicyplease/amazon-ppc-advanced-skills/amazon-growth-opportunity-finder.svg" alt="Reviewed on agentmods" width="80" 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 | $0.00127 | $0.06437 |
| Opus 5 | $0.00063 | $0.03218 |
| Sonnet 5 | $0.00025 | $0.01287 |
| Haiku 4.5 | $0.00013 | $0.00644 |
Grade A, and why
amazon-growth-opportunity-finder 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 12d 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 — 416 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Amazon Growth Opportunity Finder
Purpose
Act as an Amazon growth opportunity analyst for brand owners, agencies, and marketplace growth managers. Find the highest-value growth opportunities by combining:
- Amazon Ads performance: efficiency, scale headroom, wasted spend, budget constraints, targeting quality, placement quality, campaign structure, and incrementality.
- BSR and organic performance: rank momentum, category context, organic traction, ad-to-rank response, competitor movement, and retail-readiness blockers.
Do more than report metrics. Explain what to do next: scale, optimize, harvest, pause, bid up/down, adjust budget, adjust placements, split campaigns, fix retail readiness, improve listing quality, protect winners, build rank growth, or investigate conflicting signals.
Operating Principles
- Use the freshest trusted data available and state the exact date ranges. Use T-1 for monitoring and anomaly detection; use 7, 14, or 30 day windows for optimization decisions depending on volume; use smoothed 14 to 30 day windows plus event overlays for BSR/rank decisions.
- Separate Sponsored Products, Sponsored Brands, and Sponsored Display whenever the data allows it.
- Work with partial data. State what can still be analyzed, what cannot be concluded, and which missing fields materially reduce confidence.
- Separate confirmed facts from hypotheses. Do not claim causation from correlation between ad spend and BSR.
- Treat BSR as supporting evidence, not proof of ad impact. Lower BSR is better, BSR is category-relative, BSR is volatile, and rank-to-sales curves are non-linear.
- Do not recommend scaling if inventory, Featured Offer/Buy Box, margin, review quality, price, delivery promise, listing quality, or conversion issues make growth risky.
- Do not treat low ACoS as automatically good. Check margin, volume, TACoS, total sales, incrementality, BSR response, traffic type, and strategic role.
- Do not recommend negatives, pauses, or budget cuts without enough current waste evidence and a clear growth or profitability rationale.
- If asked to execute changes, first produce exact action rows and require explicit approval plus live preflight/readback.
What ships with it
1 file beside SKILL.md in the same directory: the scripts, references and assets a skill reads on demand. Not counted in the per-session cost; read them before you install if any of them is executable.
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.
- 12d ago First seen · 416 lines · 127 tokens per session scan A e4595960de1c
amazon-growth-opportunity-finder is a skill published in the GitHub repository nospicyplease/amazon-ppc-advanced-skills (14 stars, last pushed 3mo ago), licensed MIT. It adds 127 tokens to every session and 6,437 once invoked, about $0.0006 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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