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 nexscope-ai/Amazon-Skills --skill amazon-fba-prepgit clone --depth 1 https://github.com/nexscope-ai/Amazon-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/nexscope-ai/amazon-skills/amazon-fba-prep)<a href="https://agentmods.dev/skills/nexscope-ai/amazon-skills/amazon-fba-prep"><img src="https://agentmods.dev/badge/skills/nexscope-ai/amazon-skills/amazon-fba-prep/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/nexscope-ai/amazon-skills/amazon-fba-prep"><img src="https://agentmods.dev/badge/skills/nexscope-ai/amazon-skills/amazon-fba-prep.svg" alt="Reviewed on agentmods" width="80" height="20"></a>- Socket pass
- Snyk pass
- NVIDIA SkillSpector warn
SkillSpector: 1 finding, up to medium
These are SkillSpector’s own severities. On a checked sample its high-severity flags on skills were ~96% false positives — a documented command, a public API, a “never do X” rule — so we show them as a caution to read, not a verdict. Why →
- medium MCP Rug Pull · line 13 npx commands without a version suffix (e.g. @1.0.0) create a rug-pull risk if the upstream server is compromised and publishes a malicious update.Fix: Pin the version: npx @scope/[email protected]
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 | $0.00088 | $0.02331 |
| Opus 5 | $0.00044 | $0.01166 |
| Sonnet 5 | $0.00018 | $0.00466 |
| Haiku 4.5 | $0.00009 | $0.00233 |
Grade A, and why
amazon-fba-prep 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 10d 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 — 229 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Amazon FBA Prep
Convert product and shipment facts into a traceable unit-prep specification, carton plan, handoff checklist, and final go/hold decision before inventory is sent to Amazon.
Installation
npx skills add nexscope-ai/Amazon-Skills --skill amazon-fba-prep -g
Capabilities
- Build a SKU-level prep and labeling matrix.
- Identify product attributes that trigger additional review or preparation.
- Plan barcode choice, label placement, unit packaging, sets, case packs, and carton QA.
- Create supplier, factory, warehouse, or prep-center work instructions.
- Compare self-prep, supplier prep, prep-center, and available Amazon service options.
- Produce a shipment-readiness audit with evidence, owners, and blocking issues.
Usage Examples
Walk me through FBA prep for 500 glass water bottles.
Create a supplier-ready prep sheet for this three-piece kitchen bundle.
I have apparel, cosmetics, and battery-powered items. Tell me which SKUs need separate FBA prep verification.
Audit my first FBA shipment plan and flag anything that could delay receiving.
Inputs and Collection
Use supplied evidence first. Collect:
- target Amazon marketplace, ship-from location, account access, and shipment workflow status;
- SKU, ASIN, FNSKU or other barcode data, quantity, condition, and ownership of each unit;
- exact product type, included items, set or multipack status, dimensions, weight, and packaging dimensions;
- materials, fragility, sharp edges, liquids, powders, textiles, small parts, expiration dates, lot controls, magnets, batteries, chemicals, temperature sensitivity, and regulated claims;
- current retail packaging, visible barcodes, labels, seals, openings, and scannability;
- individual or case-packed configuration, carton counts, carton dimensions/weights, pallet use, and carrier plan;
- who will prep, label, inspect, photograph, and approve the shipment.
If essential fields are missing, ask one consolidated follow-up. Continue with an incomplete checklist only when every assumption and blocked decision is clearly marked.
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.
- 10d ago First seen · 229 lines · 88 tokens per session scan A 06ddf515e697
amazon-fba-prep is a skill published in the GitHub repository nexscope-ai/Amazon-Skills (649 stars, last pushed 14d ago), licensed MIT. It adds 88 tokens to every session and 2,331 once invoked, about $0.0004 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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