Getting it into your agent
It runs from inside its repository, so the clone comes first — what it calls does not travel with the file alone.
git clone --depth 1 https://github.com/zpoint/vibe-sellernpx agentmods add skills/zpoint/vibe-seller/amazon-listingWrote 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/zpoint/vibe-seller/amazon-listing)<a href="https://agentmods.dev/skills/zpoint/vibe-seller/amazon-listing"><img src="https://agentmods.dev/badge/skills/zpoint/vibe-seller/amazon-listing/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/zpoint/vibe-seller/amazon-listing"><img src="https://agentmods.dev/badge/skills/zpoint/vibe-seller/amazon-listing.svg" alt="Reviewed on agentmods" width="80" height="20"></a>- NVIDIA SkillSpector pass
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 | $0.00149 | $0.02829 |
| Opus 5 | $0.00075 | $0.01414 |
| Sonnet 5 | $0.00030 | $0.00566 |
| Haiku 4.5 | $0.00015 | $0.00283 |
Grade A, and why
amazon-listing 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 — 197 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Amazon — Listing CRUD (flat-file upload)
PREREQUISITE: read
../amazon-shared/SKILL.mdfor login, Ziniao auto-fill / OTP, marketplace TLDs, hamburger navigation, and the capture rule (live data →/tmp/<task>/, neverknowledge/).
Amazon's Add Products via Upload takes a category flat-file
template — a macro-enabled .xlsm whose Template sheet is a wide
table (one column per attribute). One upload creates or edits a whole
variation family (a Parent plus N colour/size Children) at once.
This is the batch equivalent of the per-SKU web wizard, and the default
for anything touching more than one variant.
Two references, load what the task needs:
references/template-round-trip.md— the download → inspect → fill → upload → read-feedback loop, the operation column (create/update/partialupdate/delete), and the parent-child cluster. Load for any listing CRUD.references/1688-sourcing.md— turning a supplier link into a filled template: page extraction, local no-GPU OCR of detail images, AI-generated copy, the bilingual review step, and image handling. Load when the task starts from a product link.
Work it like a human: upload → read the report → fix → repeat
The template, its required fields, valid values, and even the upload mechanics change per product type and over time. Do not follow a fixed recipe from memory. Run the loop a human runs:
- Download a FRESH template for the exact product type — Amazon's own error messages say "download the latest template". Never reuse a stale one.
inspectit. The field set / required fields / valid values for THIS category are the ground truth, not this doc.- Fill, upload, then download the processing report and run
parse-feedback REPORT.xlsm. It reads the summary tables and the per-cell comments (批注) on the report'sTemplatetab — where Amazon writes the precise, field-level verdict per SKU — and printssku=… field=… : MESSAGE. - For each ERROR line, fix exactly the field it names — set it to a
value from the template's own valid set (
inspect --field NAME). Do not reinterpret or theorise a root cause; act on the report's words. (If a WARNING names a key defining attribute like material/pattern, fix it too — that's often what unblocks new-ASIN creation.) - Re-upload and repeat until only expected noise remains (see the main-image rule below).
- Final verify — the two sources of truth, not the feed count: the
downloaded report shows 0 blocking errors, AND the Manage
Inventory page shows the family (parent's "Variations (N)", each
child a real ASIN — not
-— with title / description / bullets).
What ships with it
5 files 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 · 197 lines · 149 tokens per session scan A 7d2929872a88
amazon-listing is a skill published in the GitHub repository zpoint/vibe-seller (66 stars, last pushed yesterday), licensed Apache-2.0. It adds 149 tokens to every session and 2,829 once invoked, about $0.0007 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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