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 kangise/ecommerce-ai-skills --skill ecom-listinggit clone --depth 1 https://github.com/kangise/ecommerce-ai-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/kangise/ecommerce-ai-skills/ecom-listing)<a href="https://agentmods.dev/skills/kangise/ecommerce-ai-skills/ecom-listing"><img src="https://agentmods.dev/badge/skills/kangise/ecommerce-ai-skills/ecom-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/kangise/ecommerce-ai-skills/ecom-listing"><img src="https://agentmods.dev/badge/skills/kangise/ecommerce-ai-skills/ecom-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 | $0.00041 | $0.00316 |
| Opus 5 | $0.00020 | $0.00158 |
| Sonnet 5 | $0.00008 | $0.00063 |
| Haiku 4.5 | $0.00004 | $0.00032 |
Grade A, and why
ecom-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 11d 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.
What it actually says
Listing Skill
When to Use
Generate and optimize Amazon/Shopify/TikTok Shop product listings. Use when creating titles, bullet points, descriptions, A+ Content, Search Terms, or multi-language listings.
Method
Step 1: Read Platform Constraints
Read references/constraints.md for platform-specific rules (character limits, byte constraints, format requirements).
Step 2: Review Boundaries
Read references/boundaries.md to know when this skill should NOT be used.
Step 3: Pick the Prompt
Pick the appropriate prompt from references/playbook.md for your scenario.
Step 4: Execute and Verify
Execute the prompt with your data. Use the <自检>/<self_check>/<セルフチェック> self-check block in each prompt to verify output quality before delivering results.
References
- Constraints — Platform rules and limits
- Playbook — Prompt collection
- Boundaries — When not to use
Templates
Copy-ready prompt templates (in assets/templates/):
What ships with it
6 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.
- 11d ago First seen · 42 lines · 41 tokens per session scan A 324c287923e1
ecom-listing is a skill published in the GitHub repository kangise/ecommerce-ai-skills (67 stars, last pushed 4d ago), licensed CC0-1.0. It adds 41 tokens to every session and 316 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 2026-08-30.
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