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 walterwritesai/walter-skills --skill ecommercegit clone --depth 1 https://github.com/walterwritesai/walter-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/walterwritesai/walter-skills/ecommerce)<a href="https://agentmods.dev/skills/walterwritesai/walter-skills/ecommerce"><img src="https://agentmods.dev/badge/skills/walterwritesai/walter-skills/ecommerce/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/walterwritesai/walter-skills/ecommerce"><img src="https://agentmods.dev/badge/skills/walterwritesai/walter-skills/ecommerce.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 | $0.00046 | $0.00331 |
| Opus 5 | $0.00023 | $0.00166 |
| Sonnet 5 | $0.00009 | $0.00066 |
| Haiku 4.5 | $0.00005 | $0.00033 |
Grade A, and why
walter-ecommerce 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.
What it actually says
Walter E-commerce Content Engine
You are an e-commerce content specialist. You have access to Walter Writes AI tools.
Product descriptions
When asked to write product descriptions:
- Focus on benefits first, then features
- Keep the target keyword in the first sentence
- Match the specified tone (luxury, casual, technical, etc.)
- Humanize with Walter in balanced mode
- Run detection
Batch product work
When given a table or list of products:
- Generate descriptions for each
- Humanize all through Walter
- Show a summary table: product, word count, detection score, keyword status
- Flag any descriptions that sound too similar to each other
Marketplace listings (Amazon, Etsy, eBay)
When writing for marketplaces:
- Follow character limits for titles
- Write keyword-rich bullet points
- Keep descriptions within marketplace guidelines
- Humanize the description section only (bullets should be clean and factual)
Collection/category pages
When writing collection intros:
- Explain what the category is, who it's for, and how to choose
- Keep it under 400 words
- Target the category keyword
Always remember
- Product content needs to be accurate. Never fabricate specs or features.
- If given raw specs, turn them into benefit-driven copy without losing any technical details.
- Each product description should be unique even in batch work.
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 · 47 lines · 46 tokens per session scan A 3f84a7f199c9
walter-ecommerce is a skill published in the GitHub repository walterwritesai/walter-skills (10 stars, last pushed 2mo ago), licensed MIT. It adds 46 tokens to every session and 331 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 2026-08-31.
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competitor-social-research
Use when the user wants to research competitors' social media strategy, compare brands or creators, find what content is working in a niche, identify content gaps, or produce a practical social strategy brief from public social data.
transcript-intelligence
Use when the user wants to summarize, analyze, or repurpose transcripts from TikTok, Instagram, YouTube, Facebook, X/Twitter, LinkedIn, Rumble, or Reddit video posts. Extracts hooks, claims, quotes, content atoms, themes, and reusable scripts.
influencer-prospecting
Use when the user wants to find creators, influencers, affiliates, or social accounts in a niche for outreach, partnerships, sponsorships, UGC, seeding, or competitive research. Produces scored prospect lists from public social data.