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 commerce-agentic/agentic-commerce-skills --skill agentic-commerce-generate-alt-textgit clone --depth 1 https://github.com/commerce-agentic/agentic-commerce-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/commerce-agentic/agentic-commerce-skills/agentic-commerce-generate-alt-text)<a href="https://agentmods.dev/skills/commerce-agentic/agentic-commerce-skills/agentic-commerce-generate-alt-text"><img src="https://agentmods.dev/badge/skills/commerce-agentic/agentic-commerce-skills/agentic-commerce-generate-alt-text/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/commerce-agentic/agentic-commerce-skills/agentic-commerce-generate-alt-text"><img src="https://agentmods.dev/badge/skills/commerce-agentic/agentic-commerce-skills/agentic-commerce-generate-alt-text.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 | $0.00044 | $0.00959 |
| Opus 5 | $0.00022 | $0.00479 |
| Sonnet 5 | $0.00009 | $0.00192 |
| Haiku 4.5 | $0.00004 | $0.00096 |
Grade A, and why
agentic-commerce-generate-alt-text 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 — 90 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Purpose
Most Shopify catalogs have <20% alt-text coverage. AI shopping agents that parse listings via vision-language models systematically deprioritize products with missing or generic alt text ("image-1.jpg", "untitled").
This skill scans every image without descriptive alt text, sends the image + product context (title, vendor, type) to Claude (or any vision-capable model), and writes back a concise, accurate alt-text describing the product as seen.
Prerequisites
- Authenticated Shopify CLI session
- API scopes:
read_products,write_products,read_files,write_files ANTHROPIC_API_KEYenv var set (or equivalent for chosen model)
Parameters
| Parameter | Type | Required | Default | Description |
|---|---|---|---|---|
| store | string | yes | — | Store domain |
| product_ids | array | no | — | Specific products to process. If omitted, processes all products with image alt-coverage < 0.50 |
| dry_run | bool | no | true | Preview generated alt text without persisting |
| max_length | integer | no | 125 | Max characters per alt text (HTML/SEO convention) |
| skip_existing | bool | no | true | Skip images that already have descriptive alt text (length >= 5) |
| model | string | no | claude-sonnet-4-6 | Vision-language model to use |
Workflow Steps
-
Identify target images: query products via
agentic-commerce-audit-images-alt. Collect image URLs + product context. -
For each image needing alt text:
- Fetch the image bytes
- Send to the chosen vision model with prompt:
Generate a concise alt text (under {max_length} chars) for this product image. Product title: {title} Vendor: {vendor} Product type: {productType} Rules: - Describe what is visually present in the image - Include color, material, perspective (front/side/lifestyle) when visible - Do not invent specs that are not visible - No marketing language; factual description only - Capture the response
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 · 90 lines · 44 tokens per session scan A 7416f4513dce
agentic-commerce-generate-alt-text is a skill published in the GitHub repository commerce-agentic/agentic-commerce-skills (2 stars, last pushed 4mo ago), licensed MIT. It adds 44 tokens to every session and 959 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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