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 imartinstudio/cover-prompt-skills --skill cover-light-product-with-docsgit clone --depth 1 https://github.com/imartinstudio/cover-prompt-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/imartinstudio/cover-prompt-skills/cover-light-product-with-docs)<a href="https://agentmods.dev/skills/imartinstudio/cover-prompt-skills/cover-light-product-with-docs"><img src="https://agentmods.dev/badge/skills/imartinstudio/cover-prompt-skills/cover-light-product-with-docs/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/imartinstudio/cover-prompt-skills/cover-light-product-with-docs"><img src="https://agentmods.dev/badge/skills/imartinstudio/cover-prompt-skills/cover-light-product-with-docs.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 | $0.00109 | $0.02419 |
| Opus 5 | $0.00055 | $0.01210 |
| Sonnet 5 | $0.00022 | $0.00484 |
| Haiku 4.5 | $0.00011 | $0.00242 |
Grade A, and why
cover-light-product-with-docs 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 12d 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 — 302 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Light Product With Docs
Use this skill when one article needs both a cover and section-bound inline
visuals in the light-product family. This skill is self-contained. Do not
route runtime work to cover-light-product, light-product-kit, or
illustration-light-product.
Hard Boundaries
- Accepted article sources: pasted article text, Markdown files, or plain-text files.
- Do not claim DOCX, PDF, remote article, or web-page ingestion support.
- The article source remains read-only.
- If no valid article content is available, ask the user for pasted content or a Markdown/plain-text path. Do not fall back to a single cover.
- Default output is returned in the conversation. Write a file only when the user explicitly provides an output path.
- An output path applies only to that requested path; do not overwrite or modify any other file.
Output Type
Use the explicit --out-type parameter to decide what to output.
--out-type template: output the invocation template only.--out-type brief: output the article visual brief set only.--out-type prompt: output final image prompts for every planned asset.--out-type all: output the brief set first, then the prompts.- Omitted
--out-type: default tobrief.
Treat 直接生成, 出图, 生成封面和配图, and 开始生图 as direct image
generation only when the user explicitly asks for images.
Template Output
For template-only mode, output exactly this structure and fill every field:
使用 $cover-light-product-with-docs 生成一套文章封面+正文配图方案
文章来源:{article_source}
输出类型:{out_type}
封面用途:{cover_use_case}
正文配图用途:{inline_use_case}
正文配图数量:{inline_count}
语言:{language}
封面画幅比例:{cover_ratio}
正文主画幅比例:{inline_ratio}
产品/场景:{product_context}
已有图片处理:{image_handling}
补充背景:{context}
禁用元素:{forbidden_elements}
Required Inputs
Extract or infer:
- Article source: required.
- Topic / article thesis: required.
- Cover use case: X header, WeChat article cover, blog header, SaaS launch cover, PPT cover, LinkedIn header.
- Inline use case: product docs, feature walkthrough, article inline image, workflow explainer, module explanation.
- Inline count: this is a hard constraint. If
正文配图数量is omitted, use3. If it is explicitly supplied, accept only an integer from1to5. Validate this before producing any template, brief, prompt, or image. An explicit0, negative number, non-integer, or value above5must fail with a clear request to use an integer from1to5; never clamp, round, expand, truncate, omit, or route to the base cover skill or cover-only behavior. - Language: Chinese, English, or mixed Chinese-English.
- Product context: AI product, agent workspace, research flow, coding workflow, automation system, dashboard, knowledge base, or feature module.
- Cover ratio and inline ratio: optional; infer from use case when omitted.
- Extra context: optional.
- Forbidden elements: optional.
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.
- 12d ago First seen · 302 lines · 109 tokens per session scan A aa83ee7ed7c1
cover-light-product-with-docs is a skill published in the GitHub repository imartinstudio/cover-prompt-skills (9 stars, last pushed 1mo ago), licensed MIT. It adds 109 tokens to every session and 2,419 once invoked, about $0.0005 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.
Other skills, from other repositories
systematic-debugging
Use when encountering any bug, test failure, or unexpected behavior, before proposing fixes.
local-ai-agents
Build local-first AI agents that run entirely on a developer workstation with Microsoft Foundry Local and Qwen function-calling models. Covers Small Language Models (SLMs), the OpenAI-compatible local endpoint, sandboxed local tools, local RAG with Chroma, local MCP servers, hybrid cloud/local routing, and the…
next-cache-components-adoption
Turn on Cache Components in a Next.js app and resolve the blocking routes it surfaces. Use when the user wants to enable, adopt, or migrate to Cache Components, flip the cacheComponents flag, work through a flood of blocking-prerender / instant validation errors, run the cache-components-instant-false codemod, or…
chat-pet-sprite-creation
Use when creating or changing VS Code chat pet sprite art, sprite sheets, state animations, eye treatments, Stable/Insiders variants, or pet transitions under src/vs/workbench/contrib/chat/browser/widget/media/chatPet.
cpu-profile-analysis
Analyze V8/Chrome CPU profiles (.cpuprofile) and DevTools trace files (Trace-.json). Use when: profiling performance, investigating slow functions, comparing code paths, finding bottlenecks, analyzing timeToRequest, understanding call trees from sampling profiler data, analyzing layout/paint/rendering, investigating…
insight-error-page
Write or audit an insight-kind error page for the Next.js dev overlay. Use when creating a new errors/ .mdx page, auditing an existing one, or checking that a page matches the framework fix cards. Covers page structure, title alignment, FixCard cards with Copy prompt button, code snippets, terminology verification…