baoyu-xhs-images

baoyu-xhs-images is a skill for Claude Code, Codex from guanyang/open-agent-hub. It costs 100 tokens per session (7,316 once invoked), scanned A, a copy of baoyu-xhs-images, MIT.

An image-card generator for Xiaohongshu, a Chinese social-media platform, that turns written content into a series of illustrated infographic cards. It supports several visual styles, layouts, and color palettes, with between one and ten cards per series.

In plain words
What is it for?
Use it to break articles or ideas into Xiaohongshu image posts, choose a visual style and layout, and create cartoon-style card series.
Why use it?
It removes the need to plan and format each social-media card by hand. It helps turn a longer explanation into smaller visual pieces suited to a card-based post.

Skill for Claude CodeCodex

Written for Claude Code and Codex: shipped in a Claude Code plugin, but also runs codex exec. Also seen: mentions subagents; names the AskUserQuestion tool; mentions Codex.

Part of the open-agent-hub plugin — 103 skills, 3 commands, 5 agents, 6 MCP servers shipped together

Good fit Use it to break articles or ideas into Xiaohongshu image posts, choose a visual style and layout, and create cartoon-style card series.

Compare 6 skills from other repositories ↓
Install with agentmods
npx agentmods add skills/guanyang/open-agent-hub/baoyu-xhs-images
Install

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.

Any agent
npx skills add guanyang/open-agent-hub --skill baoyu-xhs-images
Clone the repo
git clone --depth 1 https://github.com/guanyang/open-agent-hub

Made for: Claude Code, Codex.

Or install open-agent-hub, the plugin that ships this one along with the rest of its 103 skills, 3 commands, 5 agents, 6 MCP servers.

Wrote 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.

agentmods badge for baoyu-xhs-images

README.md
[![agentmods](https://agentmods.dev/badge/skills/guanyang/open-agent-hub/baoyu-xhs-images/github.svg)](https://agentmods.dev/skills/guanyang/open-agent-hub/baoyu-xhs-images)
Your own site
<a href="https://agentmods.dev/skills/guanyang/open-agent-hub/baoyu-xhs-images"><img src="https://agentmods.dev/badge/skills/guanyang/open-agent-hub/baoyu-xhs-images/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.

agentmods 80×15 button for baoyu-xhs-images

Your own site · 80×15
<a href="https://agentmods.dev/skills/guanyang/open-agent-hub/baoyu-xhs-images"><img src="https://agentmods.dev/badge/skills/guanyang/open-agent-hub/baoyu-xhs-images.svg" alt="Reviewed on agentmods" width="80" height="20"></a>
Per session 100 Skills are progressive disclosure: only the name and description are preloaded; the body loads when the skill is used.
When invoked 7,316 The whole file, excluding the scripts and references it only reads on demand.
Security scan A 0 findings. A grade says what 26 rules found in the file — not that it is safe.
Origin 100% copy Near-identical to another mod in the catalogue.
Token cost

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.

ModelPer sessionOnce invoked
Fable 5.1 $0.00100 $0.07316
Opus 5 $0.00050 $0.03658
Sonnet 5 $0.00020 $0.01463
Haiku 4.5 $0.00010 $0.00732

Measured 13d ago against content hash 17bf5498641c, method: parsed. Prices are Anthropic first-party input rates as of 2026-09-12, from the pricing page.

Security

Grade A, and why

baoyu-xhs-images 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 13d 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.

Origin

This is a copy

100% identical to baoyu-xhs-images — 0 lines differ, which has more behind it and is treated as the original. This page carries a canonical link to it rather than competing with it.

skills/baoyu-xhs-images/SKILL.md · 485 lines

How it starts

The opening of the file, as written. The whole thing — 485 lines — stays where its author put it; the contents beside it link to each section on GitHub.

Image Card Series Generator

Break down complex content into eye-catching image card series with multiple style options.

User Input Tools

When this skill prompts the user, follow this tool-selection rule (priority order):

  1. Prefer built-in user-input tools exposed by the current agent runtime — e.g., AskUserQuestion, request_user_input, clarify, ask_user, or any equivalent.
  2. Fallback: if no such tool exists, emit a numbered plain-text message and ask the user to reply with the chosen number/answer for each question.
  3. Batching: if the tool supports multiple questions per call, combine all applicable questions into a single call; if only single-question, ask them one at a time in priority order.

Concrete AskUserQuestion references below are examples — substitute the local equivalent in other runtimes.

Image Generation Tools

When this skill needs to render an image, resolve the backend in this order:

  1. Current-request override — if the user names a specific backend in the current message, use it.
  2. Saved preference — if EXTEND.md sets preferred_image_backend to a backend available right now, use it.
  3. Auto-select (when the preference is auto, unset, or the pinned backend isn't available):
    • Codex (imagegen) — first, inspect your available-skills / tool inventory. If a skill named imagegen is listed, you are running inside Codex and MUST use it: invoke via the Skill tool with skill: "imagegen", passing the saved prompt file's content (plus output path and aspect ratio per Codex imagegen's own args). Codex imagegen is the official raster backend in that runtime and outranks any non-native skill (e.g., baoyu-image-gen) unless the user has explicitly pinned a different preferred_image_backend.
    • Codex via codex exec (codex-imagegen) — if the current runtime exposes no native imagegen skill but the codex CLI is on PATH with an active codex login, route through baoyu-image-gen --provider codex-cli (preferred), or — if baoyu-image-gen is unavailable — invoke the bundled wrapper directly. Details, parameters, and the runtime-discovery procedure live in references/codex-imagegen.md — load that file only when this branch is selected.
    • Cursor (GenerateImage) — if the runtime exposes a native GenerateImage tool, you are running inside Cursor and it outranks any non-native skill the same way Codex imagegen does. Two hard caveats: (a) it has no aspect-ratio parameter — state the target aspect ratio / dimensions explicitly in the prompt text passed as description; (b) it does not accept an output directory — it saves to a tool-managed location, so after generation copy/move the file to the skill's expected output path (e.g., outputs/.../NN-xxx.png). Reference images go in reference_image_paths.
    • Other runtime-native tools — if the runtime exposes a different native image tool (e.g., Hermes image_generate), use it the same way.
    • Otherwise, if exactly one non-native backend is installed (e.g., baoyu-image-gen), use it.
    • Otherwise (multiple non-native backends with no runtime-native tool), ask the user once — batch with any other initial questions.
  4. If none are available, tell the user and ask how to proceed.

Read the full file on GitHub · 485 lines

Changes

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.

  1. 13d ago First seen · 485 lines · 100 tokens per session scan A 17bf5498641c

Subscribe to this mod's changes

baoyu-xhs-images is a skill published in the GitHub repository guanyang/open-agent-hub (967 stars, last pushed yesterday), licensed MIT. It adds 100 tokens to every session and 7,316 once invoked, about $0.0005 per session on Opus 5. A static security scan graded it A with 0 findings. It is 100% identical to baoyu-xhs-images, differing in 0 lines, and is treated as a copy.

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