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 guanyang/open-agent-hub --skill baoyu-xhs-imagesgit clone --depth 1 https://github.com/guanyang/open-agent-hubWrote 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/guanyang/open-agent-hub/baoyu-xhs-images)<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.
<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>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 | $0.00100 | $0.07316 |
| Opus 5 | $0.00050 | $0.03658 |
| Sonnet 5 | $0.00020 | $0.01463 |
| Haiku 4.5 | $0.00010 | $0.00732 |
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.
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.
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):
- Prefer built-in user-input tools exposed by the current agent runtime — e.g.,
AskUserQuestion,request_user_input,clarify,ask_user, or any equivalent. - 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.
- 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:
- Current-request override — if the user names a specific backend in the current message, use it.
- Saved preference — if
EXTEND.mdsetspreferred_image_backendto a backend available right now, use it. - 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 namedimagegenis listed, you are running inside Codex and MUST use it: invoke via theSkilltool withskill: "imagegen", passing the saved prompt file's content (plus output path and aspect ratio per Codeximagegen's own args). Codeximagegenis 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 differentpreferred_image_backend. - Codex via
codex exec(codex-imagegen) — if the current runtime exposes no nativeimagegenskill but thecodexCLI is onPATHwith an activecodex login, route throughbaoyu-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 nativeGenerateImagetool, you are running inside Cursor and it outranks any non-native skill the same way Codeximagegendoes. Two hard caveats: (a) it has no aspect-ratio parameter — state the target aspect ratio / dimensions explicitly in the prompt text passed asdescription; (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 inreference_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.
- Codex (
- If none are available, tell the user and ask how to proceed.
What ships with it
28 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.
- references/codex-imagegen.md 3.6 KB
- references/config/first-time-setup.md 3.4 KB
- references/config/preferences-schema.md 3.9 KB
- references/config/watermark-guide.md 1.9 KB
- references/confirmation.md 3.8 KB
- references/elements/canvas.md 3.6 KB
- references/elements/decorations.md 4.9 KB
- references/elements/image-effects.md 2.9 KB
- references/elements/typography.md 3.2 KB
- references/palettes/macaron.md 1.4 KB
- references/palettes/neon.md 1.2 KB
- references/palettes/warm.md 1.2 KB
- references/presets/bold.md 1.5 KB
- references/presets/chalkboard.md 2.3 KB
- references/presets/cute.md 1.5 KB
- references/presets/fresh.md 1.5 KB
- references/presets/minimal.md 1.4 KB
- references/presets/notion.md 1.6 KB
- references/presets/pop.md 1.5 KB
- references/presets/retro.md 1.4 KB
- references/presets/screen-print.md 2.6 KB
- references/presets/sketch-notes.md 3.1 KB
- references/presets/study-notes.md 2.9 KB
- references/presets/warm.md 1.4 KB
- references/style-presets.md 1.9 KB
- references/workflows/analysis-framework.md 7.1 KB
- references/workflows/outline-template.md 6.0 KB
- references/workflows/prompt-assembly.md 10 KB
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.
- 13d ago First seen · 485 lines · 100 tokens per session scan A 17bf5498641c
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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