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 code2rich/agentwaker-xiaohongshu-operator --skill xiaohongshu-visualsgit clone --depth 1 https://github.com/code2rich/agentwaker-xiaohongshu-operatorWrote 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/code2rich/agentwaker-xiaohongshu-operator/xiaohongshu-visuals)<a href="https://agentmods.dev/skills/code2rich/agentwaker-xiaohongshu-operator/xiaohongshu-visuals"><img src="https://agentmods.dev/badge/skills/code2rich/agentwaker-xiaohongshu-operator/xiaohongshu-visuals/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/code2rich/agentwaker-xiaohongshu-operator/xiaohongshu-visuals"><img src="https://agentmods.dev/badge/skills/code2rich/agentwaker-xiaohongshu-operator/xiaohongshu-visuals.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 | $0.00072 | $0.02323 |
| Opus 5 | $0.00036 | $0.01162 |
| Sonnet 5 | $0.00014 | $0.00465 |
| Haiku 4.5 | $0.00007 | $0.00232 |
Grade A, and why
xiaohongshu-visuals 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 9d 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 — 154 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Xiaohongshu Visuals
Purpose
Turn an approved note angle, verified facts, and lawful source assets into finished Xiaohongshu flat visuals. Own the cover, first image, carousel cards, explanatory diagrams, evidence-screenshot treatment, export package, and visual handoff; do not stop at an image brief when production tools and inputs are available.
Keep factual evidence visibly separate from generated concept imagery. Never imply that a generated scene, reconstructed interface, illustrative chart, or mock screenshot is observed proof.
Trigger Conditions
Use this skill when the request needs one or more of:
- A cover or first image for a Xiaohongshu note.
- A multi-card carousel with a coherent reading sequence.
- A comparison, process, architecture, timeline, annotated screenshot, or other explanatory graphic.
- An evidence-screenshot list, redaction plan, citation treatment, or provenance review.
- Brand-consistent visual variants or a complete file package for publishing.
- Visual QA for copy accuracy, crop resilience, mobile readability, rights, privacy, or evidence integrity.
Do not trigger it for a custom-coded interactive demo, web page, component, or reusable visual application. Hand those implementations to FrontDeveloper while retaining the Xiaohongshu copy, audience intent, and acceptance constraints.
Required Inputs
- Note goal, target audience, approved angle, and intended reader action.
- Final or versioned copy, factual claims, sources, and any mandatory qualifiers.
- Brand guidance: logo rules, colors, typography, tone, prohibited treatments, and reference examples when available.
- Provided asset paths plus origin, ownership, license, consent, and reuse limits.
- Target placement for every image: cover, first image, carousel position, explanation, evidence, or backup variant.
- Current platform and user constraints for the exact publishing surface, including the currently accepted file types, dimensions or aspect ratios, count, crop behavior, and size limits.
What ships with it
2 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.
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.
- 9d ago First seen · 154 lines · 72 tokens per session scan A 03f681cebf94
xiaohongshu-visuals is a skill published in the GitHub repository code2rich/agentwaker-xiaohongshu-operator (5 stars, last pushed 1mo ago), licensed MIT. It adds 72 tokens to every session and 2,323 once invoked, about $0.0004 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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