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zhangifonly

Openclaw Xiaohongshu Ops

by zhangifonly · GitHub ↗ · v0.1.0
cross-platform ⚠ suspicious
967
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Install in OpenClaw
/install openclaw-xiaohongshu-ops
Description
Review-first Xiaohongshu/Rednote content ops for OpenClaw. Use when creating a repeatable workflow for topic research, draft generation, Feishu review, exact...
Usage Guidance
This package is largely what it says: a review-first Xiaohongshu content workflow with helper scripts. Before installing, note these practical issues and checks: 1) The metadata does not list required env vars but the code requires XHS_TOOLKIT_ROOT (and the README mentions XHS_REVIEW_OPEN_ID). Set and verify these before use. 2) publish_approved_note.py will call a local xhs_toolkit.py (via subprocess) and can perform a live publish if run with --allow-live and an exact --confirm-title; review that toolkit's code and understand its credentials and UI automation before allowing live runs. 3) The scripts write to .openclaw/pending-xhs/ and memory/ in your workspace and create a temporary Chrome user-data directory for publish runs—ensure you’re comfortable with those locations and have backups. 4) If you need the skill to declare requirements, request that the author add XHS_TOOLKIT_ROOT and XHS_REVIEW_OPEN_ID to the skill manifest so the platform can surface warnings and enforce least privilege. 5) If you want lower risk, run the scripts manually in a controlled environment (inspect xhs_toolkit.py first) rather than enabling autonomous invocation.
Capability Analysis
Type: OpenClaw Skill Name: openclaw-xiaohongshu-ops Version: 0.1.0 The skill bundle implements a structured Xiaohongshu (Rednote) content workflow with a strong emphasis on 'human-in-the-loop' safety. The Python scripts (e.g., publish_approved_note.py and save_publish_package.py) handle local draft management and interface with an external toolkit via subprocess calls, but they include explicit guardrails such as mandatory exact-title matching and an --allow-live flag to prevent unauthorized execution. No evidence of data exfiltration, malicious prompt injection, or obfuscation was found.
Capability Assessment
Purpose & Capability
The name/description (Xiaohongshu content ops with review-first workflow) matches the included docs and scripts: research, draft, preview, save packages, write memory, and a publish helper that invokes a local xhs_toolkit. However the skill package does not declare environment variables even though the README and scripts require XHS_TOOLKIT_ROOT (and the README references XHS_REVIEW_OPEN_ID). This omission is an inconsistency between declared requirements and actual needs.
Instruction Scope
SKILL.md and workspace docs instruct the agent to read many local template files and use the bundled scripts. The runtime scripts read and write local files (.openclaw/pending-xhs/, memory/), call a local toolkit (xhs_toolkit.py) via subprocess, and set a temporary Chrome user-data dir for publishing. These actions are coherent with the stated publish-assist purpose but the instructions assume a pre-existing local Xiaohongshu toolkit and specific environment variables (not listed in the skill metadata).
Install Mechanism
There is no network install spec and no downloads; the skill is instruction-heavy and ships Python scripts and docs. That reduces remote-install risk. The included scripts will be present on disk as part of the skill package, but nothing in the manifest fetches remote code.
Credentials
The skill metadata declares no required env vars, yet scripts explicitly require XHS_TOOLKIT_ROOT (publish_approved_note.py raises if not set) and the README/TOOLS.md reference XHS_REVIEW_OPEN_ID. These environment variables are appropriate for a local publish workflow, but the omission from declared requirements is a coherence problem: a user could install/run the skill without realizing these variables are mandatory. No unrelated cloud credentials or broad secrets are requested, which is good.
Persistence & Privilege
The skill is not marked always:true and does not request elevated platform privileges. It writes files to local workspace subpaths (.openclaw/pending-xhs, memory/) and creates a temporary Chrome profile dir when publishing; those are reasonable for a content workflow and are scoped to the user's workspace/environment.
How to Use
  1. Make sure OpenClaw is installed (local or Docker)
  2. Run the install command in chat: /install openclaw-xiaohongshu-ops
  3. After installation, invoke the skill by name or use /openclaw-xiaohongshu-ops
  4. Provide required inputs per the skill's parameter spec and get structured output
Version History
v0.1.0
Initial release of clawnote: Xiaohongshu content workflow skill for OpenClaw. - Enables structured, review-first content ops for Xiaohongshu/Rednote inside OpenClaw. - Supports research, drafting, Feishu review, exact-title approval, and structured publish packaging. - Bundles ready-to-use scripts for key workflow steps. - Emphasizes user confirmation before publishing and clear safety boundaries for risky actions. - Default workflow prioritizes review before publishing; publishing requires explicit approval.
Metadata
Slug openclaw-xiaohongshu-ops
Version 0.1.0
License
All-time Installs 4
Active Installs 4
Total Versions 1
Frequently Asked Questions

What is Openclaw Xiaohongshu Ops?

Review-first Xiaohongshu/Rednote content ops for OpenClaw. Use when creating a repeatable workflow for topic research, draft generation, Feishu review, exact... It is an AI Agent Skill for Claude Code / OpenClaw, with 967 downloads so far.

How do I install Openclaw Xiaohongshu Ops?

Run "/install openclaw-xiaohongshu-ops" in the OpenClaw or Claude Code chat to install it in one step — no extra setup required.

Is Openclaw Xiaohongshu Ops free?

Yes, Openclaw Xiaohongshu Ops is completely free (open-source). You can download, install and use it at no cost.

Which platforms does Openclaw Xiaohongshu Ops support?

Openclaw Xiaohongshu Ops is cross-platform and runs anywhere OpenClaw / Claude Code is available (cross-platform).

Who created Openclaw Xiaohongshu Ops?

It is built and maintained by zhangifonly (@zhangifonly); the current version is v0.1.0.

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