SKILLEMALL.ai

AC xhs

Use this skill when publishing or managing posts on Xiaohongshu (小红书 / RED / xiaohongshu) via the official Creator Center. Triggers on requests to draft, save, or publish a note; generate titles, captions, or topic chips; reply to comments or DMs; or check creator dashboard metrics. The skill follows the language of the user's input (Chinese, English, or any locale the user supplies) — no locale is forced. Workflow is browser-automation-based; final publish always requires explicit user confirmation.

ClawHub Agent Skills author: Jacky Shen v0.2.0 MIT-0 6 files body ≈ 1 241 tokens Open the sourceclawhub.ai analyzed 2 d ago

Triggers on requests to draft, save, or publish a note; generate titles, captions, or topic chips; reply to comments or DMs; or check creator dashboard metrics.

As a process C 57/100 · Has gaps — weak spots: result and completion, inputs and preconditions, failures and branches

ProcedureData and analyticstype and topics are labelled automatically from the skill text
JSON
Technical rating
A
94/100
safety, quality, tests
Safety 60%
100
Quality 40%
84
Run on models
none yet
Process rating
C
57/100
Has gaps
Result and completion w 14
0
Inputs and preconditions w 11
0
Failures and branches w 10
0
the three weakest of ten parameters · all ten

How to improve

    For the model run — optional
    • Your own cases (evals/evals.json, 4–6 real requests with expected answers): the full check would then run those instead of a model-drafted suite.
    • A spec.yaml with trigger phrases and assertions — a behaviour contract for CI; `skilltest init` writes a template.

    Guard findings · 0

    ✓ No critical or high findings

    Files scanned: 6. Evidence is masked. Grey chips explain why severity was lowered.

    Against the Agent Skills spec

    ✓ No remarks against the Agent Skills spec

    Process rating: all ten parameters 57/100

    • 0Result and completion. Does not say what the result is
    • 0Inputs and preconditions. Does not say what the process needs to start
    • 0Failures and branches. Linear process with no failure handling
    • 0Progress reporting. Says nothing while it works
    • 30Running it twice. 12 mutating operations with no state check
    • 70When it triggers. States when to use, but not when not to
    • 100Tools and files. No external tools needed
    • 100Steps. 75 steps
    • 100Consistency. Name and required fields are in place
    • 100Execution cost. Instruction body is 1241 tokens
    • low 10 top-level sections: this looks like several domains in one skill
    • low The response is described with custom markup (6 tags): a typed call is more reliable

    Everything here is measured from the skill text rather than judged by a model, so the numbers are checkable. A parameter weighs more when it is a more common reason for the process to stall.

    Quality signals

    • +5Description has no quoted example phrases that should trigger the skill
    • +4Description does not say when NOT to use the skill (false activations)
    • +3Output format is not stated: the model decides each time
    • -4Absolute local paths (C:\Users, /home/…): not portable
    • +1No license
    • +2Single-language instructions
    • +3Description length 505: enough signal without eating the budget
    • +4Structure: 11 headings
    • +3Step-by-step instructions: 75 items
    • +4Has examples (1 code blocks)
    • +4Reference files are cited in the instructions (1 of 1)

    Quality base 70; lint remarks subtract, signals add up to 100. Result: 84.

    External checks

    ClawHub: suspicious
    The skill is mostly coherent for Xiaohongshu browser automation, but one draft-saving instruction appears to target the publish button, creating a real risk of unintended public posting.
    LLM: suspicious (medium) · VirusTotal: · 18 Aug 2026