SKILLEMALL.ai

AB xiaohongshu-note-research

Turn a category, a note link, or notes you already copied into a research memo. This note analysis and Xiaohongshu research workflow reads public notes, comments, and a creator's recent notes on Xiaohongshu, or works from the titles, bodies, and comments you paste, then lays out title patterns, structure, verbatim comments, and followable angles. Use it for note analysis, Xiaohongshu research, note research, and competitor notes when you want the patterns a category is already using.

ClawHub Agent Skills author: beatra-ai v0.1.2 MIT-0 16 files body ≈ 1 902 tokens Open the sourceclawhub.ai analyzed 2 d ago

Turn a category, a note link, or notes you already copied into a research memo.

As a process B 66/100 · Nearly there — weak spots: result and completion, running it twice, progress reporting

ProcedureSoftware developmentData and analyticsAI and agentstype and topics are labelled automatically from the skill text
JSON
Technical rating
A
94/100
safety, quality, tests
Safety 60%
100
Quality 40%
85
Run on models
none yet
Process rating
B
66/100
Nearly there
Result and completion w 14
0
Progress reporting w 2
0
Running it twice w 4
30
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: 16. 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 66/100

    • 0Result and completion. Does not say what the result is
    • 0Progress reporting. Says nothing while it works
    • 30Running it twice. 2 mutating operations with no state check
    • 50Failures and branches. 0 branches, has a failure section
    • 60Tools and files. Uses tools (bash) that frontmatter does not declare
    • 70Inputs and preconditions. Inputs and preconditions are listed
    • 100Steps. 14 steps
    • 100When it triggers. States when to use and when not to
    • 100Consistency. Name and required fields are in place
    • 100Execution cost. Instruction body is 1902 tokens

    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
    • -32 of 3 scripts are never mentioned in SKILL.md
    • +1No license
    • +2Single-language instructions
    • +3Description length 488: enough signal without eating the budget
    • +4Structure: 10 headings
    • +3Step-by-step instructions: 14 items
    • +4Has examples (2 code blocks)
    • +4Reference files are cited in the instructions (10 of 10)

    Quality base 70; lint remarks subtract, signals add up to 100. Result: 85.

    External checks

    ClawHub: suspicious
    The skill is a disclosed note-research workflow, but it also installs and manages a broad shared Beatra authorization, silent self-updates, upload capability, telemetry, and credential lifecycle controls that go well beyond note research.
    LLM: suspicious (high) · 28 Aug 2026