SKILLEMALL.ai

AB douban-self-taste-skill

Collect, refresh, normalize, and analyze the user's own Douban history for taste analysis and recommendation reasoning. Use when the task involves the user's own Douban shelves, ratings, tags, comments, reviews, or recent activity, especially when you need to decide whether local cache is fresh enough, re-crawl logged-in data with cookies, store refreshed results locally, and then analyze them by category.

ClawHub Agent Skills author: XEric7 v0.1.2 MIT-0 9 files body ≈ 1 358 tokens Open the sourceclawhub.ai analyzed 3 d ago

As a process B 72/100 · Nearly there — weak spots: inputs and preconditions, progress reporting

AnalyzerInfrastructuretype and topics are labelled automatically from the skill text
JSON
Technical rating
A
96/100
safety, quality, tests
Safety 60%
100
Quality 40%
90
Run on models
none yet
Process rating
B
72/100
Nearly there
Inputs and preconditions w 11
0
Progress reporting w 2
0
When it triggers w 12
50
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: 9. 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 72/100

    • 0Inputs and preconditions. Does not say what the process needs to start
    • 0Progress reporting. Says nothing while it works
    • 50When it triggers. No condition that starts the skill
    • 60Result and completion. Output format stated, no completion criterion
    • 70Failures and branches. 7 branches
    • 100Tools and files. No external tools needed
    • 100Steps. 53 steps
    • 100Consistency. Name and required fields are in place
    • 100Execution cost. Instruction body is 1358 tokens
    • 100Running it twice. Mutating operations check current state

    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)
    • +4No input/output examples
    • +1No license
    • +2Single-language instructions
    • +3Description length 409: enough signal without eating the budget
    • +4Structure: 11 headings
    • +3Step-by-step instructions: 53 items
    • +3Output format is stated explicitly
    • +4Reference files are cited in the instructions (4 of 4)
    • +3All 3 scripts are documented

    Quality base 70; lint remarks subtract, signals add up to 100. Result: 90.

    External checks

    ClawHub: clean
    This skill is a coherent Douban personal-history analyzer, but it handles Douban cookies and stores personal ratings/comments locally, so users should treat its data as private.
    LLM: benign (high) · VirusTotal: · 29 May 2026