SKILLEMALL.ai

AB amazon-review-workbook

Collect all customer reviews from an Amazon product URL or product-reviews URL through a logged-in Chrome session on port 9222, export a 14-column factual workbook, optionally fill translations through DeepLX, and then help the model tag the rows into a final delivery-ready spreadsheet. Use when the user sends an Amazon link and wants review scraping, competitor review analysis, review export, or a delivery-ready spreadsheet with usernames, review links, review time, helpful votes, translation, summary, sentiment, categories, and tags.

ClawHub Agent Skills author: aduo6668 v1.0.3 MIT-0 13 files body ≈ 2 315 tokens Open the sourceclawhub.ai analyzed 2 d ago

As a process B 71/100 · Nearly there — weak spots: result and completion, running it twice, progress reporting

AnalyzerWriting and documentsData 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%
85
Run on models
none yet
Process rating
B
71/100
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: 13. 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 71/100

    • 0Result and completion. Does not say what the result is
    • 0Progress reporting. Says nothing while it works
    • 30Running it twice. 3 mutating operations with no state check
    • 60Tools and files. Uses tools (bash) that frontmatter does not declare
    • 70Inputs and preconditions. Inputs and preconditions are listed
    • 100Steps. 59 steps
    • 100When it triggers. States when to use and when not to
    • 100Failures and branches. 5 branches, has a failure section
    • 100Consistency. Name and required fields are in place
    • 100Execution cost. Instruction body is 2315 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
    • -31 of 5 scripts are never mentioned in SKILL.md
    • +1No license
    • +2Single-language instructions
    • +3Description length 541: enough signal without eating the budget
    • +4Structure: 10 headings
    • +3Step-by-step instructions: 59 items
    • +4Has examples (7 code blocks)
    • +4Reference files are cited in the instructions (3 of 3)

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

    External checks

    ClawHub: suspicious
    This skill appears to do the stated Amazon review workbook job, but it asks users to expose a logged-in Chrome profile through remote debugging and lacks strong safeguards around that access.
    LLM: suspicious (high) · VirusTotal: · 29 May 2026