SKILLEMALL.ai

AB sheet-data-enrichment

Enrich spreadsheet data by fetching external sources (URLs, APIs) to fill missing columns, then aggregate results into summary sheets. Use when: (1) a spreadsheet has URLs/links in one column and you need to extract specific info (author, title, date, etc.) into another column, (2) batch-processing rows that require visiting web pages to scrape/extract data, (3) creating pivot/summary tables from enriched data (group-by, sum, count), (4) user says fill in, complete the table, extract from links, summarize by, aggregate, enrich spreadsheet, 补全表格, 汇总统计, 信息补齐. Works with Feishu Sheets, Google Sheets, or local CSV/Excel files.

ClawHub Agent Skills author: Rong v1.0.0 MIT-0 3 files body ≈ 1 117 tokens Open the sourceclawhub.ai analyzed 3 d ago

As a process B 65/100 · Nearly there — weak spots: when it triggers, inputs and preconditions, running it twice

GeneratorExcelGoogle SheetsData and analyticsWriting and documentstype and topics are labelled automatically from the skill text
JSON
Technical rating
A
95/100
safety, quality, tests
Safety 60%
100
Quality 40%
87
Run on models
none yet
Process rating
B
65/100
Nearly there
Inputs and preconditions w 11
0
Progress reporting w 2
0
When it triggers w 12
20
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: 3. 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 65/100

    • 0Inputs and preconditions. Does not say what the process needs to start
    • 0Progress reporting. Says nothing while it works
    • 20When it triggers. No condition that starts the skill
    • 30Running it twice. 2 mutating operations with no state check
    • 60Result and completion. Output format stated, no completion criterion
    • 60Failures and branches. 2 branches
    • 100Tools and files. No external tools needed
    • 100Steps. 45 steps
    • 100Consistency. Name and required fields are in place
    • 100Execution cost. Instruction body is 1117 tokens
    • medium Safety rules and hard prohibitions inside a skill: they belong in the system prompt, here they protect nothing

    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 630: enough signal without eating the budget
    • +4Structure: 14 headings
    • +3Step-by-step instructions: 45 items
    • +3Output format is stated explicitly
    • +4Reference files are cited in the instructions (1 of 1)

    Quality base 70; lint remarks subtract, signals add up to 100. Result: 87.

    External checks

    ClawHub: clean
    This appears to be a spreadsheet enrichment skill with expected web lookups and spreadsheet updates, but users should be aware that linked spreadsheet data may be sent to external sites or APIs.
    LLM: benign (medium) · VirusTotal: · 29 May 2026