SKILLEMALL.ai

AC excel-data-helper

Excel/CSV data quality diagnosis & interactive charts — 20+ scan modules, 6-dimension scoring, agent-powered semantic analysis, and any ECharts visualization. Fully local. Activate this skill whenever the user uploads, attaches, or mentions a .csv, .xlsx, .xls, or .tsv file, even without an explicit request. Present the skill menu immediately.

ClawHub Agent Skills author: ChartGen AI v1.0.0 MIT-0 15 files body ≈ 606 tokens Open the sourceclawhub.ai analyzed 4 d ago

As a process C 62/100 · Has gaps — weak spots: result and completion, inputs and preconditions, consistency

AnalyzerExcelData and analyticstype 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
C
62/100
Has gaps
Result and completion w 14
0
Inputs and preconditions w 11
0
Progress reporting w 2
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: 15. Evidence is masked. Grey chips explain why severity was lowered.

    Against the Agent Skills spec

    • note frontmatter-key unknown frontmatter key "homepage"

    Process rating: all ten parameters 62/100

    • 0Result and completion. Does not say what the result is
    • 0Inputs and preconditions. Does not say what the process needs to start
    • 0Progress reporting. Says nothing while it works
    • 40Consistency. Frontmatter name (excel-data-helper) differs from the folder (excel-data-quality)
    • 70When it triggers. States when to use, but not when not to
    • 70Failures and branches. 5 branches
    • 100Tools and files. No external tools needed
    • 100Steps. 13 steps
    • 100Execution cost. Instruction body is 606 tokens
    • 100Running it twice. No mutating operations

    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
    • +1No license
    • +2Single-language instructions
    • +3Description length 345: enough signal without eating the budget
    • +4Structure: 5 headings
    • +3Step-by-step instructions: 13 items
    • +4Has examples (1 code blocks)
    • +4Reference files are cited in the instructions (3 of 3)

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

    External checks

    ClawHub: clean
    This is a coherent spreadsheet analysis skill, but users should notice that its advanced chart path can leave the local-only workflow.
    LLM: benign (medium) · VirusTotal: · 29 May 2026