SKILLEMALL.ai
RU Sign in

AB Data Analysis

Data analysis and visualization. Query databases, generate reports, automate spreadsheets, and turn raw data into clear, actionable insights. Use when (1) you need to analyze, visualize, or explain data; (2) the user wants reports, dashboards, or metrics turned into a decision; (3) the work involves SQL, Python, spreadsheets, BI tools, or notebooks; (4) you need to compare segments, cohorts, funnels, experiments, or time periods; (5) the user explicitly installs or references the skill for the current task.

ClawHub Agent Skills author: KirkRaman v1.0.0 MIT-0 7 files body ≈ 1 767 tokens Open the sourceclawhub.ai↗ analyzed 2 d ago

As a process B 67/100 · Nearly there — weak spots: inputs and preconditions, consistency, running it twice

AnalyzerData and analyticstype and topics are labelled automatically from the skill text
Runs in: OpenClaw Claude / Claude Code ChatGPT / Codex Gemini CLI Cursor GitHub Copilot / VS Code Qwen Code Kimi Code CLI Z.ai (GLM) DeepSeek (Deep Code) Mistral Vibe LangChain (deepagents) Goose OpenCode
JSON
Technical rating
A
90/100
safety, quality, tests
Safety 60%
100
Quality 40%
75
Run on models
none yet
Process rating
B
67/100
Nearly there
Inputs and preconditions w 11
0
Progress reporting w 2
0
Running it twice w 4
30
the three weakest of ten parameters · all ten
This is a copy of a skill from another catalog; the rating counts the canonical one: Data Analysis (ClawHub)

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: 7. Evidence is masked. Grey chips explain why severity was lowered.

    Against the Agent Skills spec

    • warning name-format name should be kebab-case (lowercase letters, digits, hyphens)
    • note frontmatter-key unknown frontmatter key "slug"
    • note frontmatter-key unknown frontmatter key "homepage"
    • note frontmatter-key unknown frontmatter key "changelog"

    Process rating: all ten parameters 67/100

    • 0Inputs and preconditions. Does not say what the process needs to start
    • 0Progress reporting. Says nothing while it works
    • 30Running it twice. 2 mutating operations with no state check
    • 40Consistency. Frontmatter name (Data Analysis) differs from the folder (jx-data-analysis)
    • 60Result and completion. Output format stated, no completion criterion
    • 70When it triggers. States when to use, but not when not to
    • 70Failures and branches. 4 branches
    • 100Tools and files. No external tools needed
    • 100Steps. 56 steps
    • 100Execution cost. Instruction body is 1767 tokens
    • medium Safety rules and hard prohibitions inside a skill: they belong in the system prompt, here they protect nothing
    • low 15 top-level sections: this looks like several domains in one skill

    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 512: enough signal without eating the budget
    • +4Structure: 22 headings
    • +3Step-by-step instructions: 56 items
    • +3Output format is stated explicitly

    Quality base 70; lint remarks subtract, signals add up to 100. Result: 75.

    External checks

    ClawHub: clean
    This is a markdown-only data analysis guidance skill with no executable code, network behavior, credential handling, or persistence.
    LLM: benign (high) · VirusTotal: · 29 May 2026