SKILLEMALL.ai

AB pmu-data-quality

Run data quality checks on PMU (Phasor Measurement Unit) data. Use when the user asks to validate, check, or audit PMU measurements including frequency, voltage magnitude, and phasor angle data against security limits. Also triggers for keywords like "data quality", "PMU check", "out of range", "bad data", or "security limit".

ClawHub Agent Skills author: Jiahui (Clay) Yang v1.0.0 MIT-0 5 files body ≈ 601 tokens Open the sourceclawhub.ai analyzed 2 d ago

As a process B 70/100 · Nearly there — weak spots: inputs and preconditions, consistency, progress reporting

AnalyzerInfrastructuretype and topics are labelled automatically from the skill text
JSON
Technical rating
A
95/100
safety, quality, tests
Safety 60%
95
Quality 40%
95
Run on models
none yet
Process rating
B
70/100
Nearly there
Inputs and preconditions w 11
0
Progress reporting w 2
0
Consistency w 8
40
the three weakest of ten parameters · all ten

What is at stake

Medium-severity findings: the skill is probably honest, but read what alarmed the scanner.

Broad scope medium severity

Below is the worst case for this category. The finding here is medium: the guard saw a sign, not a proof.

If you install

The skill asks for more than the task needs: broad tool access, credential environment variables, binaries. Every extra permission widens the damage from a mistake or a compromise.

For the author

Narrow allowed-tools and the variable list to the minimum; replace binaries with readable sources or scripts.

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 · 1

    ✓ No critical or high findings

    Medium and low: 1
    • medium Broad scope meta-broad-allowed-tools SKILL.md:1
      Broad tool permissions pre-approved: Bash
      allowed-tools: Bash Read Write Glob

    Files scanned: 5. 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 70/100

    • 0Inputs and preconditions. Does not say what the process needs to start
    • 0Progress reporting. Says nothing while it works
    • 40Consistency. Frontmatter name (pmu-data-quality) differs from the folder (pmu-data-quality-skill)
    • 60Result and completion. Output format stated, no completion criterion
    • 65Failures and branches. 3 branches
    • 70When it triggers. States when to use, but not when not to
    • 100Tools and files. Tools declared in frontmatter
    • 100Steps. 17 steps
    • 100Execution cost. Instruction body is 601 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

    • +4Description does not say when NOT to use the skill (false activations)
    • +1No license
    • +2Single-language instructions
    • +5Description quotes 5 example trigger phrases
    • +3Description length 328: enough signal without eating the budget
    • +4Structure: 9 headings
    • +3Step-by-step instructions: 17 items
    • +3Output format is stated explicitly
    • +4Has examples (3 code blocks)
    • +3All 1 scripts are documented

    Quality base 70; lint remarks subtract, signals add up to 100. Result: 95.

    External checks

    ClawHub: clean
    This skill locally checks PMU CSV data and writes expected local reports, with no evidence of hidden network access, credential use, or persistence.
    LLM: benign (high) · VirusTotal: · 29 May 2026