SKILLEMALL.ai

AC school-run

Manages the School Run Schedule Google Sheet. Use when reading or updating the school run drop-off schedule for Damian and Zachary (date, responsible person, marks).

ClawHub Agent Skills author: cbasah v1.0.0 MIT-0 2 files body ≈ 361 tokens Open the sourceclawhub.ai analyzed 3 d ago

As a process C 61/100 · Has gaps — weak spots: result and completion, when it triggers, inputs and preconditions

ReferenceGoogle SheetsInfrastructuretype and topics are labelled automatically from the skill text
JSON
Technical rating
A
92/100
safety, quality, tests
Safety 60%
97
Quality 40%
84
Run on models
none yet
Process rating
C
61/100
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 · 3

    ✓ No critical or high findings

    Medium and low: 3
    • low Secrets in code secret-high-entropy-token SKILL.md:8
      High-entropy token-like string (may be an id, hash or a credential) (quoted — discussed, not commanded)
      This skill provides direct CLI access to the School Run Schedule Google Sheet: `1BCX…yt4`.
      quoted
    • low Secrets in code secret-high-entropy-token SKILL.md:29
      High-entropy token-like string (may be an id, hash or a credential) (quoted — discussed, not commanded)
      --params '{"spreadsheetId": "1BCX…yt4", "range": "MAR 2026!A11:C11"}'
      quoted
    • low Secrets in code secret-high-entropy-token SKILL.md:36
      High-entropy token-like string (may be an id, hash or a credential) (quoted — discussed, not commanded)
      --params '{"spreadsheetId": "1BCX…yt4", "range": "MAR 2026!C11", "valueInputOption": "USER_ENTERED"}' \
      quoted

    Files scanned: 2. 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 61/100

    • 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
    • 20When it triggers. No condition that starts the skill
    • 30Running it twice. 2 mutating operations with no state check
    • 100Tools and files. No external tools needed
    • 100Steps. 9 steps
    • 100Failures and branches. 1 branches, has a failure section
    • 100Consistency. Name and required fields are in place
    • 100Execution cost. Instruction body is 361 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
    • +1No license
    • +2Single-language instructions
    • +3Description length 165: enough signal without eating the budget
    • +4Structure: 7 headings
    • +3Step-by-step instructions: 9 items
    • +4Has examples (2 code blocks)

    Quality base 70; lint remarks subtract, signals add up to 100. Result: 84.

    External checks

    ClawHub: clean
    This is a narrowly scoped Google Sheets helper for a school-run schedule, with disclosed live read and update capability but no hidden or unrelated behavior found.
    LLM: benign (high) · VirusTotal: · 29 May 2026