SKILLEMALL.ai

AC pantry-tracker

Track grocery purchases and monitor food freshness using Supabase. Use when monitoring grocery orders, checking what food is expiring, logging pantry items, getting morning freshness summaries, or managing food waste. Email scanning is done by the agent using its existing email skill (e.g. gog for Gmail) — this skill does not access email directly or require email credentials.

ClawHub Agent Skills author: Diana Park v1.3.0 MIT-0 5 files body ≈ 882 tokens Open the sourceclawhub.ai analyzed 3 d ago

As a process C 53/100 · Has gaps — weak spots: result and completion, inputs and preconditions, running it twice

ProcedureSupabaseGmailInfrastructureAI and agentstype and topics are labelled automatically from the skill text
JSON
Technical rating
A
96/100
safety, quality, tests
Safety 60%
100
Quality 40%
90
Run on models
none yet
Process rating
C
53/100
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: 5. Evidence is masked. Grey chips explain why severity was lowered.

    Against the Agent Skills spec

    • note frontmatter-key unknown frontmatter key "requires"

    Process rating: all ten parameters 53/100

    • 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
    • 30Running it twice. 2 mutating operations with no state check
    • 50When it triggers. No condition that starts the skill
    • 55Failures and branches. 1 branches
    • 60Tools and files. Uses tools (python) that frontmatter does not declare
    • 100Steps. 14 steps
    • 100Consistency. Name and required fields are in place
    • 100Execution cost. Instruction body is 882 tokens
    • low The response is described with custom markup (7 tags): a typed call is more reliable

    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 379: enough signal without eating the budget
    • +4Structure: 9 headings
    • +3Step-by-step instructions: 14 items
    • +4Has examples (4 code blocks)
    • +4Reference files are cited in the instructions (1 of 1)
    • +3All 1 scripts are documented

    Quality base 70; lint remarks subtract, signals add up to 100. Result: 90.

    External checks

    ClawHub: suspicious
    The skill does what it says, but it stores email-derived grocery data in Supabase while the included database setup lacks the access controls implied by its anon-key guidance.
    LLM: suspicious (high) · VirusTotal: · 29 May 2026