SKILLEMALL.ai

AC food-cal-order

Order food delivery via browser automation, triggered by calendar events. Supports two modes — Direct (specific service + restaurant) and Discovery (criteria-based search across all services). Services include DoorDash, Uber Eats, Grubhub. Use when a calendar event matches food ordering patterns. Spawns sub-agents for browser control.

ClawHub Agent Skills author: Jeron Wong v1.1.0 5 files body ≈ 2 744 tokens Open the sourceclawhub.ai analyzed 2 d ago

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

ProcedurePersonal productivityInfrastructuretype and topics are labelled automatically from the skill text
JSON
Technical rating
A
95/100
safety, quality, tests
Safety 60%
100
Quality 40%
88
Run on models
none yet
Process rating
C
61/100
Has gaps
Result and completion w 14
0
When it triggers w 12
20
Running it twice w 4
30
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

    ✓ No remarks against the Agent Skills spec

    Process rating: all ten parameters 61/100

    • 0Result and completion. Does not say what the result is
    • 20When it triggers. No condition that starts the skill
    • 30Running it twice. 5 mutating operations with no state check
    • 60Tools and files. Uses tools (bash) that frontmatter does not declare
    • 70Inputs and preconditions. Inputs and preconditions are listed
    • 85Steps. 32 steps, 1 vague phrases
    • 100Failures and branches. 2 branches, has a failure section
    • 100Consistency. Name and required fields are in place
    • 100Execution cost. Instruction body is 2744 tokens
    • 100Progress reporting. Reports progress
    • medium Safety rules and hard prohibitions inside a skill: they belong in the system prompt, here they protect nothing

    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 336: enough signal without eating the budget
    • +4Structure: 18 headings
    • +3Step-by-step instructions: 32 items
    • +4Has examples (7 code blocks)
    • +4Reference files are cited in the instructions (3 of 3)

    Quality base 70; lint remarks subtract, signals add up to 100. Result: 88.

    External checks

    ClawHub: suspicious
    This skill is purpose-aligned, but it needs Review because it can place real food orders through a logged-in browser profile and some instructions weaken the promised final confirmation step.
    LLM: suspicious (high) · VirusTotal: suspicious · 10 Sept 2026