SKILLEMALL.ai

AF cron-creator

Create Clawdbot cron jobs from natural language. Use when: users want to schedule recurring messages, reminders, or check-ins without using terminal commands. Examples: 'Create a daily reminder at 8am', 'Set up a weekly check-in on Mondays', 'Remind me to drink water every 2 hours'.

sundial-org/awesome-openclaw-skills Agent Skills author: sundial-org 1 file body ≈ 1 044 tokens Open the sourcegithub.com analyzed 29 h ago

Create Clawdbot cron jobs from natural language.

As a process F 38/100 · Will not run — References files that are not bundled: scripts/cron_creator.py

GeneratorWhatsAppGitHubSoftware developmentAI and agentsPersonal productivitytype and topics are labelled automatically from the skill text
JSON
Technical rating
A
91/100
safety, quality, tests
Safety 60%
100
Quality 40%
78
Run on models
none yet
Process rating
F
38/100
Will not run
References files that are not bundled: scripts/cron_creator.py
Tools and files w 18
0
Result and completion w 14
0
Inputs and preconditions w 11
0
the three weakest of ten parameters · all ten

How to improve

  1. The text references files that are not there: add them or drop the references.
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: 1. Evidence is masked. Grey chips explain why severity was lowered.

Against the Agent Skills spec

  • warning missing-ref reference to a missing file: scripts/cron_creator.py

Process rating: all ten parameters 38/100

Will not run. References files that are not bundled: scripts/cron_creator.py
  • 0Tools and files. 1 referenced file(s) missing: scripts/cron_creator.py
  • 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. 15 mutating operations with no state check
  • 50Failures and branches. 0 branches, has a failure section
  • 100Steps. 29 steps
  • 100Consistency. Name and required fields are in place
  • 100Execution cost. Instruction body is 1044 tokens
  • low 11 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)
  • +3Output format is not stated: the model decides each time
  • +1No license
  • +2Single-language instructions
  • +3Description length 283: enough signal without eating the budget
  • +4Structure: 17 headings
  • +3Step-by-step instructions: 29 items
  • +4Has examples (6 code blocks)

Quality base 70; lint remarks subtract, signals add up to 100. Result: 78.