SKILLEMALL.ai

AC agent-cron-service

Run a hosted agent on a cron schedule — daily digests, uptime monitors, recurring scrapes, periodic reports — that fire on their own and bill exactly-once with idempotent billing and spend caps. Use when the user wants a cron job / scheduled task / recurring task / to run an agent on a schedule / a daily digest / a periodic scrape / a stateful background job that survives past a single conversation turn, without running or funding their own server, database, or scheduler.

ClawHub Agent Skills author: StructureIntelligence v1.0.0 MIT-0 2 files body ≈ 907 tokens Open the sourceclawhub.ai analyzed 33 h ago

Run a hosted agent on a cron schedule — daily digests, uptime monitors, recurring scrapes, periodic reports — that fire on their own and bill exactly-once…

As a process C 59/100 · Has gaps — weak spots: result and completion, inputs and preconditions

ProcedureAI and agentstype and topics are labelled automatically from the skill text
JSON
Technical rating
A
94/100
safety, quality, tests
Safety 60%
100
Quality 40%
85
Run on models
none yet
Process rating
C
59/100
Has gaps
Result and completion w 14
0
Inputs and preconditions w 11
0
Failures and branches w 10
50
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: 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 59/100

    • 0Result and completion. Does not say what the result is
    • 0Inputs and preconditions. Does not say what the process needs to start
    • 50Failures and branches. 0 branches, has a failure section
    • 60Tools and files. Uses tools (bash, node) that frontmatter does not declare
    • 70When it triggers. States when to use, but not when not to
    • 100Steps. 8 steps
    • 100Consistency. Name and required fields are in place
    • 100Execution cost. Instruction body is 907 tokens
    • 100Running it twice. Mutating operations check current state
    • 100Progress reporting. Reports progress

    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
    • +2Single-language instructions
    • +3Description length 476: enough signal without eating the budget
    • +4Structure: 6 headings
    • +3Step-by-step instructions: 8 items
    • +4Has examples (3 code blocks)
    • +1License stated

    Quality base 70; lint remarks subtract, signals add up to 100. Result: 85.

    External checks

    ClawHub: clean
    This is a disclosed SettleMesh scheduling helper for hosted recurring agents, with billing and authentication risks that fit its stated purpose.
    LLM: benign (high) · VirusTotal: · 9 Jul 2026