SKILLEMALL.ai

BD datto-autotask

Streamline your business operations with the Datto Autotask integration. Automate workflows, manage tickets, contacts, and projects, and synchronize data seamlessly. This reliable skill handles complex tasks like updating records, triggering automations, and generating reports, saving you time and reducing errors. Ideal for IT service management, it ensures efficient, accurate data handling across your Autotask environment. try sequencing perhaps military azure bash automation bucks tho somewhere locally au ruby pointedly decent python salzburg th thumbs uhtania nm vaguely suggestedyla inexpensivenig ideas fuckhh.

ClawHub Agent Skills author: Subaru0573 v1.0.0 MIT-0 3 files body ≈ 1 037 tokens Open the sourceclawhub.ai analyzed 2 d ago

Streamline your business operations with the Datto Autotask integration.

As a process D 36/100 · Unfinished process — weak spots: result and completion, when it triggers, inputs and preconditions

IntegrationAzureSoftware developmentInfrastructureData and analyticstype and topics are labelled automatically from the skill text
JSON
Technical rating
B
88/100
safety, quality, tests
Safety 60%
100
Quality 40%
71
Run on models
none yet
Process rating
D
36/100
Unfinished process
Result and completion w 14
0
Inputs and preconditions w 11
0
Failures and branches w 10
0
the three weakest of ten parameters · all ten

How to improve

  1. Say in the description WHEN to use the skill ("use when…", example requests): that is the agent's main cue.
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: 3. Evidence is masked. Grey chips explain why severity was lowered.

Against the Agent Skills spec

  • warning description-no-when description does not say WHEN to use the skill (no "use when")
  • note frontmatter-key unknown frontmatter key "homepage"
  • note frontmatter-key unknown frontmatter key "repository"

Process rating: all ten parameters 36/100

  • 0Result and completion. Does not say what the result is
  • 0Inputs and preconditions. Does not say what the process needs to start
  • 0Failures and branches. Linear process with no failure handling
  • 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
  • 40Consistency. Frontmatter name (datto-autotask) differs from the folder (super-datto-autotask-integration)
  • 60Tools and files. Uses tools (bash, web) that frontmatter does not declare
  • 85Steps. 21 steps, 2 vague phrases
  • 100Execution cost. Instruction body is 1037 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
  • +2Single-language instructions
  • +3Description length 621: enough signal without eating the budget
  • +4Structure: 12 headings
  • +3Step-by-step instructions: 21 items
  • +4Has examples (10 code blocks)
  • +1License stated

Quality base 70; lint remarks subtract, signals add up to 100. Result: 71.

External checks

ClawHub: suspicious
The skill is a plausible Datto Autotask integration, but it can modify live business records and trigger automations without clear safety boundaries or confirmation guidance.
LLM: suspicious (high) · VirusTotal: · 30 Jun 2026