SKILLEMALL.ai

DF evomasterscheduler

(no description)

Not recommendedlow grade D
ClawHub Agent Skills author: blueworldmarketing v1.0.0 MIT-0 11 files · 9 scripts body ≈ 243 tokens Open the sourceclawhub.ai analyzed 3 d ago

As a process F 31/100 · Will not run — weak spots: steps, result and completion, when it triggers

ReferenceInfrastructuretype and topics are labelled automatically from the skill text
JSON
Technical rating
D
59/100
safety, quality, tests
Safety 60%
99
Quality 40%
0
Run on models
none yet
Process rating
F
31/100
Will not run
Steps w 15
0
Result and completion w 14
0
When it triggers w 12
0
the three weakest of ten parameters · all ten

How to improve

  1. Add a description to the frontmatter: without it the skill never triggers.
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 · 1

✓ No critical or high findings

Medium and low: 1
  • low Exfiltration read-dotenv cron-backup.sh:16
    Reads a .env file
    cp ~/.openclaw/.env "$BACKUP_DIR/" 2>/dev/null || true

Files scanned: 11. Evidence is masked. Grey chips explain why severity was lowered.

Against the Agent Skills spec

  • error frontmatter SKILL.md: no YAML frontmatter block found
  • error name-missing SKILL.md: frontmatter has no `name`
  • error description-missing SKILL.md: no `description` — the skill can never trigger

Process rating: all ten parameters 31/100

  • 0Steps. Prose only: no discrete steps
  • 0Result and completion. Does not say what the result is
  • 0When it triggers. No condition that starts the skill
  • 0Inputs and preconditions. Does not say what the process needs to start
  • 0Failures and branches. Linear process with no failure handling
  • 60Tools and files. Uses tools (bash) that frontmatter does not declare
  • 100Consistency. Name and required fields are in place
  • 100Execution cost. Instruction body is 243 tokens
  • 100Running it twice. No mutating operations
  • 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)
  • +3Description length 0: 120–800 characters recommended
  • +3No numbered steps or checklist
  • +3Output format is not stated: the model decides each time
  • +4No input/output examples
  • +1No license
  • +2Single-language instructions
  • +4Structure: 4 headings

Quality base 70; lint remarks subtract, signals add up to 100. Result: 0.

External checks

ClawHub: suspicious
This maintenance scheduler appears purpose-built rather than malicious, but it installs persistent jobs that can copy secrets, mutate workspace state, delete logs, and send operational details to Slack without enough scoping or user control.
LLM: suspicious (high) · VirusTotal: · 29 May 2026