SKILLEMALL.ai

BC astrill-watchdog

Monitor and auto-reconnect Astrill VPN on Ubuntu Linux (deb GUI package). Detects dropped connections via tun interface + ping, then reconnects using Astrill's built-in /reconnect command or full process restart with /autostart. No sudo required.

modbender/skill-library-mcp Agent Skills author: modbender MIT 5 files · 2 scripts body ≈ 978 tokens Open the sourcegithub.com analyzed 3 d ago

Monitor and auto-reconnect Astrill VPN on Ubuntu Linux (deb GUI package).

As a process C 60/100 · Has gaps — weak spots: result and completion, when it triggers, failures and branches

ProcedureAI and agentstype and topics are labelled automatically from the skill text
JSON
Technical rating
B
87/100
safety, quality, tests
Safety 60%
97
Quality 40%
72
Run on models
none yet
Process rating
C
60/100
Has gaps
Result and completion w 14
0
Failures and branches w 10
0
When it triggers w 12
20
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 · 3

✓ No critical or high findings

Medium and low: 3
  • low Dangerous commands cmd-background-process astrill-watchdog.sh:102
    Starts a background / autostarted process
    env "${DESKTOP_ENV[@]}" run_as_astrill nohup "$ASTRILL_BIN" /autostart &>/dev/null &
  • low Dangerous commands cmd-background-process astrill-watchdog.sh:103
    Starts a background / autostarted process
    disown $! 2>/dev/null || true
  • low Dangerous commands cmd-background-process astrill-watchdog.sh:154
    Starts a background / autostarted process
    nohup bash "$0" _loop >> "$LOG_FILE" 2>&1 &

Files scanned: 5. 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")

Process rating: all ten parameters 60/100

  • 0Result and completion. Does not say what the result is
  • 0Failures and branches. Linear process with no failure handling
  • 20When it triggers. No condition that starts the skill
  • 30Running it twice. 4 mutating operations with no state check
  • 70Inputs and preconditions. Inputs and preconditions are listed
  • 100Tools and files. No external tools needed
  • 100Steps. 16 steps
  • 100Consistency. Name and required fields are in place
  • 100Execution cost. Instruction body is 978 tokens
  • 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
  • +1No license
  • +2Single-language instructions
  • +3Description length 246: enough signal without eating the budget
  • +4Structure: 13 headings
  • +3Step-by-step instructions: 16 items
  • +4Has examples (4 code blocks)

Quality base 70; lint remarks subtract, signals add up to 100. Result: 72.