SKILLEMALL.ai
GitHub ↗ RU Sign in

BC openclaw-status-monitor

Manages OpenClaw Agent status upload scripts, periodically syncing agent online status to the cloud monitoring platform

ClawHub Agent Skills author: Jax Hao Yang v1.0.5 MIT-0 6 files body ≈ 2 420 tokens Open the sourceclawhub.ai↗ analyzed 3 d ago

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

ProcedureInfrastructureAI and agentstype and topics are labelled automatically from the skill text
Runs in: OpenClaw Claude / Claude Code ChatGPT / Codex Gemini CLI Cursor GitHub Copilot / VS Code Qwen Code Kimi Code CLI Z.ai (GLM) DeepSeek (Deep Code) Mistral Vibe LangChain (deepagents) Goose OpenCode
JSON
Technical rating
B
88/100
safety, quality, tests
Safety 60%
99
Quality 40%
72
Run on models
none yet
Process rating
C
59/100
Has gaps
Result and completion w 14
0
Inputs and preconditions w 11
0
Consistency w 8
40
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 · 1

✓ No critical or high findings

Medium and low: 1
  • low Dangerous commands cmd-background-process scripts/status_uploader.py:232
    Starts a background / autostarted process
    os.setsid()

Files scanned: 6. 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 59/100

  • 0Result and completion. Does not say what the result is
  • 0Inputs and preconditions. Does not say what the process needs to start
  • 40Consistency. Frontmatter name (openclaw-status-monitor) differs from the folder (status-monitor)
  • 60Tools and files. Uses tools (python) that frontmatter does not declare
  • 70When it triggers. States when to use, but not when not to
  • 100Steps. 36 steps
  • 100Failures and branches. 3 branches, has a failure section
  • 100Execution cost. Instruction body is 2420 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)
  • +3Description length 119: 120–800 characters recommended
  • +3Output format is not stated: the model decides each time
  • +1No license
  • +2Single-language instructions
  • +4Structure: 33 headings
  • +3Step-by-step instructions: 36 items
  • +4Has examples (21 code blocks)
  • +3All 1 scripts are documented

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

External checks

ClawHub: clean
This skill does what it claims: it uploads OpenClaw agent IDs to a cloud status dashboard, but users should understand the credential and background-sync implications before enabling it.
LLM: benign (medium) · VirusTotal: · 29 May 2026