SKILLEMALL.ai
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AC web-observer

Watches websites and reports what broke: uptime checks that alert when a site goes down and again when it recovers, Vercel error logs and Core Web Vitals, and GA4 traffic. Ask "is my site up", "did anything error on Vercel", or "how much traffic last week".

ClawHub Agent Skills author: Anatoli ILIEV v0.1.1 MIT-0 53 files · 45 scripts body ≈ 3 812 tokens Open the sourceclawhub.ai↗ analyzed 5 d ago

Watches websites and reports what broke: uptime checks that alert when a site goes down and again when it recovers, Vercel error logs and Core Web Vitals, and…

As a process C 57/100 · Has gaps — weak spots: result and completion, inputs and preconditions

ProcedureGoogle AnalyticsTelegramSoftware developmentData and analyticstype 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
A
96/100
safety, quality, tests
Safety 60%
100
Quality 40%
89
Run on models
none yet
Process rating
C
57/100
Has gaps
Result and completion w 14
0
Inputs and preconditions w 11
0
When it triggers w 12
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: 53. Evidence is masked. Grey chips explain why severity was lowered.

    Against the Agent Skills spec

    • note frontmatter-key unknown frontmatter key "homepage"

    Process rating: all ten parameters 57/100

    • 0Result and completion. Does not say what the result is
    • 0Inputs and preconditions. Does not say what the process needs to start
    • 50When it triggers. No condition that starts the skill
    • 50Failures and branches. 0 branches, has a failure section
    • 60Tools and files. Uses tools (bash, web) that frontmatter does not declare
    • 100Steps. 22 steps
    • 100Consistency. Name and required fields are in place
    • 100Execution cost. Instruction body is 3812 tokens
    • 100Running it twice. Mutating operations check current state
    • 100Progress reporting. Reports progress
    • medium Safety rules and hard prohibitions inside a skill: they belong in the system prompt, here they protect nothing
    • low The response is described with custom markup (4 tags): a typed call is more reliable

    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

    • +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
    • +5Description quotes 3 example trigger phrases
    • +3Description length 257: enough signal without eating the budget
    • +4Structure: 18 headings
    • +3Step-by-step instructions: 22 items
    • +4Has examples (5 code blocks)
    • +1License stated

    Quality base 70; lint remarks subtract, signals add up to 100. Result: 89.

    External checks

    ClawHub: clean
    This is a disclosed website monitoring skill that schedules checks and uses existing Vercel or GA4 credentials only for the monitoring features it describes.
    LLM: benign (high) · VirusTotal: · 23 Sept 2026