SKILLEMALL.ai

AD whatsapp-diagnostics

Diagnose and fix WhatsApp connectivity issues for OpenClaw agents. Use when: a PA is not responding, WhatsApp shows connected but messages don't arrive, the agent is online but not replying, or troubleshooting a new agent setup.

ClawHub Agent Skills author: Netanel Abergel v1.0.1 MIT-0 3 files body ≈ 1 455 tokens Open the sourceclawhub.ai analyzed 3 d ago

As a process D 47/100 · Unfinished process — weak spots: result and completion, inputs and preconditions, failures and branches

AnalyzerWhatsAppAI and agentstype and topics are labelled automatically from the skill text
JSON
Technical rating
A
92/100
safety, quality, tests
Safety 60%
98
Quality 40%
84
Run on models
none yet
Process rating
D
47/100
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

    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 · 2

    ✓ No critical or high findings

    Medium and low: 2
    • low Exfiltration exfil-secret-in-url SKILL.md:107
      Credential passed in a URL query string (normal for some APIs — verify the host is the intended service) (destination is a well-known publishing service; quoted — discussed, not commanded)
      "https://generativelanguage.googleapis.com/v1beta/models?key=…"
      known servicequoted
    • low Exfiltration exfil-secret-in-url SKILL.md:155
      Credential passed in a URL query string (normal for some APIs — verify the host is the intended service) (placeholder value)
      "https://generativelanguage.googleapis.com/v1beta/models?key=…" 2>/dev/null)
      placeholder

    Files scanned: 3. Evidence is masked. Grey chips explain why severity was lowered.

    Against the Agent Skills spec

    ✓ No remarks against the Agent Skills spec

    Process rating: all ten parameters 47/100

    • 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
    • 30Running it twice. 2 mutating operations with no state check
    • 50When it triggers. No condition that starts the skill
    • 60Tools and files. Uses tools (web) that frontmatter does not declare
    • 100Steps. 22 steps
    • 100Consistency. Name and required fields are in place
    • 100Execution cost. Instruction body is 1455 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
    • +1No license
    • +2Single-language instructions
    • +3Description length 228: enough signal without eating the budget
    • +4Structure: 10 headings
    • +3Step-by-step instructions: 22 items
    • +4Has examples (4 code blocks)

    Quality base 70; lint remarks subtract, signals add up to 100. Result: 84.

    External checks

    ClawHub: clean
    This is a visible WhatsApp troubleshooting guide, but some optional checks use live provider API keys and should be run carefully.
    LLM: benign (high) · VirusTotal: · 29 May 2026