SKILLEMALL.ai
GitHub ↗ RU Sign in

AF openclaw-network-diagnostics

Standalone advanced network diagnostics for OpenClaw to continuously test end-to-end connectivity from OpenClaw agent to Telegram Bot API and approximate delivery to a personal Telegram client. Use when investigating latency spikes, packet loss, DPI/throttling/blocking suspicion, DNS instability, TLS/TCP issues, route changes, MTU shifts, retry/timeout behavior, or Telegram rate-limits with structured rotating JSON logs.

ClawHub Agent Skills author: h8kxrfp68z-lgtm v0.1.1 7 files body ≈ 1 418 tokens Open the sourceclawhub.ai↗ analyzed 4 d ago

As a process F 53/100 · Will not run — References files that are not bundled: references/example-log-entries.jsonl

AnalyzerTelegramInfrastructureAI 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
A
92/100
safety, quality, tests
Safety 60%
100
Quality 40%
81
Run on models
none yet
Process rating
F
53/100
Will not run
References files that are not bundled: references/example-log-entries.jsonl
Tools and files w 18
0
When it triggers w 12
20
Running it twice w 4
30
the three weakest of ten parameters · all ten

How to improve

  1. The text references files that are not there: add them or drop the references.
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: 7. Evidence is masked. Grey chips explain why severity was lowered.

Against the Agent Skills spec

  • warning missing-ref reference to a missing file: references/example-log-entries.jsonl

Process rating: all ten parameters 53/100

Will not run. References files that are not bundled: references/example-log-entries.jsonl
  • 0Tools and files. 1 referenced file(s) missing: references/example-log-entries.jsonl
  • 20When it triggers. No condition that starts the skill
  • 30Running it twice. 7 mutating operations with no state check
  • 40Result and completion. Does not say what the result is
  • 50Failures and branches. 0 branches, has a failure section
  • 70Inputs and preconditions. Inputs and preconditions are listed
  • 100Steps. 88 steps
  • 100Consistency. Name and required fields are in place
  • 100Execution cost. Instruction body is 1418 tokens
  • 100Progress reporting. Reports progress
  • low 12 top-level sections: this looks like several domains in one skill

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
  • -4Absolute local paths (C:\Users, /home/…): not portable
  • +1No license
  • +2Single-language instructions
  • +3Description length 424: enough signal without eating the budget
  • +4Structure: 17 headings
  • +3Step-by-step instructions: 88 items
  • +4Has examples (4 code blocks)
  • +4Reference files are cited in the instructions (2 of 2)
  • +3All 1 scripts are documented

Quality base 70; lint remarks subtract, signals add up to 100. Result: 81.

External checks

ClawHub: suspicious
This network diagnostic skill is mostly purpose-aligned, but it can expose Telegram credentials through validation output and an extra runtime config file.
LLM: suspicious (high) · VirusTotal: · 29 May 2026