SKILLEMALL.ai
GitHub ↗ RU Sign in

BB amernet-ai-saas

Connect your AI SaaS intelligent agent to any messaging channel via OpenClaw (WhatsApp, Telegram, Slack, Discord, iMessage, and more)

ClawHub Agent Skills author: Amernet v1.1.0 MIT-0 4 files body ≈ 913 tokens Open the sourceclawhub.ai↗ analyzed 4 d ago

As a process B 74/100 · Nearly there — weak spots: result and completion, progress reporting

ProcedureSlackDiscordTelegramWhatsAppInfrastructureAI 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%
100
Quality 40%
71
Run on models
none yet
Process rating
B
74/100
Nearly there
Result and completion w 14
0
Progress reporting w 2
0
Failures and branches w 10
65
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 · 0

✓ No critical or high findings

Files scanned: 4. 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")
  • note frontmatter-key unknown frontmatter key "homepage"

Process rating: all ten parameters 74/100

  • 0Result and completion. Does not say what the result is
  • 0Progress reporting. Says nothing while it works
  • 65Failures and branches. 3 branches
  • 70When it triggers. States when to use, but not when not to
  • 70Inputs and preconditions. Inputs and preconditions are listed
  • 100Tools and files. No external tools needed
  • 100Steps. 11 steps
  • 100Consistency. Name and required fields are in place
  • 100Execution cost. Instruction body is 913 tokens
  • 100Running it twice. Mutating operations check current state

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 133: enough signal without eating the budget
  • +4Structure: 6 headings
  • +3Step-by-step instructions: 11 items
  • +4Has examples (4 code blocks)

Quality base 70; lint remarks subtract, signals add up to 100. Result: 71.

External checks

ClawHub: suspicious
This skill does what it says, but it forwards every connected-channel message and stable user identifier to an external SaaS using a broadly privileged API key, so it needs careful review before installation.
LLM: suspicious (high) · 3 Jul 2026