SKILLEMALL.ai

AB alibabacloud-openclaw-ecs-dingtalk

Deploy OpenClaw AI agent platform on Alibaba Cloud ECS and integrate with DingTalk bot. OpenClaw (formerly Clawdbot/Moltbot, 中文名"龙虾") is an open-source AI assistant and automation platform supporting natural language-driven task automation with multi-channel chat integration. This Skill covers the full workflow from ECS instance creation, public network configuration, base environment setup, one-click OpenClaw deployment to DingTalk bot verification. End users can chat with the AI assistant by @mentioning the bot in a DingTalk group. Triggers: "OpenClaw", "龙虾", "Clawdbot", "Moltbot", "DingTalk bot", "DingTalk AI", "deploy OpenClaw on ECS", "AI agent platform", "DingTalk integration", "openclaw dingtalk", "openclaw deploy", "DingTalk AI employee", "Alibaba Cloud OpenClaw", "Bailian + DingTalk", "DingTalk group AI", "DingTalk smart assistant", "部署龙虾", "龙虾机器人", "龙虾钉钉"

ClawHub Agent Skills author: alibabacloud-skills-team v0.0.2 MIT-0 5 files body ≈ 4 223 tokens Open the sourceclawhub.ai analyzed 2 d ago

As a process B 68/100 · Nearly there — weak spots: result and completion, when it triggers, progress reporting

IntegrationInfrastructuretype and topics are labelled automatically from the skill text
JSON
Technical rating
A
90/100
safety, quality, tests
Safety 60%
98
Quality 40%
78
Run on models
none yet
Process rating
B
68/100
Nearly there
Progress reporting w 2
0
When it triggers w 12
20
Result and completion w 14
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 · 2

✓ No critical or high findings

Medium and low: 2
  • low Dangerous commands cmd-pipe-to-shell-known-host SKILL.md:276
    Pipe-to-shell installer from a well-known host (still executes remote code) (quoted — discussed, not commanded)
    --CommandContent "apt-get update -y && apt-get install -y git curl wget && curl -fsSL --connect-timeout 30 --max-time 300 https://deb.nodesource.com/setup_22.x | bash - && apt-get install -y nodejs &&
    quoted
  • low Exfiltration net-credential-use SKILL.md:312
    Credential used in a network call (verify the destination is the intended service) (quoted — discussed, not commanded)
    --CommandContent "curl -fsSL --connect-timeout 30 --max-time 300 https://openclaw-install-scripts.oss-cn-hangzhou.aliyuncs.com/install.sh -o /tmp/openclaw-install.sh && BAILIAN_API_KEY=\$(echo '${BAIL
    quoted

Files scanned: 5. 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 68/100

  • 0Progress reporting. Says nothing while it works
  • 20When it triggers. No condition that starts the skill
  • 40Result and completion. Does not say what the result is
  • 60Tools and files. Uses tools (bash, web, node) that frontmatter does not declare
  • 70Failures and branches. 4 branches
  • 70Execution cost. Instruction body is 4223 tokens
  • 100Steps. 24 steps
  • 100Inputs and preconditions. Inputs and preconditions are listed
  • 100Consistency. Name and required fields are in place
  • 100Running it twice. Mutating operations check current state
  • medium Safety rules and hard prohibitions inside a skill: they belong in the system prompt, here they protect nothing
  • low 19 top-level sections: this looks like several domains in one skill
  • high The skill tells the model to perform an irreversible action with no human approval

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)
  • +3Description length 877: 120–800 characters recommended
  • +3Output format is not stated: the model decides each time
  • +1No license
  • +2Single-language instructions
  • +5Description quotes 15 example trigger phrases
  • +4Structure: 31 headings
  • +3Step-by-step instructions: 24 items
  • +4Has examples (16 code blocks)
  • +4Reference files are cited in the instructions (2 of 3)

Quality base 70; lint remarks subtract, signals add up to 100. Result: 78.

External checks

ClawHub: clean
This skill is a disclosed Alibaba Cloud deployment guide whose main risks are expected cloud, credential, and remote-installation risks, not hidden or malicious behavior.
LLM: benign (high) · VirusTotal: · 29 May 2026