AC openclaw-remote-install
One-click remote OpenClaw deployment via SSH. Auto-detects OS and selects best method (Docker/Podman/npm). Use when: (1) Installing on VPS/cloud servers, (2) Automating multi-machine deployment, (3) Configuring models/channels/gateway post-install.
As a process C 50/100 · Has gaps — weak spots: result and completion, when it triggers, inputs and preconditions
How to improve
- 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 · 3
✓ No critical or high findings
Medium and low: 3
-
low Dangerous commands
cmd-pipe-to-shellscripts/install_openclaw_remote.sh:284Downloads and executes remote code from an unrecognised host (pipe to shell) (string literal in code, not executed; the skill's own vendor host)install_cmd="curl -fsSL https://get.docker.com | sh"
code literalvendor-host -
low Dangerous commands
cmd-pipe-to-shellscripts/install_openclaw_remote.sh:325Downloads and executes remote code from an unrecognised host (pipe to shell) (string literal in code, not executed; the skill's own vendor host)install_cmd="curl -fsSL https://openclaw.ai/install-cli.sh | bash -s -- --version $VERSION"
code literalvendor-host -
low Dangerous commands
cmd-pipe-to-shellscripts/install_openclaw_remote.sh:333Downloads and executes remote code from an unrecognised host (pipe to shell) (string literal in code, not executed; the skill's own vendor host)install_cmd="curl -fsSL https://openclaw.ai/install.sh | bash -s --"
code literalvendor-host
Files scanned: 4. 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 50/100
- 0Result and completion. Does not say what the result is
- 0Inputs and preconditions. Does not say what the process needs to start
- 20When it triggers. No condition that starts the skill
- 30Running it twice. 2 mutating operations with no state check
- 50Failures and branches. 0 branches, has a failure section
- 60Tools and files. Uses tools (web, python, node) that frontmatter does not declare
- 100Steps. 25 steps
- 100Consistency. Name and required fields are in place
- 100Execution cost. Instruction body is 1139 tokens
- 100Progress reporting. Reports progress
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 248: enough signal without eating the budget
- +4Structure: 22 headings
- +3Step-by-step instructions: 25 items
- +4Has examples (12 code blocks)
- +3All 2 scripts are documented
Quality base 70; lint remarks subtract, signals add up to 100. Result: 87.