BC Aleph Cloud Self-Deployment
This skill gives an AI agent everything it needs to: 1. Provision its own VM on the Aleph Cloud network 2. Install its agent framework (OpenClaw) on the new instance 3. Configure its own credential...
This skill gives an AI agent everything it needs to: 1.
As a process C 54/100 · Has gaps — weak spots: result and completion, when it triggers, consistency
What is at stake
Medium-severity findings: the skill is probably honest, but read what alarmed the scanner.
Below is the worst case for this category. The finding here is medium: the guard saw a sign, not a proof.
The skill contains commands that delete files, rewrite disks or execute code fetched from the network. The agent may run them without asking if it believes the instructions require it.
Replace destructive commands with safe equivalents that ask for confirmation, scope them to one folder, and stop piping curl into a shell: pin a version and a checksum.
How to improve
- Say in the description WHEN to use the skill ("use when…", example requests): that is the agent's main cue.
- 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
-
medium Dangerous commands
cmd-pipe-to-shell-known-hostSKILL.md:268Pipe-to-shell installer from a well-known host (still executes remote code)curl -fsSL https://deb.nodesource.com/setup_22.x | bash -
-
medium Dangerous commands
cmd-pipe-to-shell-known-hostSKILL.md:560Pipe-to-shell installer from a well-known host (still executes remote code)curl -fsSL https://deb.nodesource.com/setup_22.x | bash -
Files scanned: 1. Evidence is masked. Grey chips explain why severity was lowered.
Against the Agent Skills spec
- warning
name-formatname should be kebab-case (lowercase letters, digits, hyphens) - warning
description-no-whendescription does not say WHEN to use the skill (no "use when")
Process rating: all ten parameters 54/100
- 0Result and completion. Does not say what the result is
- 20When it triggers. No condition that starts the skill
- 30Running it twice. 19 mutating operations with no state check
- 40Consistency. Frontmatter name (Aleph Cloud Self-Deployment) differs from the folder (aleph-vm-replication)
- 60Tools and files. Uses tools (bash, python, node) that frontmatter does not declare
- 70Inputs and preconditions. Inputs and preconditions are listed
- 70Execution cost. Instruction body is 4971 tokens
- 85Steps. 37 steps, 1 vague phrases
- 100Failures and branches. 1 branches, has a failure section
- 100Progress reporting. Reports progress
- medium Safety rules and hard prohibitions inside a skill: they belong in the system prompt, here they protect nothing
- low 15 top-level sections: this looks like several domains in one skill
- low The response is described with custom markup (6 tags): a typed call is more reliable
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 200: enough signal without eating the budget
- +4Structure: 47 headings
- +3Step-by-step instructions: 37 items
- +4Has examples (29 code blocks)
Quality base 70; lint remarks subtract, signals add up to 100. Result: 67.