BB alibabacloud-workbench-cli
Agent-native CLI for managing ECS instances without public IPs, primarily for single-instance operations. It supports millisecond-level remote command execution, large file transfers up to 1GB, and TCP port forwarding. It offers four authentication modes: AK, RamRoleArn, CredentialsCmd, and CredentialsURI. Use it to run commands, deploy code, view logs, check processes, transfer files, set up port forwarding, or query and filter ECS instance lists.
Agent-native CLI for managing ECS instances without public IPs, primarily for single-instance operations.
As a process B 70/100 · Nearly there — weak spots: when it triggers, inputs and preconditions, progress reporting
What is at stake
The skill contains fragments that, in the wrong hands, cost money or data. Below: what the installer risks and what the author should do.
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.
Below is the worst case for this category. The finding here is medium: the guard saw a sign, not a proof.
The skill asks for more than the task needs: broad tool access, credential environment variables, binaries. Every extra permission widens the damage from a mistake or a compromise.
Narrow allowed-tools and the variable list to the minimum; replace binaries with readable sources or scripts.
How to improve
- Address the high-severity findings: each costs 18 safety points. If one is a false positive, add the rule id to guard.allow in spec.yaml.
- 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
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high Dangerous commands
cmd-pipe-to-shellSKILL.md:29Downloads and executes remote code from an unrecognised host (pipe to shell)curl -fsSL https://workbench-cli.oss-cn-hangzhou.aliyuncs.com/install.sh | bash
Medium and low: 1
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medium Broad scope
meta-broad-allowed-toolsSKILL.md:1Broad tool permissions pre-approved: Bashallowed-tools: Bash
Files scanned: 3. 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 70/100
- 0Inputs and preconditions. Does not say what the process needs to start
- 0Progress reporting. Says nothing while it works
- 20When it triggers. No condition that starts the skill
- 60Result and completion. Output format stated, no completion criterion
- 85Steps. 6 steps, 1 vague phrases
- 100Tools and files. Tools declared in frontmatter
- 100Failures and branches. 1 branches, has a failure section
- 100Consistency. Name and required fields are in place
- 100Execution cost. Instruction body is 3036 tokens
- 100Running it twice. Mutating operations check current state
- low The response is described with custom markup (4 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)
- -2localhost URLs: will not work for another user
- -41 reference files, but SKILL.md never points to them: the model will not open them
- +2Single-language instructions
- +3Description length 452: enough signal without eating the budget
- +4Structure: 14 headings
- +3Step-by-step instructions: 6 items
- +3Output format is stated explicitly
- +4Has examples (20 code blocks)
- +1License stated
Quality base 70; lint remarks subtract, signals add up to 100. Result: 82.