BF cfgpu-api
A powerful OpenClaw skill for managing and automating GPU container instances on CFGPU cloud platform. Designed for AI/ML developers, researchers, and content creators, providing full lifecycle management of GPU cloud resources.
As a process F 60/100 · Will not run — References files that are not bundled: LICENSE
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 instructions or scripts send data out: environment variables, keys, file contents, chat history. You may never notice, because the agent performs the upload as "part of the task".
If the upload is not needed for the task, remove it: catalogs flag such skills and delist them. If it is needed, name the destination explicitly, say what leaves the machine, and give the user a switch.
How to improve
- The text references files that are not there: add them or drop the references.
- 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 · 6
✓ No critical or high findings
Medium and low: 6
-
medium Exfiltration
net-credential-usereferences/api-reference.md:341Credential used in a network call (verify the destination is the intended service)instances=$(curl -s -H "Authorization: $CFGPU_API_TOKEN" \
-
medium Exfiltration
net-credential-usescripts/cfgpu-helper.sh:34Credential used in a network call (verify the destination is the intended service)local curl_cmd="curl -s -H 'Authorization: $CFGPU_API_TOKEN'"
-
medium Exfiltration
net-credential-usescripts/check-config.sh:68Credential used in a network call (verify the destination is the intended service)RESPONSE=$(curl -s -H "Authorization: $TEST_TOKEN" \
-
medium Exfiltration
net-credential-useSKILL.md:147Credential used in a network call (verify the destination is the intended service)curl -X POST -H "Authorization: $CFGPU_API_TOKEN" -H "Content-Type: application/json" \
-
low Exfiltration
net-credential-useSKILL.md:141Credential used in a network call (verify the destination is the intended service) (the skill's own vendor host)curl -H "Authorization: $CFGPU_API_TOKEN" https://api.cfgpu.com/userapi/v1/region/list
vendor-host -
low Exfiltration
net-credential-useSKILL.md:144Credential used in a network call (verify the destination is the intended service) (the skill's own vendor host)curl -H "Authorization: $CFGPU_API_TOKEN" https://api.cfgpu.com/userapi/v1/gpu/list
vendor-host
Files scanned: 14. Evidence is masked. Grey chips explain why severity was lowered.
Against the Agent Skills spec
- warning
missing-refreference to a missing file: LICENSE
Process rating: all ten parameters 60/100
- 0Tools and files. 1 referenced file(s) missing: LICENSE
- 0Progress reporting. Says nothing while it works
- 50Failures and branches. 0 branches, has a failure section
- 60Result and completion. Output format stated, no completion criterion
- 70When it triggers. States when to use, but not when not to
- 70Inputs and preconditions. Inputs and preconditions are listed
- 85Steps. 58 steps, 1 vague phrases
- 100Consistency. Name and required fields are in place
- 100Execution cost. Instruction body is 2273 tokens
- 100Running it twice. Mutating operations check current state
- low 20 top-level sections: this looks like several domains in one skill
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)
- -218 emoji in the instructions: noise for the model
- +1No license
- +2Single-language instructions
- +3Description length 228: enough signal without eating the budget
- +4Structure: 39 headings
- +3Step-by-step instructions: 58 items
- +3Output format is stated explicitly
- +4Has examples (19 code blocks)
- +4Reference files are cited in the instructions (1 of 1)
- +3All 6 scripts are documented
Quality base 70; lint remarks subtract, signals add up to 100. Result: 86.