BF ai-common-sense
Use when user mentions model names, versions, pricing, API IDs, "which model should I use", "what's the latest model", "model comparison", "API pricing", "what models are available", "哪個模型最新", "模型比較", "API 定價", or when generating code that references specific AI model IDs.
As a process F 42/100 · Will not run — References files that are not bundled: references/openai.md, references/anthropic.md, references/google.md
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 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
- 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 · 3
✓ No critical or high findings
Medium and low: 3
-
medium Broad scope
meta-broad-allowed-toolsSKILL.md:1Broad tool permissions pre-approved: Bashallowed-tools: Bash Read WebSearch WebFetch
-
low Exfiltration
exfil-secret-in-urlgoogle.md:49Credential passed in a URL query string (normal for some APIs — verify the host is the intended service) (destination is a well-known publishing service; quoted — discussed, not commanded)curl "https://generativelanguage.googleapis.com/v1beta/models/gemi…ent?key=…" \
known servicequoted -
low Exfiltration
net-credential-usegoogle.md:49Credential used in a network call (verify the destination is the intended service) (destination is a well-known publishing service)curl "https://generativelanguage.googleapis.com/v1beta/models/gemi…ent?key=…" \
known service
Files scanned: 11. Evidence is masked. Grey chips explain why severity was lowered.
Against the Agent Skills spec
- warning
missing-refreference to a missing file: references/openai.md - warning
missing-refreference to a missing file: references/anthropic.md - warning
missing-refreference to a missing file: references/google.md - warning
missing-refreference to a missing file: references/meta.md - warning
missing-refreference to a missing file: references/mistral.md - warning
missing-refreference to a missing file: references/deepseek.md - warning
missing-refreference to a missing file: references/xai.md - warning
missing-refreference to a missing file: references/cohere.md - warning
missing-refreference to a missing file: references/*.md
Process rating: all ten parameters 42/100
- 0Tools and files. 9 referenced file(s) missing: references/openai.md, references/anthropic.md, references/google.md
- 0Result and completion. Does not say what the result is
- 0Inputs and preconditions. Does not say what the process needs to start
- 0Progress reporting. Says nothing while it works
- 30Running it twice. 2 mutating operations with no state check
- 50When it triggers. No condition that starts the skill
- 55Failures and branches. 1 branches
- 100Steps. 32 steps
- 100Consistency. Name and required fields are in place
- 100Execution cost. Instruction body is 2109 tokens
- low 10 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
- +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
- +5Description quotes 7 example trigger phrases
- +3Description length 273: enough signal without eating the budget
- +4Structure: 18 headings
- +3Step-by-step instructions: 32 items
- +4Has examples (2 code blocks)
Quality base 70; lint remarks subtract, signals add up to 100. Result: 77.