AC multilingual-kb-update
Add new language translations to customer service knowledge base templates, sync to Feishu Wiki, and create a GitHub issue to document the change. Use when asked to translate/add languages to KB templates, update multilingual customer service response templates, or run the multilingual KB update workflow end-to-end.
Add new language translations to customer service knowledge base templates, sync to Feishu Wiki, and create a GitHub issue to document the change.
As a process C 51/100 · Has gaps — weak spots: result and completion, when it triggers, failures and branches
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 · 1
✓ No critical or high findings
Medium and low: 1
-
low Exfiltration
net-credential-useSKILL.md:49Credential used in a network call (verify the destination is the intended service) (the skill's own vendor host)DOC_ID=$(curl -s -X GET "https://open.feishu.cn/open-apis/wiki/v2/spaces/$FEISHU_WIKI_SPACE_ID/nodes/$FEISHU_WIKI_NODE_TOKEN" \
vendor-host
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 51/100
- 0Result and completion. Does not say what the result is
- 0Failures and branches. Linear process with no failure handling
- 0Progress reporting. Says nothing while it works
- 20When it triggers. No condition that starts the skill
- 30Running it twice. 4 mutating operations with no state check
- 60Tools and files. Uses tools (web, node) that frontmatter does not declare
- 70Inputs and preconditions. Inputs and preconditions are listed
- 100Steps. 14 steps
- 100Consistency. Name and required fields are in place
- 100Execution cost. Instruction body is 1010 tokens
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 317: enough signal without eating the budget
- +4Structure: 8 headings
- +3Step-by-step instructions: 14 items
- +4Has examples (5 code blocks)
- +4Reference files are cited in the instructions (1 of 1)
Quality base 70; lint remarks subtract, signals add up to 100. Result: 88.