BD ow
OW Buyer (Open World Buyer) - 发飙全球购. EN: Global procurement system with AI-powered bidding evaluation. 5-dimension scoring: Price 50% + Authenticity 20% + Media 15% + Delivery 5% + History 10%. Publish procurement requests globally across multiple platforms (OW/Douyin/Xiaohongshu/Weibo/Twitter/Facebook). 中: 全球采购系统，AI智能评标。五维度评分，多平台发布采购需求，智能选出最优供应商。Trigger: 采购,招标,投标,求购,买.
As a process D 39/100 · Unfinished process — weak spots: result and completion, when it triggers, inputs and preconditions
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 · 0
✓ No critical or high findings
Files scanned: 23. Evidence is masked. Grey chips explain why severity was lowered.
Against the Agent Skills spec
- warning
frontmatter-yamlSKILL.md: the frontmatter is not valid YAML (YAML parse error: Nested mappings are not allowed in compact mappings at line 2, column 14: description: OW Buyer (Open World Buyer) - 发飙全球购. EN: Global procurement system… ^ ); fields were read line by line. The usual cause is a colon inside an unquoted value
Process rating: all ten parameters 39/100
- 0Result and completion. Does not say what the result is
- 0Inputs and preconditions. Does not say what the process needs to start
- 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. 6 mutating operations with no state check
- 40Consistency. Frontmatter name (ow) differs from the folder (ow-buyer)
- 60Tools and files. Uses tools (python) that frontmatter does not declare
- 100Steps. 42 steps
- 100Execution cost. Instruction body is 2249 tokens
- medium Safety rules and hard prohibitions inside a skill: they belong in the system prompt, here they protect nothing
- low 13 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)
- +3Output format is not stated: the model decides each time
- -2localhost URLs: will not work for another user
- -254 emoji in the instructions: noise for the model
- -35 of 5 scripts are never mentioned in SKILL.md
- +1No license
- +2Single-language instructions
- +3Description length 372: enough signal without eating the budget
- +4Structure: 43 headings
- +3Step-by-step instructions: 42 items
- +4Has examples (21 code blocks)
Quality base 70; lint remarks subtract, signals add up to 100. Result: 67.