BC linkfox-1688-product-detail
1688 商品详情查询。通过 offerId 获取商品标题、属性、SKU/库存、1 件零售价、2 件及以上批发阶梯价、外币价、起批量、图片/视频、物流包装、供应商服务、混批、发票与证书等采购信息。用户提到 1688 商品详情、1688 链接或商品 ID 查货、SKU 价格库存、1 件采购价、跨境采购核价、供应商评估、包装重量、1688 product detail、offerId lookup、sourcing details 时触发。即使未明确说“商详”，只要希望根据 1688 offerId 核对货源、报价、MOQ、SKU、物流或供应商数据，也应触发此技能。
1688 商品详情查询。通过 offerId 获取商品标题、属性、SKU/库存、1 件零售价、2 件及以上批发阶梯价、外币价、起批量、图片/视频、物流包装、供应商服务、混批、发票与证书等采购信息。用户提到 1688 商品详情、1688 链接或商品 ID 查货、SKU 价格库存、1…
As a process C 55/100 · Has gaps — weak spots: result and completion, inputs and preconditions, running it twice
How to improve
- Say in the description WHEN to use the skill ("use when…", example requests): that is the agent's main cue.
- 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 · 4
✓ No critical or high findings
Medium and low: 4
-
low Secrets in code
secret-high-entropy-tokenreferences/api.md:174High-entropy token-like string (may be an id, hash or a credential)| coll…ent | string | 最近 30 天 48 小时揽收率 |
-
low Dangerous commands
cmd-shell-rcreferences/onboarding.md:13Writes to a shell startup file (quoted — discussed, not commanded)- macOS zsh：`echo 'export LINKFOX_AGENT_API_KEY="<key>"' >> ~/.zshrc && source ~/.zshrc`
quoted -
low Dangerous commands
cmd-shell-rcreferences/onboarding.md:14Writes to a shell startup file (detector / deny-list definition)- Linux bash：`echo 'export LINKFOX_AGENT_API_KEY="<key>"' >> ~/.bashrc && source ~/.bashrc`
detector -
low Secrets in code
secret-high-entropy-tokenscripts/onboarding.py:49High-entropy token-like string (may be an id, hash or a credential) (quoted — discussed, not commanded)or "eyJh…iJ9")
quoted
Files scanned: 6. Evidence is masked. Grey chips explain why severity was lowered.
Against the Agent Skills spec
- warning
description-no-whendescription does not say WHEN to use the skill (no "use when")
Process rating: all ten parameters 55/100
- 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. 5 mutating operations with no state check
- 55Failures and branches. 1 branches
- 60Tools and files. Uses tools (python) that frontmatter does not declare
- 70When it triggers. States when to use, but not when not to
- 100Steps. 36 steps
- 100Consistency. Name and required fields are in place
- 100Execution cost. Instruction body is 1949 tokens
- low 10 top-level sections: this looks like several domains in one skill
- low The response is described with custom markup (7 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)
- +3Output format is not stated: the model decides each time
- -31 of 2 scripts are never mentioned in SKILL.md
- +1No license
- +2Single-language instructions
- +3Description length 284: enough signal without eating the budget
- +4Structure: 12 headings
- +3Step-by-step instructions: 36 items
- +4Has examples (3 code blocks)
- +4Reference files are cited in the instructions (2 of 2)
Quality base 70; lint remarks subtract, signals add up to 100. Result: 73.