BC linkfox-seerfar-ozon-product-report-search
Seerfar Ozon 商品报表搜索：按销量、销售额、销量/销售额增长率、购物车转化率、下单转化率、价格、评分、评论数、QA数、变体数、浏览量、毛利率、退货取消率、广告费用份额、重量/体积、上架时间、品牌、卖家、配送方式、标签等多维指标筛选 Ozon 商品，返回每个商品的 SKU、标题、价格（卢布）、销量、销售额、损失销售额、转化率、评分、评论、品牌、卖家、配送方式、上架天数/月数等完整商品报表字段，用于 Ozon 选品、竞品商品分析、热销商品挖掘、价格带/转化带筛选。当用户提到 Ozon 商品报表、Ozon 选品、Ozon 商品筛选、Ozon 商品分析、Ozon 热销商品、Ozon 竞品商品分析、Ozon product report, Ozon product screener, filter Ozon products by sales, Ozon best-seller mining, Seerfar Ozon 商品报表时触发此技能。即使用户未明确提到"Seerfar"，只要其意图是按多指标筛选 Ozon 商品并查看商品级报表，也应触发此技能。
Seerfar Ozon 商品报表搜索：按销量、销售额、销量/销售额增长率、购物车转化率、下单转化率、价格、评分、评论数、QA数、变体数、浏览量、毛利率、退货取消率、广告费用份额、重量/体积、上架时间、品牌、卖家、配送方式、标签等多维指标筛选 Ozon 商品，返回每个商品的…
As a process C 56/100 · Has gaps — weak spots: result and completion, when it triggers, inputs and preconditions
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 · 3
✓ No critical or high findings
Medium and low: 3
-
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 56/100
- 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
- 20When it triggers. No condition that starts the skill
- 60Tools and files. Uses tools (python) that frontmatter does not declare
- 100Steps. 38 steps
- 100Failures and branches. 1 branches, has a failure section
- 100Consistency. Name and required fields are in place
- 100Execution cost. Instruction body is 2681 tokens
- 100Running it twice. No mutating operations
- low 10 top-level sections: this looks like several domains in one skill
- low The response is described with custom markup (12 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 484: enough signal without eating the budget
- +4Structure: 12 headings
- +3Step-by-step instructions: 38 items
- +4Has examples (5 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.