BD linkfox-seerfar-ozon-keyword-back-search
Seerfar Ozon 关键词反查：按商品 SKU 列表（最多 20 个）反查 Ozon（及 Wildberries）搜索关键词，返回这些商品出现在哪些搜索词下（自然搜索词/广告搜索词），并按搜索热度、增长、商品数、卖家数、竞品数、自然排名、广告排名、曝光、转化、加购转化等多维指标筛选，每个关键词附带月搜热度、增长、市场空间、竞品/卖家数、均价、加购转化、Top 商品及自然/广告渠道、排名、曝光、转化（dimension）等市场画像，用于 Ozon 关键词反查、Listing 选词优化、竞品流量词挖掘与广告词分析。当用户提到 Ozon 关键词反查、Ozon 反查关键词、Ozon SKU 反查、Ozon 商品流量词、Ozon 竞品出单词、Ozon 自然词/广告词反查、Seerfar Ozon、Ozon keyword back search, Ozon reverse keyword lookup, Ozon SKU keyword reverse 时触发此技能。即使用户未明确提到"Seerfar"，只要其意图是按商品 SKU 反查 Ozon 搜索关键词并查看市场画像，也应触发此技能。
Seerfar Ozon 关键词反查：按商品 SKU 列表（最多 20 个）反查 Ozon（及…
As a process D 49/100 · Unfinished process — 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 · 0
✓ No critical or high findings
Files scanned: 2. 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 49/100
- 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
- 55Failures and branches. 1 branches
- 60Tools and files. Uses tools (python) that frontmatter does not declare
- 85Steps. 34 steps, 1 vague phrases
- 100Consistency. Name and required fields are in place
- 100Execution cost. Instruction body is 2797 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 (10 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 500: enough signal without eating the budget
- +4Structure: 12 headings
- +3Step-by-step instructions: 34 items
- +4Has examples (4 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.