BC linkfox-geekbi-temu-search-by-image
基于商品图片在 Temu 公开市场检索视觉相似或同款商品,返回商品、销量、价格、评价、库存、供货价、店铺与品类数据。当用户明确提出 Temu 以图搜图、Temu 图搜同款、reverse image search on Temu、Temu visual product search,或提供图片/图片 URL 并明确希望在 Temu 查找相似商品时触发。未指定 Temu 的泛化图片找货请求不自动触发。本 skill 不用于跨平台找 1688 货源、图片识别或编辑、商品详情历史查询、关键词商品搜索。
基于商品图片在 Temu 公开市场检索视觉相似或同款商品,返回商品、销量、价格、评价、库存、供货价、店铺与品类数据。当用户明确提出 Temu 以图搜图、Temu 图搜同款、reverse image search on Temu、Temu visual product search,或提供图片/图片 URL…
As a process C 53/100 · 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:50High-entropy token-like string (may be an id, hash or a credential) (quoted — discussed, not commanded)or "eyJh…iJ9")
quoted
Files scanned: 7. 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 53/100
- 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
- 30Running it twice. 2 mutating operations with no state check
- 60Tools and files. Uses tools (web, python) that frontmatter does not declare
- 100Steps. 34 steps
- 100Failures and branches. 1 branches, has a failure section
- 100Consistency. Name and required fields are in place
- 100Execution cost. Instruction body is 2026 tokens
- low 11 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 3 scripts are never mentioned in SKILL.md
- +1No license
- +2Single-language instructions
- +3Description length 250: enough signal without eating the budget
- +4Structure: 13 headings
- +3Step-by-step instructions: 34 items
- +4Has examples (2 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.