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BD linkfox-xiyou-dongcha

西柚找词（西柚洞察）亚马逊 ASIN 与关键词分析，经 LinkFox 网关转发西柚 OpenAPI。覆盖 ASIN 流量得分、反查关键词、词排名/流量趋势、BSR、ABA 周趋势、关键词竞争度与建议竞价等 17 个接口，支持 US/UK/DE 等 13 个站点。当用户提到西柚找词、西柚洞察、Xiyou、ASIN 反查关键词、关键词分析、ABA 周搜索量、流量得分、词排名趋势、xiyou keyword research, ASIN traffic score, reverse ASIN lookup, search term analysis 时触发。即使用户未写「西柚」，只要需求是通过西柚找词查亚马逊 ASIN/关键词流量与排名数据，也应触发。使用前须配置 LINKFOXAGENT_API_KEY 以及环境变量 XIYOU_CLIENT_ID、XIYOU_CLIENT_SECRET。

ClawHub Agent Skills author: linkfox-ai v0.0.8 MIT-0 7 files body ≈ 1 630 tokens Open the sourceclawhub.ai↗ analyzed 2 d ago

西柚找词（西柚洞察）亚马逊 ASIN 与关键词分析，经 LinkFox 网关转发西柚 OpenAPI。覆盖 ASIN 流量得分、反查关键词、词排名/流量趋势、BSR、ABA 周趋势、关键词竞争度与建议竞价等 17 个接口，支持 US/UK/DE 等 13 个站点。当用户提到西柚找词、西柚洞察、Xiyou、ASIN…

As a process D 46/100 · Unfinished process — weak spots: result and completion, when it triggers, inputs and preconditions

ProcedureData and analyticsCommercetype and topics are labelled automatically from the skill text
Runs in: OpenClaw Claude / Claude Code ChatGPT / Codex Gemini CLI Cursor GitHub Copilot / VS Code Qwen Code Kimi Code CLI Z.ai (GLM) DeepSeek (Deep Code) Mistral Vibe LangChain (deepagents) Goose OpenCode
JSON
Technical rating
B
77/100
safety, quality, tests
Safety 60%
79
Quality 40%
73
Run on models
none yet
Process rating
D
46/100
Unfinished process
Result and completion w 14
0
Inputs and preconditions w 11
0
Failures and branches w 10
0
the three weakest of ten parameters · all ten

What is at stake

Medium-severity findings: the skill is probably honest, but read what alarmed the scanner.

Dangerous commands medium severity

Below is the worst case for this category. The finding here is medium: the guard saw a sign, not a proof.

If you install

The skill contains commands that delete files, rewrite disks or execute code fetched from the network. The agent may run them without asking if it believes the instructions require it.

For the author

Replace destructive commands with safe equivalents that ask for confirmation, scope them to one folder, and stop piping curl into a shell: pin a version and a checksum.

How to improve

  1. Say in the description WHEN to use the skill ("use when…", example requests): that is the agent's main cue.
For the model run — optional
  • 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 · 9

✓ No critical or high findings

Medium and low: 9
  • medium Dangerous commands cmd-shell-rc SKILL.md:45
    Writes to a shell startup file
    echo 'export LINKFOXAGENT_API_KEY="your-linkfox-api-key"' >> ~/.zshrc
  • medium Dangerous commands cmd-shell-rc SKILL.md:46
    Writes to a shell startup file
    echo 'export XIYOU_CLIENT_ID="your…-id"' >> ~/.zshrc
  • medium Dangerous commands cmd-shell-rc SKILL.md:47
    Writes to a shell startup file
    echo 'export XIYOU_CLIENT_SECRET="your…ret"' >> ~/.zshrc
  • low Secrets in code secret-high-entropy-token references/api.md:108
    High-entropy token-like string (may be an id, hash or a credential) (detector / deny-list definition; documentation table row)
    | `prev…ore` | integer | 前一个 7 天自然流量得分 |
    detectortable
  • low Secrets in code secret-high-entropy-token references/api.md:109
    High-entropy token-like string (may be an id, hash or a credential) (detector / deny-list definition; documentation table row)
    | `prev…ore` | integer | 前一个 7 天广告流量得分 |
    detectortable
  • low Secrets in code secret-high-entropy-token references/api.md:110
    High-entropy token-like string (may be an id, hash or a credential) (documentation table row)
    | `prev…ore` | integer | 前一个 7 天总流量得分 |
    table
  • low Dangerous commands cmd-shell-rc references/onboarding.md:13
    Writes 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-rc references/onboarding.md:14
    Writes 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-token scripts/onboarding.py:49
    High-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-when description does not say WHEN to use the skill (no "use when")

Process rating: all ten parameters 46/100

  • 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
  • 60Tools and files. Uses tools (bash, python) that frontmatter does not declare
  • 100Steps. 37 steps
  • 100Consistency. Name and required fields are in place
  • 100Execution cost. Instruction body is 1630 tokens
  • 100Running it twice. No mutating operations
  • low 11 top-level sections: this looks like several domains in one skill
  • low The response is described with custom markup (8 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 399: enough signal without eating the budget
  • +4Structure: 17 headings
  • +3Step-by-step instructions: 37 items
  • +4Has examples (6 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.

External checks

ClawHub: suspicious
The skill largely performs the advertised Xiyou Amazon analytics, but it also has automatic external feedback reporting, durable local response storage, and account/billing helper flows that deserve user review before installation.
LLM: suspicious (high) · 14 Aug 2026