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BD 1688-multi-shop-compare

1688 多店经营对比分析 skill。通过获取多店铺绑定关系及各店铺经营数据，按"店铺层→类目层→商品层"三层结构做横向对比分析，输出多维排名、商品分层诊断、异常归因、机会识别和落到单品的行动建议。

ClawHub Agent Skills author: 1688AiInfra v1.0.0 MIT-0 23 files body ≈ 6 601 tokens Open the sourceclawhub.ai↗ analyzed 3 d ago

As a process D 44/100 · Unfinished process — weak spots: result and completion, when it triggers, inputs and preconditions

ProcedureInfrastructuretype 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
82/100
safety, quality, tests
Safety 60%
100
Quality 40%
56
Run on models
none yet
Process rating
D
44/100
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

How to improve

  1. Say in the description WHEN to use the skill ("use when…", example requests): that is the agent's main cue.
  2. The SKILL.md body is over 5,000 tokens: move reference detail into references/ and load it when needed.
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 · 0

✓ No critical or high findings

Files scanned: 23. 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")
  • warning body-long SKILL.md body ≈ 6601 tokens (recommended < 5000); move details to references/
  • note frontmatter-key unknown frontmatter key "install_source"
  • note frontmatter-key unknown frontmatter key "enabled_at"

Process rating: all ten parameters 44/100

  • 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 (python) that frontmatter does not declare
  • 70Execution cost. Instruction body is 6601 tokens
  • 100Steps. 176 steps
  • 100Consistency. Name and required fields are in place
  • 100Running it twice. No mutating operations
  • low 11 top-level sections: this looks like several domains in one skill

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)
  • +3Description length 100: 120–800 characters recommended
  • +3Output format is not stated: the model decides each time
  • -233 emoji in the instructions: noise for the model
  • -36 of 7 scripts are never mentioned in SKILL.md
  • +1No license
  • +2Single-language instructions
  • +4Structure: 60 headings
  • +3Step-by-step instructions: 176 items
  • +4Has examples (17 code blocks)
  • +4Reference files are cited in the instructions (3 of 3)

Quality base 70; lint remarks subtract, signals add up to 100. Result: 56.

External checks

ClawHub: clean
This skill legitimately supports 1688 multi-shop analysis, but it should only be installed by users comfortable sharing 1688 access keys and shop business data with the OpenClaw/1688 gateway.
LLM: benign (high) · VirusTotal: · 29 May 2026