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BC 1688-supplychain-api-procurement

1688 供应链采购 API Skill。面向云端 API 调用，不提供交互式找品、复杂表格或下单流程。支持两个功能：发起找挑询并返回 instanceId；按 instanceId 查询实例数据，并由脚本按输出模式返回 instanceId、fieldDesc 和 result。此 Skill 的最终回复格式默认是 raw JSON passthrough；查询实例数据时必须使用文件模式，通过 stream_output 工具输出结果，避免进入大模型上下文。

ClawHub Agent Skills author: 1688AiInfra v0.0.6 MIT-0 19 files body ≈ 896 tokens Open the sourceclawhub.ai↗ analyzed 2 d ago

1688 供应链采购 API Skill。面向云端 API 调用，不提供交互式找品、复杂表格或下单流程。支持两个功能：发起找挑询并返回 instanceId；按 instanceId 查询实例数据，并由脚本按输出模式返回 instanceId、fieldDesc 和 result。此 Skill…

As a process C 55/100 · Has gaps — weak spots: when it triggers, inputs and preconditions, failures and branches

IntegrationProcurementAI and agentstype 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
88/100
safety, quality, tests
Safety 60%
99
Quality 40%
72
Run on models
none yet
Process rating
C
55/100
Has gaps
Inputs and preconditions w 11
0
Failures and branches w 10
0
Progress reporting w 2
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.
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 · 1

✓ No critical or high findings

Medium and low: 1
  • low Secrets in code secret-high-entropy-token scripts/settings.py:34
    High-entropy token-like string (may be an id, hash or a credential) (quoted — discussed, not commanded)
    CREATE_TASK_METHOD = "aiDi…eV2"
    quoted

Files scanned: 19. 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 55/100

  • 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) that frontmatter does not declare
  • 60Result and completion. Output format stated, no completion criterion
  • 100Steps. 40 steps
  • 100Consistency. Name and required fields are in place
  • 100Execution cost. Instruction body is 896 tokens
  • 100Running it twice. No mutating operations

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)
  • -39 of 9 scripts are never mentioned in SKILL.md
  • +1No license
  • +2Single-language instructions
  • +3Description length 232: enough signal without eating the budget
  • +4Structure: 7 headings
  • +3Step-by-step instructions: 40 items
  • +3Output format is stated explicitly
  • +4Has examples (5 code blocks)

Quality base 70; lint remarks subtract, signals add up to 100. Result: 72.

External checks

ClawHub: suspicious
The skill mostly matches its procurement API purpose, but it has under-disclosed telemetry, credential fallback, URL fetching, and a query mode that can expose result data directly into the agent context.
LLM: suspicious (high) · VirusTotal: · 5 Jun 2026