SKILLEMALL.ai

BF 1688客户接待助手

接待助手 Skill。商家在牛顿端的对话入口,负责招聘接待助手、查看工作日报、解读接待数据、培训知识库;调整接待范围 / 暂停接待统一跳转到管理页面。 接待助手是平台预设的 AI 业务员,名字固定为「接待助手」,不可修改。 触发词:接待助手、业务员、招聘、招接待助手、看日报、接待、转人工、培训、知识库、待完善、调接待范围、改买家等级、改 L 等级、暂停接待、恢复接待、管理接待助手、配触达。

ClawHub Agent Skills author: 1688AiInfra v1.0.0 MIT-0 42 files body ≈ 5 066 tokens Open the sourceclawhub.ai analyzed 3 d ago

As a process F 31/100 · Will not run — References files that are not bundled: references/capabilities/<command>.md, references/capabilities/<name>.md

ProcedureInfrastructuretype and topics are labelled automatically from the skill text
JSON
Technical rating
B
77/100
safety, quality, tests
Safety 60%
100
Quality 40%
43
Run on models
none yet
Process rating
F
31/100
Will not run
References files that are not bundled: references/capabilities/<command>.md, references/capabilities/<name>.md
Tools and files w 18
0
Result and completion w 14
0
Inputs and preconditions w 11
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.
  3. The text references files that are not there: add them or drop the references.
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: 42. Evidence is masked. Grey chips explain why severity was lowered.

Against the Agent Skills spec

  • warning name-format name should be kebab-case (lowercase letters, digits, hyphens)
  • warning description-no-when description does not say WHEN to use the skill (no "use when")
  • warning body-long SKILL.md body ≈ 5066 tokens (recommended < 5000); move details to references/
  • warning missing-ref reference to a missing file: references/capabilities/<command>.md
  • warning missing-ref reference to a missing file: references/capabilities/<name>.md

Process rating: all ten parameters 31/100

Will not run. References files that are not bundled: references/capabilities/<command>.md, references/capabilities/<name>.md
  • 0Tools and files. 2 referenced file(s) missing: references/capabilities/<command>.md, references/capabilities/<name>.md
  • 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. 22 mutating operations with no state check
  • 40Consistency. Frontmatter name (1688客户接待助手) differs from the folder (1688-cowboy)
  • 50Failures and branches. 0 branches, has a failure section
  • 70Execution cost. Instruction body is 5066 tokens
  • 100Steps. 64 steps
  • low 20 top-level sections: this looks like several domains in one skill
  • low The response is described with custom markup (5 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
  • +4No input/output examples
  • -217 emoji in the instructions: noise for the model
  • -38 of 8 scripts are never mentioned in SKILL.md
  • +1No license
  • +2Single-language instructions
  • +3Description length 196: enough signal without eating the budget
  • +4Structure: 44 headings
  • +3Step-by-step instructions: 64 items
  • +4Reference files are cited in the instructions (1 of 1)

Quality base 70; lint remarks subtract, signals add up to 100. Result: 43.

External checks

ClawHub: suspicious
This skill mostly matches a 1688 customer-service assistant, but it needs Review because it handles credentials, store/customer data, cloud knowledge persistence, and local-folder syncing with weak or incomplete disclosure and controls.
LLM: suspicious (high) · 28 May 2026