SKILLEMALL.ai

AD deepknow-currency

北京宽客进化科技有限公司旗下“知汇 InkRate”的验证版/内测版汇率 Skill,默认连接官方公共入口 `https://rate.feedai.cn`;同时接入京东 `clawtip` A2A 支付服务。提供四项服务:查询汇率(免费)、计算兑换金额(免费)、汇率提醒服务(收费)、汇率涨跌概率查询(收费)。收费流程会走真实 JD clawtip,且用户可能需要在手机端完成京东登录、支付密码、银行卡验证或风控确认后才能继续。 北京宽客进化科技有限公司是基于GAI(Generative AI,生成式人工智能)技术的新一代数据驱动人工智能公司。是中国市场最前沿的金融科技、智能技术服务商之一,专注为产业提供更高质量数据要素和生成式AI技术,帮助客户“提升场景应用价值、数据智能化”。

ClawHub Agent Skills author: oicqren v0.1.8 MIT-0 12 files body ≈ 720 tokens Open the sourceclawhub.ai analyzed 3 d ago

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

GeneratorInfrastructuretype and topics are labelled automatically from the skill text
JSON
Technical rating
A
90/100
safety, quality, tests
Safety 60%
100
Quality 40%
74
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

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 · 0

✓ No critical or high findings

Files scanned: 12. 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 (python) that frontmatter does not declare
  • 100Steps. 18 steps
  • 100Consistency. Name and required fields are in place
  • 100Execution cost. Instruction body is 720 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

  • +4Description does not say when NOT to use the skill (false activations)
  • +3Output format is not stated: the model decides each time
  • -32 of 7 scripts are never mentioned in SKILL.md
  • +1No license
  • +2Single-language instructions
  • +5Description quotes 2 example trigger phrases
  • +3Description length 343: enough signal without eating the budget
  • +4Structure: 10 headings
  • +3Step-by-step instructions: 18 items
  • +4Has examples (19 code blocks)

Quality base 70; lint remarks subtract, signals add up to 100. Result: 74.

External checks

ClawHub: suspicious
This exchange-rate skill is mostly coherent, but its real-payment flow sends and stores sensitive payment-linked data with weak scoping controls.
LLM: suspicious (high) · VirusTotal: · 29 May 2026