SKILLEMALL.ai

AD auto-purchase-executor-claw

自动下单执行虾 — 规则驱动的采购自动化执行引擎。达到触发条件后自动执行支付采购,完成从发现到付钱的闭环。 当以下情况时使用此 Skill: (1) 需要根据库存水位自动触发补货采购 (2) 需要监控价格并在跌破目标价时自动下单 (3) 需要配置定期自动续订(办公用品、SaaS 订阅等) (4) 需要生产线缺料时快速响应自动采购 (5) 需要在供应商促销窗口自动抢购锁定优惠价 (6) 用户提到"自动下单"、"自动采购"、"自动补货"、"触发采购"、"执行采购"、"自动支付"、"库存预警"、"价格触发"、"自动续订"、"紧急采购" (7) 需要设计或实现采购规则引擎、条件判断逻辑、订单生成与支付执行流程

ClawHub Agent Skills author: Ricky v1.0.0 MIT-0 6 files · 1 script body ≈ 422 tokens Open the sourceclawhub.ai analyzed 5 d ago

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

ProcedureInfrastructuretype and topics are labelled automatically from the skill text
JSON
Technical rating
A
91/100
safety, quality, tests
Safety 60%
99
Quality 40%
79
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 · 1

✓ No critical or high findings

Medium and low: 1
  • low Dangerous commands cmd-background-process scripts/monitor-and-execute.sh:260
    Starts a background / autostarted process
    nohup bash "$0" monitor >> "$LOG_FILE" 2>&1 &

Files scanned: 6. 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, web) that frontmatter does not declare
  • 100Steps. 22 steps
  • 100Consistency. Name and required fields are in place
  • 100Execution cost. Instruction body is 422 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)
  • +3Output format is not stated: the model decides each time
  • +1No license
  • +2Single-language instructions
  • +3Description length 305: enough signal without eating the budget
  • +4Structure: 7 headings
  • +3Step-by-step instructions: 22 items
  • +4Has examples (2 code blocks)
  • +4Reference files are cited in the instructions (3 of 3)
  • +3All 1 scripts are documented

Quality base 70; lint remarks subtract, signals add up to 100. Result: 79.

External checks

ClawHub: suspicious
This skill is openly built for automated purchasing, but it can run persistent live order/payment automation with weak approval controls and unsafe rule-handling details.
LLM: suspicious (high) · VirusTotal: · 29 May 2026