SKILLEMALL.ai

AC lingqu-banner-config

灵渠发现页Banner配置编排。数字员工负责预占、收料、比对帧位排期、决策不一致,后台真实写操作委托 promotion-apply-skills 执行,催办交灵渠助手。三个阶段共享一张追踪表。触发场景:(1)PM私聊或群内表达预占排期意图(说"预占""帮我占排期""建推广"等)— 阶段一排期预占;(2)PM私聊发物料素材(图片/角标/资源ID/跳转链接)— 阶段二收料配置;(3)任何人在群里@数字员工并发帧位排期(说"最新版帧位排期"或含排期格式的消息)— 阶段三比对;(4)PM或业务方说"延期""恢复排期""取消"— 阶段三异常;(5)PM说"换物料""换图""换链接""换角标"— 阶段三换物料。

ClawHub Agent Skills author: CIO v1.0.12 MIT-0 8 files body ≈ 2 450 tokens Open the sourceclawhub.ai analyzed 2 d ago

灵渠发现页Banner配置编排。数字员工负责预占、收料、比对帧位排期、决策不一致,后台真实写操作委托 promotion-apply-skills 执行,催办交灵渠助手。三个阶段共享一张追踪表。触发场景:(1)PM私聊或群内表达预占排期意图(说"预占""帮我占排期""建推广"等)—…

As a process C 51/100 · Has gaps — weak spots: result and completion, when it triggers, inputs and preconditions

ProcedureAI and agentstype and topics are labelled automatically from the skill text
JSON
Technical rating
A
92/100
safety, quality, tests
Safety 60%
100
Quality 40%
81
Run on models
none yet
Process rating
C
51/100
Has gaps
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: 8. 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 51/100

  • 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
  • 30Running it twice. 1 mutating operations with no state check
  • 100Tools and files. No external tools needed
  • 100Steps. 48 steps
  • 100Consistency. Name and required fields are in place
  • 100Execution cost. Instruction body is 2450 tokens

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
  • +1No license
  • +2Single-language instructions
  • +5Description quotes 3 example trigger phrases
  • +3Description length 304: enough signal without eating the budget
  • +4Structure: 14 headings
  • +3Step-by-step instructions: 48 items
  • +4Has examples (2 code blocks)
  • +4Reference files are cited in the instructions (6 of 6)

Quality base 70; lint remarks subtract, signals add up to 100. Result: 81.

External checks

ClawHub: suspicious
This skill is not malware, but it gives chat-triggered workflows enough authority to change shared campaign state and delegate backend promotion changes that users should review its scope before installing.
LLM: suspicious (high) · VirusTotal: · 23 Jun 2026