SKILLEMALL.ai

BD notebook-builder

分段式 Jupyter Notebook 生成与修改工具。当用户需要创建、分段追加、修改、合并 Jupyter Notebook (.ipynb) 时使用此技能。支持的高级功能包括:(1) 分段多次生成 Notebook 内容,避免一次性生成过大导致超时或内容截断;(2) 本地图片 base64 嵌入到 Markdown cell;(3) 内置哈希判题系统(不显示明文答案);(4) 灵活的 cell 级增删改查;(5) 合并多个 notebook 为一个;(6) 导出为纯 Python 脚本;(7) 自动生成目录;(8) Cell 标签分组与重排序。适用场景包括教学课件、编程练习、技术教程、学习笔记等 notebook 的创建与维护。

ClawHub Agent Skills author: Ren Bo v1.0.3 MIT-0 5 files body ≈ 2 140 tokens Open the sourceclawhub.ai analyzed 3 d ago

As a process D 43/100 · Unfinished process — weak spots: result and completion, when it triggers, inputs and preconditions

ProcedureSoftware developmentInfrastructuretype and topics are labelled automatically from the skill text
JSON
Technical rating
B
89/100
safety, quality, tests
Safety 60%
100
Quality 40%
72
Run on models
none yet
Process rating
D
43/100
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: 5. 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 43/100

  • 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. 4 mutating operations with no state check
  • 60Tools and files. Uses tools (bash, python) that frontmatter does not declare
  • 100Steps. 36 steps
  • 100Consistency. Name and required fields are in place
  • 100Execution cost. Instruction body is 2140 tokens
  • low 15 top-level sections: this looks like several domains in one skill

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
  • -4Absolute local paths (C:\Users, /home/…): not portable
  • +2Single-language instructions
  • +3Description length 321: enough signal without eating the budget
  • +4Structure: 34 headings
  • +3Step-by-step instructions: 36 items
  • +4Has examples (15 code blocks)
  • +3All 1 scripts are documented
  • +1License stated

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

External checks

ClawHub: clean
This is a coherent Jupyter notebook creation and editing skill that runs local Python helpers and writes notebook files as expected.
LLM: benign (high) · VirusTotal: · 29 May 2026