SKILLEMALL.ai

BD system-data-intelligence

专为需要直接操作系统应用并进行深度数据分析的场景设计。 【强制触发场景】: - 用户提及 Excel、WPS、Word、TXT、Markdown、RTZ 等文件的读取/写入/操控 - 用户想从任何应用中「抓取」「提取」「获取」数据 - 用户需要对数据进行「深度分析」「趋势研究」「异常检测」「预测」 - 用户要求生成「图表」「可视化」「仪表盘」「数据报告」 - 用户说「帮我看看这个文件里...」「分析一下这份数据...」「做个图表展示..." - 任何涉及跨应用数据流转的任务 【核心能力】:系统接口调用 × 数据深度分析 × 专业可视化 IMPORTANT: 只要涉及文件操作、数据分析、可视化中的任何一项,必须使用此 skill。 不要因为任务「看起来简单」就跳过——底层接口调用有很多坑,skill 里有避坑指南。

ClawHub Agent Skills author: zhaojie v1.0.0 16 files body ≈ 899 tokens Open the sourceclawhub.ai analyzed 3 d ago

As a process D 41/100 · Unfinished process — weak spots: result and completion, when it triggers, inputs and preconditions

ProcedureData and analyticsInfrastructuretype and topics are labelled automatically from the skill text
JSON
Technical rating
B
89/100
safety, quality, tests
Safety 60%
100
Quality 40%
73
Run on models
none yet
Process rating
D
41/100
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: 16. 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 41/100

  • 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
  • 40Consistency. Frontmatter name (system-data-intelligence) differs from the folder (system-data-intelligence-skill)
  • 60Tools and files. Uses tools (python) that frontmatter does not declare
  • 100Steps. 26 steps
  • 100Execution cost. Instruction body is 899 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
  • -31 of 6 scripts are never mentioned in SKILL.md
  • +1No license
  • +2Single-language instructions
  • +3Description length 361: enough signal without eating the budget
  • +4Structure: 25 headings
  • +3Step-by-step instructions: 26 items
  • +4Has examples (11 code blocks)
  • +4Reference files are cited in the instructions (4 of 5)

Quality base 70; lint remarks subtract, signals add up to 100. Result: 73.

External checks

ClawHub: suspicious
This skill appears intended for local file and data analysis, but it gives itself broad activation scope and includes under-disclosed local persistence plus raw macOS automation helpers.
LLM: suspicious (medium) · VirusTotal: · 29 May 2026