SKILLEMALL.ai

BD xlsx

当电子表格文件是主要输入或输出时使用此技能。这意味着用户想要:打开、读取、编辑或修复现有的 .xlsx、.xlsm、.csv 或 .tsv 文件(例如添加列、计算公式、格式化、制图、清理混乱数据);从头创建新的电子表格或从其他数据源创建;或在表格文件格式之间进行转换。当用户通过名称或路径引用电子表格文件时特别触发——即使是随意提及(如"我下载目录里的 xlsx")——并且想对其进行操作或从中生成内容。也适用于将混乱的表格数据文件(格式错误的行、错位的表头、垃圾数据)清理或重构为规范的电子表格。交付物必须是电子表格文件。当主要交付物是 Word 文档、HTML 报告、独立 Python 脚本、数据库管道或 Google Sheets API 集成时不触发,即使涉及表格数据也不触发。

agentscope-ai/CoPaw Agent Skills author: agentscope-ai Apache-2.0 15 files · 13 scripts body ≈ 1 652 tokens Open the sourcegithub.com↗ analyzed 2 d ago

当电子表格文件是主要输入或输出时使用此技能。这意味着用户想要:打开、读取、编辑或修复现有的 .xlsx、.xlsm、.csv 或 .tsv…

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

IntegrationExcelGoogle SheetsData and analyticstype and topics are labelled automatically from the skill text
JSON
Technical rating
B
90/100
safety, quality, tests
Safety 60%
100
Quality 40%
76
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: 15. 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 (xlsx) differs from the folder (xlsx-zh)
  • 60Tools and files. Uses tools (bash, python) that frontmatter does not declare
  • 100Steps. 78 steps
  • 100Execution cost. Instruction body is 1652 tokens
  • 100Running it twice. No mutating operations
  • low 13 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
  • +2Single-language instructions
  • +3Description length 344: enough signal without eating the budget
  • +4Structure: 38 headings
  • +3Step-by-step instructions: 78 items
  • +4Has examples (9 code blocks)
  • +3All 1 scripts are documented
  • +1License stated

Quality base 70; lint remarks subtract, signals add up to 100. Result: 76.