CtrlK
BlogDocsLog inGet started
Tessl Logo

sn-da-excel-workflow

Excel 数据分析多步编排器。覆盖:(1) 读取多 Sheet Excel 文件并统计行数,(2) 大文件检测(≥10k 行自动 Parquet 优化),(3) 数据清洗(缺失值、文本标准化、无效字符),(4) 条件筛选与分类提取,(5) 跨 Sheet 统计聚合,(6) 导出 Excel/CSV 并提供下载链接。覆盖从数据读取到报告生成全流程,按步骤编排 capability 子 skill。**遇到以下任一情况就主动使用本 skill,不要自行写几行 pandas 就回答**:①用户出现触发词:Excel 分析 / 表格分析 / 数据分析 / 数据清洗 / 数据统计 / 数据筛选 / 数据可视化 / 数据导出 / 汇总统计 / 透视表 / 分组统计 / 交叉分析 / 趋势分析 / 对比分析 / 异常值检测 / 去重 / 缺失值处理 / Excel 报告 / 生成报表 / analyze Excel / data analysis / data cleaning / pivot table;②用户上传或指定了 .xlsx / .xls / .csv 文件并要求分析、清洗、统计或可视化;③任务涉及多 Sheet 读取、条件筛选、分类汇总、图表生成中的任意一项;④用户要求导出带格式的 Excel 报告或下载链接。仅不用于:不涉及表格数据的纯文本处理、图片分析(使用 sn-da-image-caption)、单个公式计算的简单问答。

70

Quality

86%

Does it follow best practices?

Run evals on this skill

Adds up to 20 points to the overall score

View guide

SecuritybySnyk

Passed

No findings from the security scan

SKILL.md
Quality
Evals
Security

Quality

Content

72%

Reviews the quality of instructions and guidance provided to agents. Good implementation is clear, handles edge cases, and produces reliable results.

The content is highly actionable and well-structured for progressive disclosure, with executable code at every step. Its weaknesses are mild verbosity from the inline sub-skill catalog and a missing validation checkpoint around the export step.

Suggestions

Move the large capability sub-skill catalog (the category tables) into a reference file and link to it, keeping only the categories actually exercised in the workflow inline — this tightens conciseness.

Dedupe the ≥100k-row prohibition so the rule lives in one canonical place (e.g., Key rules) rather than being restated in Steps 2, 4, and Key rules.

Add a validation/verification checkpoint after Step 6 export (e.g., verify the output file exists and is non-empty before presenting the download link) to close the batch-write feedback loop.

DimensionReasoningScore

Conciseness

Code blocks and warnings are lean and assume competence, but the ~90-line inline capability sub-skill catalog and the ≥100k prohibition repeated in Step 2, Step 4, and Key rules add tokens that could be tightened or moved out.

2 / 3

Actionability

Fully executable, copy-paste-ready code throughout — openpyxl read_only row counting, Parquet caching, regex text cleaning, condition masking, to_excel with download link, and a fixed CJK font block — plus a concrete threshold table.

3 / 3

Workflow Clarity

A clear six-step sequence with an explicit row-count gate exists, but the export/batch write step has no validate→fix→retry feedback loop, capping workflow clarity at 2 per the batch-operations guideline.

2 / 3

Progressive Disclosure

The body is an overview that loads capability sub-skills on demand via one-level-deep read_file references, organized by category in a navigable catalog — matching the clear-overview, one-level-deep anchor.

3 / 3

Total

10

/

12

Passed

Description

100%

Based on the skill's description, can an agent find and select it at the right time? Clear, specific descriptions lead to better discovery.

The description is specific, trigger-rich, and complete, clearly stating both capabilities and explicit use/non-use conditions in a distinct niche. It is long but every clause earns its place as trigger guidance.

DimensionReasoningScore

Specificity

Lists multiple concrete actions: '读取多 Sheet Excel 文件并统计行数', '大文件检测(≥10k 行自动 Parquet 优化)', '数据清洗', '条件筛选与分类提取', '跨 Sheet 统计聚合', '导出 Excel/CSV' — matching the anchor for several specific concrete actions.

3 / 3

Completeness

Explicitly answers both 'what' (six numbered capabilities) and 'when' ('遇到以下任一情况就主动使用本 skill' with four numbered trigger conditions) plus explicit 'when not' exclusions.

3 / 3

Trigger Term Quality

Extensive natural trigger terms users would say — 'Excel 分析 / 数据清洗 / 数据统计 / 透视表 / 分组统计 / 趋势分析 / 去重 / analyze Excel / data analysis / pivot table' — plus file extensions .xlsx/.xls/.csv, giving strong coverage.

3 / 3

Distinctiveness Conflict Risk

Distinct multi-step orchestrator niche with explicit exclusions ('不涉及表格数据的纯文本处理、图片分析(使用 sn-da-image-caption)'), making wrong-skill triggering unlikely.

3 / 3

Total

12

/

12

Passed

Validation

93%

Checks the skill against the spec for correct structure and formatting. All validation checks must pass before discovery and implementation can be scored.

Validation15 / 16 Passed

Validation for skill structure

CriteriaDescriptionResult

relative_links

Relative link issues: 1 suspicious

Warning

Total

15

/

16

Passed

Repository
OpenSenseNova/SenseNova-Skills
Reviewed

Table of Contents

Is this your skill?

If you maintain this skill, you can claim it as your own. Once claimed, you can manage eval scenarios, bundle related skills, attach documentation or rules, and ensure cross-agent compatibility.