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smart-data-collection

智能数据采集技能,用于从图片或文档(PDF、Word、Excel)中提取结构化数据,基于知识网络完成字段映射,生成SQL并写入数据库。当用户提到"数据采集"、"从文档提取数据"、"图片转数据"、"数据导入"、"文档数据入库"、"批量数据提取"或需要从非结构化文件中提取结构化数据并存储时,自动使用此技能。

71

Quality

88%

Does it follow best practices?

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SecuritybySnyk

Passed

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SKILL.md
Quality
Evals
Security

Quality

Content

85%Weight 40%Scale 1-5

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

A high-quality operational skill body: executable commands, a well-sequenced workflow with validation checkpoints, and clean one-level-deep reference navigation. The main weakness is conciseness — the safety rules are repeated across three sections, inflating the token budget.

Suggestions

Consolidate the safety rules into a single '安全红线' section and have '步骤约束' and '注意事项' reference it rather than restating the same prohibitions, to reduce token cost.

Move the detailed per-step constraint notes (e.g. batch-size, IN-list limits, no-backslash SQL rule) into the corresponding reference files, keeping only a one-line summary in the main checklist.

DimensionReasoningScore

Conciseness

Mostly efficient with concrete commands and a checklist, but the IRON RULEs are restated three times across '安全红线', '步骤约束', and '注意事项', adding repetition and padding that could be tightened without losing clarity.

3 / 5

Actionability

Fully executable: real CLI invocations with concrete UUIDs/table names, a worked end-to-end '真实链路速记' example, and exact failure-receipt output covering the common cases copy-paste ready.

5 / 5

Workflow Clarity

Numbered 0a–10 sequence with explicit validation checkpoints (主键预检 → 差集 → 复述确认 → 回执核对) and feedback loops (failed>0 locates the row, no auto-retry); the batch/destructive write path is fully guarded.

5 / 5

Progressive Disclosure

Clear overview in SKILL.md with a '必读 references(按步骤)' table mapping each step to one-level-deep reference files; all referenced files (parse-input, map-fields, resolve-target, csv-prepare, import-csv) exist and content is appropriately split.

5 / 5

Total

18

/

20

Passed

Description

91%Weight 40%Scale 1-5

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

A strong description: third-person, concrete on both capabilities and trigger conditions, with rich natural-language trigger phrases. The only weakness is a slight overstatement ('生成SQL') versus the actual INSERT-only data-flow write path documented in the body.

Suggestions

Replace '生成SQL并写入数据库' with a more accurate phrasing such as '通过平台 data-flow 通道执行 INSERT 写入数据库' to match the body's IRON RULE that direct SQL generation is forbidden.

Consider adding the supported file extensions (e.g. .jpg/.pdf/.xlsx) inline to further strengthen trigger-term coverage for file-based invocations.

DimensionReasoningScore

Specificity

Names the domain (images/PDF/Word/Excel) and several concrete actions (extract structured data, field mapping via knowledge network, write to database), but '生成SQL并写入数据库' slightly mischaracterizes the actual INSERT-only data-flow mechanism described in the body, a minor coverage gap.

4 / 5

Completeness

Explicitly answers both 'what' (extract→map→write) and 'when' via a concrete '当用户提到…时,自动使用此技能' trigger clause with multiple concrete trigger phrases.

5 / 5

Trigger Term Quality

Comprehensive natural Chinese trigger phrases ('数据采集', '从文档提取数据', '图片转数据', '数据导入', '文档数据入库', '批量数据提取') plus file-type coverage, matching synonyms users would actually say.

5 / 5

Distinctiveness Conflict Risk

Clear niche (unstructured files → structured DB write via ontology/data-flow) with distinct triggers; minor overlap risk with generic '数据导入' skills, but the unstructured-extraction framing distinguishes it.

4 / 5

Total

18

/

20

Passed

Validation

87%

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

Validation14 / 16 Passed

Validation for skill structure

CriteriaDescriptionResult

frontmatter_unknown_keys

Unknown frontmatter key(s) found; consider removing or moving to metadata

Warning

relative_links

Relative link issues: 1 suspicious

Warning

Total

14

/

16

Passed

Repository
UnicomAI/wanwu
Reviewed

Table of Contents

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