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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。

70

Quality

87%

Does it follow best practices?

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SecuritybySnyk

Passed

No findings from the security scan

SKILL.md
Quality
Evals
Security

Quality

Content

85%

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

The body is a strong, actionable playbook: concrete commands, a fixed sequenced workflow with validation checkpoints, and well-organized one-level references. The only notable weakness is redundancy — safety rules and step descriptions are repeated across multiple sections.

Suggestions

Consolidate the no-direct-DB / no-SQL rules into a single 安全红线 section and have 注意事项 reference it instead of restating it, to remove triplicated safety text.

Merge the 进度 checklist and 步骤约束 so each step's constraints live next to its checklist entry rather than being described twice.

DimensionReasoningScore

Conciseness

Dense and operational with no concept explanations Claude already knows, but the no-direct-DB / no-SQL safety rules are restated three times (安全红线, 注意事项, Phase 0 边界) and step content overlaps between the 进度 checklist, 步骤约束, and 真实链路速记, so it could be tightened.

2 / 3

Actionability

Copy-paste-ready executable commands with real IDs, exact flags, concrete SQL strings, expected HTTP endpoint (POST /api/automation/v1/data-flow/flow), and real error-message formats (Error 1062 Duplicate entry).

3 / 3

Workflow Clarity

Fixed sequence (Phase 0 → steps 1–10) with explicit validation checkpoints: primary-key pre-check difference set, user confirmation before write, and receipt verification with no-auto-retry feedback loop for the batch write.

3 / 3

Progressive Disclosure

Overview body with a per-step reference table pointing one level deep to 5 real, clearly-signaled files (parse-input, map-fields, resolve-target, csv-prepare, import-csv), all verified present in ./references/.

3 / 3

Total

11

/

12

Passed

Description

90%

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 clearly states capabilities and explicit trigger terms, answering both 'what' and 'when' in third person. Its main weakness is an over-claim: it advertises '生成SQL并写入数据库', which contradicts the body's IRON RULE that forbids SQL generation and direct database writes.

Suggestions

Replace '生成SQL并写入数据库' with the actual mechanism, e.g. '通过 ontology ds import-csv 经平台 data-flow 写入', so the description matches the body's safety constraints.

Add the supported file extensions (.jpg/.png/.pdf/.docx/.xlsx) to the description to sharpen trigger matching.

DimensionReasoningScore

Specificity

Names concrete actions and input types ('从图片或文档...提取结构化数据', '基于知识网络完成字段映射', '写入数据库'), but '生成SQL并写入数据库' over-claims the mechanism since the skill body forbids SQL generation and direct DB writes (only ontology ds import-csv is allowed).

2 / 3

Completeness

Explicitly answers both what (extract → map → write) and when ('当用户提到...自动使用此技能'), with an explicit trigger clause and unstructured-to-structured storage scenario.

3 / 3

Trigger Term Quality

Lists natural user phrasings verbatim — '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' — giving good coverage of terms users would actually say.

3 / 3

Distinctiveness Conflict Risk

Clear niche (knowledge-network field mapping + ontology write path) with distinctive trigger terms; unlikely to fire for unrelated skills.

3 / 3

Total

11

/

12

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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