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pdf-analysis

PDF 文档解析。自动区分文字型 PDF 与扫描型 PDF,覆盖:文本/表格提取、多页全量扫描、嵌入图表 caption、单位感知数值计算。

56

Quality

63%

Does it follow best practices?

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SecuritybySnyk

Low

Low-risk findings worth noting

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tessl review fix ./skills/sn-da-non-spreadsheet-analysis/capability/pdf-analysis/SKILL.md
SKILL.md
Quality
Evals
Security

Quality

Content

67%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.

The content is a strong, executable playbook with a clear type-detection first step and a useful pitfalls table, scoring well on actionability and workflow clarity. Its main weakness is conciseness — repeated boilerplate across methods and some over-explanation — which could be reduced by factoring shared helpers.

Suggestions

Factor the repeated render-page-and-caption subprocess logic into a single shared helper to cut duplicate boilerplate across Methods 3, 4, and 5.

Add an explicit validate→fix→retry feedback loop for OCR/caption failures (e.g. retry once at higher DPI on caption failure) to push workflow_clarity to 5.

Replace the placeholder CAPTION path with guidance on resolving the sn-da-image-caption skill path at runtime, since a hardcoded '/path/to/...' value is not directly executable.

DimensionReasoningScore

Conciseness

The body is mostly executable code with little concept padding, but several multi-function blocks repeat boilerplate (repeated fitz open/close, near-duplicate caption subprocess calls) and inline comments over-explain basics Claude already knows, placing it at 'mostly efficient but could be tightened'.

3 / 5

Actionability

Provides copy-paste-ready, executable Python for every method with concrete library calls and printed diagnostics, matching 'mostly executable guidance with minor gaps' (e.g. CAPTION path is a placeholder).

4 / 5

Workflow Clarity

Step 0 detection is a clear first checkpoint with an explicit warning to never skip it, and the Pitfalls table plus table-alignment verification guidance provide most checkpoints; minor validation gaps (no explicit validate→fix→retry loop for failed OCR) keep it just below 5.

4 / 5

Progressive Disclosure

Well-organized into clearly headed methods (text/table/scanned/hybrid/images) with a Common Patterns and Pitfalls section, and no nested references; for an inline single-file skill of this size this is good structure with only minor organization gaps, though some reusable helpers (caption call, unit parser) could be split out.

4 / 5

Total

15

/

20

Passed

Description

58%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.

The description is specific and capability-rich, clearly communicating what the skill does, but it omits any explicit 'Use when...' trigger guidance, which caps completeness and limits natural trigger-term coverage. Adding concrete trigger phrases and the .pdf extension would raise both completeness and trigger_term_quality.

Suggestions

Append an explicit 'Use when...' clause naming natural triggers (e.g. 'Use when parsing PDF files, extracting tables from PDFs, or reading scanned documents').

Add common synonyms and the .pdf file extension to improve trigger-term coverage.

Consider noting form filling / merge support if in scope, or keep the capability list focused to avoid over-claims.

DimensionReasoningScore

Specificity

Lists several concrete capabilities (text/table extraction, multi-page full scan, embedded chart captions, unit-aware numeric calculation); minor gaps such as form filling or merging are absent, matching the 'several specific actions; minor gaps' anchor.

4 / 5

Completeness

The description clearly states what the skill does but contains no 'Use when...' clause or equivalent trigger guidance, so per the rubric completeness is capped at 3.

3 / 5

Trigger Term Quality

Includes the natural term 'PDF 文档' and domain terms (表格提取, 图表 caption, 数值计算) but lacks common synonyms and the file extension .pdf, fitting 'some relevant keywords but missing common variations'.

3 / 5

Distinctiveness Conflict Risk

Scoped specifically to PDF parsing with concrete sub-tasks (text vs scanned detection, OCR captioning), making it mostly distinct with only minor overlap risk against generic document or image-caption skills.

4 / 5

Total

14

/

20

Passed

Validation

100%

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

Validation16 / 16 Passed

Validation for skill structure

No warnings or errors.

Repository
OpenSenseNova/SenseNova-Skills
Reviewed

Table of Contents

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