CtrlK
BlogDocsLog inGet started
Tessl Logo

extraction-pipeline-patterns

Document extraction pipeline architecture and patterns

50

Quality

55%

Does it follow best practices?

Run evals on this skill

Adds up to 20 points to the overall score

View guide

SecuritybySnyk

Low

Low-risk findings worth noting

Fix and improve this skill with Tessl

tessl review fix ./.ai-rulez/skills/extraction-pipeline-patterns/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 well-structured, dense architecture reference with clear sequencing and concrete file locations, but its code examples are pseudocode rather than executable snippets and several reference tables are inlined instead of split into bundle files.

Suggestions

Replace the two pseudocode blocks with minimal executable Rust snippets (real function signatures and a working match arm) so guidance is copy-paste ready.

Move the 75-format extractor table and the feature-flag matrix into references/ files (e.g. FORMATS.md, FEATURE_MATRIX.md is already named) and link to them from a leaner overview.

Add an explicit validate→fix→retry feedback loop for the fallback strategies (e.g. 'If OCR confidence < threshold, re-run with alternate backend; if still failing, return both results').

DimensionReasoningScore

Conciseness

The body is information-dense with tables and code, assumes Rust competence, and avoids explaining basic concepts; minor redundancy between the inline rules and 'Critical Rules' sections keeps it just below a 5.

4 / 5

Actionability

Concrete file paths and named modules are actionable for navigation, but both code blocks are explicitly labeled '// Pseudocode' rather than executable code, matching the rubric's pseudocode anchor.

3 / 5

Workflow Clarity

The four-step pipeline (detection → extraction → fallback → post-processing) is clearly sequenced and the mandatory post-pipeline validators plus Critical Rules act as checkpoints, though explicit fix-and-retry feedback loops are only implied.

4 / 5

Progressive Disclosure

Sections are well-organized with clear headers and a Related Skills pointer, but the format and feature-flag reference tables are inlined in a >50-line document where separate reference files could lighten the overview.

4 / 5

Total

15

/

20

Passed

Description

43%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 names a clear domain but reads as a noun phrase about architecture rather than a statement of concrete actions, and it entirely lacks trigger guidance for when to use the skill. Adding action verbs and a 'Use when...' clause would materially improve it.

Suggestions

Lead with concrete verbs, e.g. 'Document extraction pipeline: detect file formats, route to format-specific extractors, and apply fallback strategies for 75+ file formats.'

Add a 'Use when...' trigger clause naming natural terms users say — 'Use when working with PDF, DOCX, Excel, HTML, image, or archive extraction, or when handling encrypted/OCR fallbacks.'

Include common file extensions (PDF, DOCX, XLSX, ZIP) to improve trigger-term coverage and distinctiveness.

DimensionReasoningScore

Specificity

The phrase 'Document extraction pipeline architecture and patterns' names the domain but offers no concrete actions — 'architecture and patterns' is abstract rather than a verb like 'extract', 'detect', or 'route'.

2 / 5

Completeness

A clear 'what' is present (extraction pipeline architecture and patterns) but there is no 'Use when...' clause or trigger guidance, which caps completeness at 3 per the rubric.

3 / 5

Trigger Term Quality

'Document extraction' is a natural phrase a user might say, but the description omits common variations and file extensions (PDF, DOCX, Excel, archives) that users actually mention.

3 / 5

Distinctiveness Conflict Risk

'Document extraction pipeline' is somewhat specific but 'document extraction' broadly overlaps with other document/PDF extraction skills, so conflict risk remains.

3 / 5

Total

11

/

20

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

frontmatter_unknown_keys

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

Warning

Total

15

/

16

Passed

Repository
xberg-io/xberg
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.