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wigolo-extract

Local-first structured extraction from any webpage — tables, definition lists, key-value pairs, JSON-LD, microdata, chart hints (SVG titles / aria-labels / figcaptions), brand assets, and metadata. Use when the user wants structured data, pricing tables, feature comparisons, or says "extract the table", "get structured data", "pull the pricing", "extract as JSON". For autonomous navigation across many pages, use wigolo's `agent` tool instead.

Quality

94%

Does it follow best practices?

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SecuritybySnyk

Low

Low-risk findings worth noting

SKILL.md
Quality
Evals
Security

Quality

Content

92%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 well-crafted, tool-invocation-style skill body: executable JSON examples, an explicit mode-selection table, anti-patterns, and negative-scope guidance, with no filler or background explanations. Its single weakness is redundancy — the Modes table and the dedicated mode sections repeat the same information almost verbatim.

Suggestions

Drop the standalone 'Schema Mode' and 'Brand Mode' sections (or the corresponding Modes table rows) — the table already states the provenance and null-on-hallucination behavior verbatim, so pick one location for each.

State the 'always prefer structured over tables' rule once (e.g., in the Modes section) instead of repeating it in the Modes emphasis, Anti-Patterns, and the Quick Reference comment.

In the description, add a short deflection for plain page content (e.g., 'for markdown content use wigolo-fetch') to mirror the existing agent-tool boundary and sharpen single-page conflict behavior.

DimensionReasoningScore

Conciseness

The body is lean and teaches only wigolo-specific behavior (modes, anti-patterns, token budget) rather than concepts Claude already knows. However, the Modes table rows for `schema` and `brand` are restated nearly verbatim in the "Schema Mode" and "Brand Mode" sections, and the "use structured, not tables" guidance appears three times (Modes emphasis, Anti-Patterns, Quick Reference comment) — minor trimming would earn the top score.

4 / 5

Actionability

The Quick Reference gives copy-paste-ready tool-call payloads for every common case (structured, schema, selector, metadata, raw-HTML), plus a concrete `named_schema` example and a decision table with explicit "when to use" guidance. This is fully executable instruction covering the common cases.

5 / 5

Workflow Clarity

This is a simple single-action skill (choose a mode, invoke the tool) and the mode-selection decision is unambiguous: `structured` is marked as the default in three places, alternatives have explicit "when to use" criteria, and "When NOT to use" plus Anti-Patterns handle the failure paths. No destructive or batch operations exist that would require validation checkpoints.

5 / 5

Progressive Disclosure

There are no bundle files (no references/, scripts/, or assets/ directories) and none are needed at this size; the body is compact and organized into clearly headed sections with all detail appropriately inline. The only external pointers are the one-level-deep, clearly signaled "See Also" links to sibling skills — no nested or buried references.

5 / 5

Total

19

/

20

Passed

Description

96%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.

An exemplary description: third-person voice, concrete capability inventory, explicit 'Use when' triggers with quoted natural phrasings, and boundary guidance pointing multi-page work to the agent tool. The only improvement space is explicitly distinguishing it from a plain page-fetch/content skill.

DimensionReasoningScore

Specificity

The description enumerates concrete extraction targets — "tables, definition lists, key-value pairs, JSON-LD, microdata, chart hints (SVG titles / aria-labels / figcaptions), brand assets, and metadata" — giving comprehensive, specific coverage rather than vague language. It matches the anchor for multiple specific concrete actions; nothing is padded or abstract.

5 / 5

Completeness

It explicitly answers both questions: the "what" is "Local-first structured extraction from any webpage" with a concrete inventory, and the "when" is an explicit "Use when the user wants structured data... or says..." clause with concrete trigger phrases. This mirrors the anchor-5 example structure almost exactly.

5 / 5

Trigger Term Quality

Natural user phrasings are quoted directly — "extract the table", "get structured data", "pull the pricing", "extract as JSON" — alongside keyword coverage like "structured data, pricing tables, feature comparisons". This covers synonyms and real utterances comprehensively; it is not merely technical jargon.

5 / 5

Distinctiveness Conflict Risk

The niche (structured data extraction, with clear deflection of multi-page work to wigolo's `agent` tool) is mostly distinct with quoted trigger phrases. However, the closely related sibling `wigolo-fetch` (markdown/content from pages) is not explicitly deflected in the description itself, leaving minor overlap risk for generic "get this page's data" requests.

4 / 5

Total

19

/

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.

Validation — 15 / 16 Passed

Validation for skill structure

CriteriaDescriptionResult

relative_links

Relative link issues: 2 suspicious

Warning

Total

15

/

16

Passed

Repository

KnockOutEZ/wigolo

Path

skills/wigolo-extract/SKILL.md

Reviewed

Table of Contents

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