schema-markup

When the user wants to add, fix, or optimize schema markup and structured data on their site. Also use when the user mentions "schema markup," "structured data," "JSON-LD," "rich snippets," "schema.org," "FAQ schema," "product schema," "review schema," "breadcrumb schema," "Google rich results," "knowledge panel," "star ratings in search," or "add structured data." Use this whenever someone wants their pages to show enhanced results in Google. For broader SEO issues, see seo-audit. For AI search optimization, see ai-seo.

1.14x

Quality

73%

Does it follow best practices?

Impact

93%

1.14x

Average score across 3 eval scenarios

Securityby

Passed

No known issues

Optimize this skill with Tessl

npx tessl skill review --optimize ./skills/schema-markup/SKILL.md

Quality

Discovery

89%

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

This is a strong description with excellent trigger term coverage and clear 'when to use' guidance, including helpful cross-references to related skills that reduce conflict risk. The main weakness is that the 'what' portion is somewhat general ('add, fix, or optimize') and could benefit from listing more specific concrete actions like generating JSON-LD snippets, validating markup, or implementing specific schema types.

Suggestions

Expand the capability description with more specific actions, e.g., 'Generates JSON-LD code, validates existing schema markup, implements FAQ/Product/Review schemas, and tests structured data for Google Rich Results eligibility.'

Dimension	Reasoning	Score
Specificity	The description names the domain (schema markup/structured data) and mentions actions like 'add, fix, or optimize,' but doesn't list multiple specific concrete actions such as generating JSON-LD code, validating existing markup, implementing specific schema types, or testing with Google's Rich Results tool.	2 / 3
Completeness	Clearly answers both 'what' (add, fix, or optimize schema markup and structured data) and 'when' (explicit 'Use when' clause with extensive trigger terms). Also includes helpful cross-references to related skills (seo-audit, ai-seo) for disambiguation.	3 / 3
Trigger Term Quality	Excellent coverage of natural trigger terms including 'schema markup,' 'structured data,' 'JSON-LD,' 'rich snippets,' 'schema.org,' 'FAQ schema,' 'product schema,' 'review schema,' 'breadcrumb schema,' 'Google rich results,' 'knowledge panel,' 'star ratings in search,' and 'add structured data.' These are terms users would naturally use.	3 / 3
Distinctiveness Conflict Risk	Very clearly scoped to schema markup and structured data specifically, with explicit boundary-setting by referencing related but distinct skills (seo-audit for broader SEO, ai-seo for AI search optimization). The trigger terms are highly specific to this niche.	3 / 3
	Total	11 / 12 Passed

Implementation

57%

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

This is a reasonably well-organized schema markup skill that serves as a good reference overview with appropriate progressive disclosure to detailed examples. However, it suffers from a lack of concrete, executable code examples in the main file and includes some redundant guidance (core principles, repeated assessment questions). The workflow could be strengthened with explicit sequencing and validation checkpoints.

Suggestions

Add at least one complete, executable JSON-LD example (e.g., FAQPage or Article) directly in the skill rather than deferring all examples to the reference file.

Create an explicit numbered workflow: 1. Audit existing schema → 2. Implement JSON-LD → 3. Validate with Rich Results Test → 4. If errors, fix and re-validate → 5. Deploy only when clean.

Remove or consolidate the 'Core Principles' section and 'Task-Specific Questions' section—the principles are obvious and the questions duplicate the Initial Assessment section.

Dimension	Reasoning	Score
Conciseness	The skill includes some unnecessary content like 'Core Principles' that are fairly obvious (accuracy, follow guidelines, validate), and the 'Task-Specific Questions' section restates what's already in 'Initial Assessment'. The tables and quick reference sections are efficient, but overall it could be tightened by removing redundant guidance Claude already knows.	2 / 3
Actionability	The skill provides a useful reference table and property lists, but the actual code examples are minimal—only one short @graph snippet with ellipses. Implementation sections for static/dynamic/CMS are vague descriptions rather than executable guidance. The full JSON-LD examples are deferred to a reference file, leaving the main skill without copy-paste ready code.	2 / 3
Workflow Clarity	There's a general flow (assess → implement → validate) but it's implicit rather than explicitly sequenced. The validation section lists tools but doesn't integrate validation as a checkpoint in the workflow. There's no explicit feedback loop for fixing errors and re-validating before deployment, which is important for schema implementation that could affect search results.	2 / 3
Progressive Disclosure	The skill is well-structured with clear sections, a reference table for quick lookup, and appropriately defers complete JSON-LD examples to a separate file (references/schema-examples.md). Related skills are clearly signaled at the bottom. Navigation is straightforward and one level deep.	3 / 3
	Total	9 / 12 Passed

Validation

100%

Warnings & errors only

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

Validation — 11 / 11 Passed

Validation for skill structure

No warnings or errors.

Repository: coreyhaines31/marketingskills
Commit: 1bcff9f

Reviewed: 8 days ago

Table of Contents

Discovery Implementation Validation

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.