create-geo-charts

Creates data visualizations (charts, graphs, tables) optimized for AI engine parsing and citation. Produces inline SVG/HTML with text summaries, data tables, and JSON-LD so AI engines can quote the data.

Quality

72%

Does it follow best practices?

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Securityby

Passed

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tessl review fix ./create-geo-charts/SKILL.md

Quality

Content

77%

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

The skill is highly actionable and well-sequenced with strong validation checkpoints, but it is monolithic and verbose for its size, leaving conciseness and progressive disclosure as the weaker dimensions.

Suggestions

Move the large Design System section and the Complete Output Template into separate reference files (e.g. references/design-system.md, references/output-template.md) referenced one level deep from SKILL.md to improve progressive disclosure.

De-duplicate the 'AI engines cite text, not pixels' framing so it appears once and trim the repeated rationale in Step 7 to tighten conciseness.

Verify referenced bundle paths actually resolve; with no references/ directory present, any 'See X.md' links would currently be broken.

Dimension	Reasoning	Score
Conciseness	The body is mostly efficient with concrete, dense guidance, but it is long (398 lines) and restates its core thesis repeatedly ('AI engines cite text, not pixels' appears in the intro, Step 4, and Step 7), so it is not fully lean.	2 / 3
Actionability	Provides fully executable, copy-paste-ready artifacts — JSON-LD Dataset schema, semantic HTML table markup, SVG accessibility attributes, and a nine-item output template — matching the score-3 anchor for specific, complete examples.	3 / 3
Workflow Clarity	A clearly numbered 8-step workflow with an explicit QA validation step (Step 9) and a fix-then-re-verify feedback loop ('Fix them immediately... Then re-open and verify'), plus a closing quality checklist, satisfies the explicit-checkpoints anchor.	3 / 3
Progressive Disclosure	No bundle files exist in references/scripts/assets and none are referenced, so a large skill is delivered as a single monolithic file; substantial sections (design system, output template, QA) remain inline rather than being split into one-level-deep references.	2 / 3
	Total	10 / 12 Passed

Description

67%

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 occupies a clear, distinctive niche, but it omits an explicit 'when to use' trigger clause, leaving the activation context implicit and capping completeness and trigger-term quality.

Suggestions

Append an explicit 'Use when...' clause, e.g. 'Use when the user asks for charts, data visualizations, or tables that AI engines can parse, quote, and cite.'

Add natural user-voice trigger variations such as 'data visualizations', 'infographics', or 'make this chart citable' alongside the existing technical terms.

Lead with the primary verb/action set before the GEO rationale so the what-then-when ordering reads more naturally.

Dimension	Reasoning	Score
Specificity	Lists multiple concrete actions — 'charts, graphs, tables', 'inline SVG/HTML', 'text summaries, data tables, and JSON-LD' — directly matching the score-3 anchor for several specific actions.	3 / 3
Completeness	Clearly answers 'what' with concrete outputs but provides no 'Use when...' or equivalent trigger guidance, which the rubric guidelines cap at 2 for a missing when-clause.	2 / 3
Trigger Term Quality	Contains relevant terms ('charts, graphs, tables', 'SVG/HTML', 'data tables') but misses common natural variations and lacks a user-voice 'when' framing; falls at the 'some relevant keywords' anchor rather than full coverage.	2 / 3
Distinctiveness Conflict Risk	The GEO/AI-citation niche ('optimized for AI engine parsing and citation', 'so AI engines can quote the data') is a distinct trigger space unlikely to collide with generic charting skills.	3 / 3
	Total	10 / 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 — 16 / 16 Passed

Validation for skill structure

No warnings or errors.

Repository: onvoyage-ai/gtm-engineer-skills
Path: create-geo-charts/SKILL.md
Commit: 3777930

Reviewed: about 18 hours ago

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