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visualize-data

Design, create, revise, or QA quantitative charts and figures for reports, dashboards, notebooks, slides, files, or inline analytical answers.

62

Quality

72%

Does it follow best practices?

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SecuritybySnyk

Passed

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Fix and improve this skill with Tessl

tessl review fix ./packages/opencode/src/skill/builtin/.bundle/data-analytics/workflows/visualize-data/SKILL.md
SKILL.md
Quality
Evals
Security

Quality

Content

85%

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

The content is concise and well-structured with a clear workflow and explicit QA validation checkpoints; its main gap is the absence of any executable code or copy-paste examples, which limits actionability despite otherwise concrete guidance.

Suggestions

Add one minimal executable example (e.g., a short Matplotlib/SVG snippet) to lift actionability toward a copy-paste-ready score 3.

Consider linking a short reference of palette or encoding recipes if the skill grows beyond the current single-page scope.

DimensionReasoningScore

Conciseness

The body is lean and efficient with no concept-explaining fluff; it assumes Claude's competence and every line (workflow, visual quality, QA) earns its place, matching the 'lean and efficient; every token earns its place' anchor.

3 / 3

Actionability

The chart-family decision mapping and the explicit encoding checklist ('Define explicit encodings, sorting, aggregation...') are concrete guidance, but there are no executable code snippets or copy-paste-ready examples, fitting the 'some concrete guidance but incomplete' anchor rather than fully executable score 3.

2 / 3

Workflow Clarity

A clear six-step numbered sequence is paired with a dedicated QA section containing explicit validation checkpoints ('Recompute plotted values', 'Confirm the visual answers the stated question', 'Confirm the exported file opens'), matching the 'clear sequence with explicit validation steps' anchor.

3 / 3

Progressive Disclosure

The skill is under 50 lines with no external references and is organized into well-separated Workflow, Visual quality, and QA sections, so per the simple-skills scoring note progressive disclosure scores 3 on well-organized sections alone.

3 / 3

Total

11

/

12

Passed

Description

60%

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 enumerates both actions and destinations, but it lacks an explicit 'Use when...' trigger clause and omits common natural terms like 'plot' or 'graph', which cap trigger-term quality and completeness at 2.

Suggestions

Add an explicit trigger clause such as 'Use when creating or revising charts, plots, graphs, or figures for reports, dashboards, notebooks, or slides.'

Include common user-facing variations like 'plot', 'graph', and 'data viz' alongside 'charts' and 'figures' to improve trigger-term coverage.

DimensionReasoningScore

Specificity

Enumerates multiple concrete actions ('Design, create, revise, or QA') and several destinations (reports, dashboards, notebooks, slides, files, inline analytical answers), matching the 'lists multiple specific concrete actions' anchor rather than the single-domain score 2.

3 / 3

Completeness

Clearly answers 'what' the skill does but has no 'Use when...' clause or equivalent explicit trigger guidance, so per the judging guideline completeness is capped at 2 rather than 3.

2 / 3

Trigger Term Quality

Includes natural user-facing terms like 'charts', 'figures', 'reports', 'dashboards', and 'notebooks', but omits common variations users would say such as 'plot', 'graph', or 'data viz', matching the 'some relevant keywords but missing common variations' anchor.

2 / 3

Distinctiveness Conflict Risk

'Quantitative charts and figures' is a recognizable niche, but the broad destinations and lack of distinct trigger phrasing mean it could overlap with general data-analysis skills, fitting the 'somewhat specific but could still overlap' anchor.

2 / 3

Total

9

/

12

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
XiaomiMiMo/MiMo-Code
Reviewed

Table of Contents

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