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Route broad Data Analytics requests to the appropriate quantitative analysis, visualization, dashboard, report, notebook, KPI, market-sizing, validation, or semantic-layer workflow.

68

Quality

83%

Does it follow best practices?

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SKILL.md
Quality
Evals
Security

Quality

Content

96%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 concise, highly actionable router body with a clear validated workflow sequence and well-signaled one-level-deep sibling-skill references. The only notable gap is a referenced demo asset (assets/demo-product-growth.csv) that does not exist in the bundle.

Suggestions

Either add the referenced assets/demo-product-growth.csv to the bundle or remove/soften the reference to it so no in-body path dangles.

Consider stating what to do when none of the 13 routing bullets clearly matches (e.g., fall back to the closest workflow or ask for clarification) to close a small routing-edge gap.

DimensionReasoningScore

Conciseness

The body is lean and assumes Claude's competence: it never explains what a dashboard, KPI, or notebook is, and every line provides routing, ordering, source-access, or output-format guidance that earns its place.

5 / 5

Actionability

It gives a concrete symptom-to-path routing table ('Metric changed... read ../metric-diagnostics/SKILL.md'), a numbered execution order, explicit source-request artifacts, and a per-format output policy — copy-ready and directly executable.

5 / 5

Workflow Clarity

A clear five-step sequence embeds explicit validation checkpoints (step 2 'Validate source quality and metric definitions', step 4 'Validate conclusions') plus a feedback loop ('If available sources conflict... surface the conflict and use the data-quality workflow').

5 / 5

Progressive Disclosure

Structure is good with clearly signaled one-level-deep references (13 sibling SKILL.md files via 'read ../X/SKILL.md') and well-organized sections, but the body references assets/demo-product-growth.csv which is not present in the bundle — a minor organization gap rather than a structural one.

4 / 5

Total

19

/

20

Passed

Description

70%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.

A well-targeted router description with strong distinctiveness and good concrete coverage of downstream workflow types, weakened mainly by the absence of an explicit 'Use when...' trigger clause and some missing common synonyms. Adding an explicit activation phrase would likely lift completeness and trigger-term quality.

Suggestions

Append an explicit 'Use when...' clause naming concrete activation triggers (e.g., 'Use when the user asks for metrics, a KPI, a dashboard, a data report, or an evidence-backed product/business decision').

Add common user synonyms such as 'metrics', 'analytics', and 'data' alongside the listed workflow types to improve natural-trigger coverage.

Briefly state the negative boundary in the description (e.g., 'Do not use for ordinary prose drafting or file-format conversion') to further sharpen distinctiveness.

DimensionReasoningScore

Specificity

The description names the domain (routing Data Analytics requests) and lists many concrete downstream targets ('quantitative analysis, visualization, dashboard, report, notebook, KPI, market-sizing, validation, or semantic-layer workflow'), giving broad coverage with only the single dispatch verb 'Route' as the action.

4 / 5

Completeness

It gives a clear 'what' (route to the listed workflows) but lacks an explicit 'Use when...' trigger clause; the 'when' is only weakly implied by 'Route broad Data Analytics requests', so per the rubric guideline a missing explicit trigger caps completeness at 3.

3 / 5

Trigger Term Quality

It includes natural terms users would say ('Data Analytics', 'visualization', 'dashboard', 'report', 'notebook', 'KPI', 'market-sizing') but misses common synonyms and shorthand a user might actually invoke ('metrics', 'analytics', 'data').

4 / 5

Distinctiveness Conflict Risk

It carves a clear niche (dispatching structured, evidence-backed data-analytics work to specialized workflows) with distinct triggers and minimal risk of firing for unrelated skills.

5 / 5

Total

16

/

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

referenced_paths_exist

Referenced path issues: 1 missing

Warning

Total

15

/

16

Passed

Repository
XiaomiMiMo/MiMo-Code
Reviewed

Table of Contents

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