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kpi-dashboard-design

Design effective KPI dashboards with metrics selection, visualization best practices, and real-time monitoring patterns. Use when building business dashboards, selecting metrics, or designing data visualization layouts.

65

1.16x
Quality

48%

Does it follow best practices?

Impact

97%

1.16x

Average score across 3 eval scenarios

SecuritybySnyk

Passed

No known issues

Optimize this skill with Tessl

npx tessl skill review --optimize ./tests/ext_conformance/artifacts/agents-wshobson/business-analytics/skills/kpi-dashboard-design/SKILL.md
SKILL.md
Quality
Evals
Security

Quality

Content

14%

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

This skill reads as an encyclopedic reference document rather than an actionable skill for Claude. It is extremely verbose, explaining concepts Claude already knows (SMART criteria, common KPI definitions), and lacks a clear workflow for actually designing a dashboard. The content would benefit enormously from being restructured into a concise overview with supporting bundle files for the detailed KPI lists, code examples, and layout patterns.

Suggestions

Add a clear step-by-step workflow (e.g., 1. Identify audience/level → 2. Select 5-7 KPIs → 3. Choose layout pattern → 4. Implement → 5. Validate with stakeholders) with validation checkpoints.

Remove the exhaustive KPI lists by department — Claude already knows common business metrics. Instead, provide a brief framework for selecting KPIs and move detailed lists to a separate KPIS_REFERENCE.md file.

Split the SQL queries and Streamlit code into separate bundle files (e.g., examples/sql_kpis.sql, examples/streamlit_dashboard.py) and reference them from the main skill.

Remove explanations of basic concepts like SMART criteria and the definition of KPI levels — these add no value for Claude and waste token budget.

DimensionReasoningScore

Conciseness

Extremely verbose at ~400+ lines. Extensive lists of KPIs by department (Sales, Marketing, Product, Finance) are general business knowledge Claude already knows. The ASCII dashboard mockups, while visually interesting, consume enormous token budget. The full Streamlit app and SQL queries are lengthy and could be in separate reference files.

1 / 3

Actionability

The SQL queries and Streamlit code are executable and concrete, which is good. However, much of the content is descriptive/encyclopedic (lists of KPI names, SMART acronym expansion, do's/don'ts) rather than instructive. The skill reads more like a reference document than actionable guidance for building a specific dashboard.

2 / 3

Workflow Clarity

There is no clear workflow or sequenced process for actually designing and building a KPI dashboard. The content presents patterns, lists, and code snippets but never guides through a step-by-step process (e.g., gather requirements → select KPIs → design layout → implement → validate). No validation checkpoints exist.

1 / 3

Progressive Disclosure

All content is monolithically packed into a single file with no references to supporting files. The KPI lists, SQL queries, full Streamlit app code, and ASCII layouts should be split into separate reference files. The external links at the bottom are to third-party resources, not bundle files. No bundle structure exists to support this large volume of content.

1 / 3

Total

5

/

12

Passed

Description

82%

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 solid description that clearly communicates both what the skill does and when to use it, with good trigger term coverage. Its main weaknesses are slightly abstract capability descriptions (e.g., 'best practices', 'patterns') rather than concrete actions, and some potential overlap with general data visualization or analytics skills.

Suggestions

Replace abstract terms like 'best practices' and 'patterns' with more concrete actions, e.g., 'Design KPI dashboards by selecting appropriate metrics, creating chart layouts, configuring real-time data feeds, and setting alert thresholds.'

Add more distinctive trigger terms to reduce conflict risk, such as 'KPI tracking', 'dashboard layout', 'performance indicators', or 'executive reporting'.

DimensionReasoningScore

Specificity

Names the domain (KPI dashboards) and some actions (metrics selection, visualization best practices, real-time monitoring patterns), but these are somewhat abstract rather than concrete actions like 'create charts' or 'configure alert thresholds'. Terms like 'best practices' and 'patterns' are more conceptual than actionable.

2 / 3

Completeness

Clearly answers both what ('Design effective KPI dashboards with metrics selection, visualization best practices, and real-time monitoring patterns') and when ('Use when building business dashboards, selecting metrics, or designing data visualization layouts') with an explicit 'Use when' clause.

3 / 3

Trigger Term Quality

Includes good natural keywords users would say: 'KPI dashboards', 'metrics', 'data visualization', 'business dashboards', 'real-time monitoring'. These cover common variations of how users would describe dashboard-related tasks.

3 / 3

Distinctiveness Conflict Risk

While 'KPI dashboards' is fairly specific, terms like 'data visualization' and 'metrics' could overlap with general data analysis or charting skills. The scope could conflict with broader data visualization or business intelligence skills.

2 / 3

Total

10

/

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.

Validation11 / 11 Passed

Validation for skill structure

No warnings or errors.

Repository
Dicklesworthstone/pi_agent_rust
Reviewed

Table of Contents

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