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business-analyst

Master modern business analysis with AI-powered analytics, real-time dashboards, and data-driven insights. Build comprehensive KPI frameworks, predictive models, and strategic recommendations.

43

1.03x
Quality

16%

Does it follow best practices?

Impact

87%

1.03x

Average score across 3 eval scenarios

SecuritybySnyk

Passed

No findings from the security scan

Fix and improve this skill with Tessl

tessl review fix ./plugins/AI-Agents-Safe-Coding-Skills-claude/skills/business-analyst/SKILL.md

The canonical home for this skill is business-analyst in sickn33/agentic-awesome-skills

SKILL.md
Quality
Evals
Security

Quality

Content

7%Scale 1-3

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 a persona description or job posting rather than an actionable skill file. It extensively lists capabilities and traits that Claude already possesses, consuming significant token budget without providing any concrete guidance, executable code, templates, or specific methodologies. The content would need a fundamental restructuring to be useful—replacing capability lists with specific, actionable instructions and worked examples.

Suggestions

Replace the extensive capability lists with 2-3 concrete, executable examples (e.g., a Python snippet for cohort analysis, a SQL template for churn prediction, a specific KPI dashboard structure).

Remove the 'Capabilities', 'Behavioral Traits', and 'Knowledge Base' sections entirely—these describe what Claude already knows and waste tokens.

Transform the 'Response Approach' into a concrete workflow with specific validation checkpoints, such as 'Verify data completeness: check for >5% null values in key columns before proceeding.'

Move detailed methodologies (A/B testing frameworks, financial models, etc.) into separate reference files and link to them from a concise overview in the main skill file.

DimensionReasoningScore

Conciseness

Extremely verbose with extensive lists of capabilities, behavioral traits, and knowledge bases that Claude already possesses. The content reads like a job description or persona prompt rather than a skill file. Most of the listed items (e.g., 'Advanced statistical analysis and hypothesis testing', 'Color theory and design principles') are things Claude already knows and don't need enumeration.

1 / 3

Actionability

No concrete code, commands, specific templates, or executable examples anywhere. The entire content is abstract descriptions of capabilities and vague process steps like 'Execute comprehensive analysis with statistical rigor.' The 'Example Interactions' section lists prompts but provides no actual outputs or worked examples.

1 / 3

Workflow Clarity

The 'Response Approach' section lists 8 high-level steps but they are generic and lack any validation checkpoints, specific tools/commands, or error recovery guidance. Steps like 'Assess data availability' and 'Create compelling visualizations' provide no actionable sequence for Claude to follow.

1 / 3

Progressive Disclosure

There is one reference to an external file ('resources/implementation-playbook.md') which is good, but the main content is a monolithic wall of bullet-pointed lists that should either be drastically condensed or split into separate reference files. The structure exists (sections with headers) but the content within each section is bloated.

2 / 3

Total

5

/

12

Passed

Description

25%Scale 1-3

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 reads like marketing copy rather than a functional skill description. It relies heavily on buzzwords ('AI-powered,' 'data-driven,' 'real-time') without specifying concrete actions, lacks any 'Use when...' trigger guidance, and covers such a broad scope that it would conflict with numerous other skills in a multi-skill environment.

Suggestions

Add an explicit 'Use when...' clause with specific trigger scenarios, e.g., 'Use when the user asks for business KPI tracking, revenue analysis, or strategic business recommendations.'

Replace buzzwords with concrete actions, e.g., 'Builds KPI dashboards from spreadsheet data, generates quarterly business reports, creates revenue forecasts' instead of 'AI-powered analytics and data-driven insights.'

Narrow the scope to a distinct niche to reduce conflict risk — decide whether this is about dashboard creation, KPI tracking, predictive modeling, or strategic analysis, rather than claiming all of them.

DimensionReasoningScore

Specificity

Names the domain (business analysis) and lists some actions like 'Build comprehensive KPI frameworks, predictive models, and strategic recommendations,' but many terms are buzzword-heavy rather than concrete ('AI-powered analytics,' 'data-driven insights,' 'real-time dashboards') and lack specificity about what is actually done.

2 / 3

Completeness

Describes what the skill does (albeit vaguely) but completely lacks any 'Use when...' clause or explicit trigger guidance for when Claude should select this skill. Per the rubric, a missing 'Use when...' clause caps completeness at 2, and the 'what' is also weak due to buzzword-heavy language, so this scores a 1.

1 / 3

Trigger Term Quality

Includes some relevant keywords like 'KPI,' 'dashboards,' 'predictive models,' and 'business analysis,' but these are broad and overlap with many domains. Missing natural user phrases like 'analyze sales data,' 'create a business report,' or 'forecast revenue.'

2 / 3

Distinctiveness Conflict Risk

Extremely broad scope covering analytics, dashboards, KPIs, predictive models, and strategic recommendations — this would easily conflict with data science skills, dashboard-building skills, reporting skills, and general analytics skills. No clear niche is carved out.

1 / 3

Total

6

/

12

Passed

Validation

90%

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

Validation10 / 11 Passed

Validation for skill structure

CriteriaDescriptionResult

frontmatter_unknown_keys

Unknown frontmatter key(s) found; consider removing or moving to metadata

Warning

Total

10

/

11

Passed

Repository
administrakt0r/AI-Agents-Safe-Coding-Skills
Reviewed

Table of Contents

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