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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.

25

Quality

16%

Does it follow best practices?

Impact

No eval scenarios have been run

SecuritybySnyk

Passed

No known issues

Optimize this skill with Tessl

npx tessl skill review --optimize ./skills/business-analyst/SKILL.md
SKILL.md
Quality
Evals
Security

Quality

Content

7%

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

This skill reads like a job description or persona prompt rather than an actionable skill file. It exhaustively lists topics and capabilities Claude already understands without providing any concrete code, templates, frameworks, or specific instructions. The content is extremely verbose with no executable guidance, making it essentially useless as a skill that should teach Claude how to perform specific tasks.

Suggestions

Replace the extensive capability listings with 3-5 concrete, executable examples (e.g., a Python snippet for cohort analysis, a SQL query template for churn prediction, a KPI dashboard specification template).

Add specific workflow sequences with validation checkpoints for key tasks like 'building a predictive churn model' or 'creating a KPI framework', including concrete tool commands and verification steps.

Remove the 'Behavioral Traits', 'Knowledge Base', and most of the 'Capabilities' bullet lists — Claude already knows these concepts. Focus only on project-specific conventions, templates, or non-obvious patterns.

Create actual bundle files (e.g., templates/kpi-framework.md, templates/dashboard-spec.md, examples/cohort-analysis.py) with concrete, reusable artifacts and reference them clearly from the main skill.

DimensionReasoningScore

Conciseness

Extremely verbose and padded with information Claude already knows. The massive 'Capabilities' section is essentially a resume listing topics like 'Advanced dashboard creation with Tableau, Power BI, Looker' and 'Machine learning for predictive analytics' — none of which teach Claude anything new or actionable. The 'Behavioral Traits' and 'Knowledge Base' sections describe general qualities rather than providing useful instructions. The entire skill could be reduced to under 20 lines without losing actionable content.

1 / 3

Actionability

The skill contains zero concrete code, commands, templates, frameworks, or executable examples. It is entirely descriptive — listing capabilities and topics rather than providing specific steps, formulas, SQL queries, Python snippets, dashboard configurations, or any copy-paste-ready guidance. The 'Response Approach' section is a generic 8-step process that could apply to virtually any analytical task.

1 / 3

Workflow Clarity

The 'Response Approach' provides a vague 8-step sequence ('Define business objectives', 'Assess data availability', etc.) with no validation checkpoints, no error handling, no concrete tools or commands at each step, and no feedback loops. For a skill covering complex analytical workflows, predictive modeling, and dashboard creation, the absence of any specific workflow with verification steps is a significant gap.

1 / 3

Progressive Disclosure

There is one reference to 'resources/implementation-playbook.md' for detailed examples, which suggests some attempt at progressive disclosure. However, no bundle files are provided to support this reference, and the massive inline content (capabilities lists, behavioral traits, knowledge base) should have been split into separate reference files rather than included in the main skill body.

2 / 3

Total

5

/

12

Passed

Description

25%

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 more like marketing copy than a functional skill description, relying heavily on buzzwords ('AI-powered,' 'data-driven,' 'master modern') without specifying concrete actions. It lacks a 'Use when...' clause entirely, making it difficult for Claude to know when to select this skill. The extremely broad scope covering analytics, dashboards, KPIs, and predictive models creates high conflict risk with other skills.

Suggestions

Add an explicit 'Use when...' clause with natural trigger terms like 'Use when the user asks for business analysis, KPI tracking, revenue forecasting, or building executive dashboards.'

Replace buzzword-heavy phrases ('AI-powered analytics,' 'data-driven insights') with concrete actions like 'Builds KPI dashboards from spreadsheet data, generates revenue forecasts, creates SWOT analyses.'

Narrow the scope to reduce conflict risk — clarify whether this is for financial analysis, operational metrics, strategic planning, or a specific subset, rather than claiming all of business analysis.

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 the skill actually does.

2 / 3

Completeness

Describes what it does (albeit vaguely), but completely lacks any 'Use when...' clause or explicit trigger guidance. Per the rubric, a missing 'Use when' clause caps completeness at 2, and the 'what' portion is also weak due to buzzword-heavy language, warranting a score of 1.

1 / 3

Trigger Term Quality

Includes some relevant keywords like 'KPI,' 'dashboards,' 'predictive models,' and 'business analysis,' but many terms are marketing fluff ('AI-powered,' 'data-driven insights,' 'master modern') rather than natural phrases a user would say. Missing common variations like 'business report,' 'market analysis,' 'ROI,' 'financial analysis.'

2 / 3

Distinctiveness Conflict Risk

Extremely broad scope covering analytics, dashboards, KPIs, predictive models, and strategic recommendations — this could easily conflict with data science skills, dashboard/visualization skills, reporting skills, or strategy 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
sickn33/antigravity-awesome-skills
Reviewed

Table of Contents

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