business-intelligence-pro

business-intelligence-pro is a skill for Claude Code, Codex from vignesh2027/Claude-Agentic-Skills2.0-version. It costs 68 tokens per session (732 once invoked), scanned A, original, MIT.

An AI business-intelligence assistant for defining key performance indicators (KPIs), designing dashboards, and improving SQL queries. Business intelligence turns company data into metrics and reports used for decisions.

In plain words
What is it for?
Use it to define a north-star metric and metric tree, design Looker or LookML models, write SQL with window functions and common table expressions, plan alerts, and explain data to executives.
Why use it?
It helps connect high-level business goals to measurable drivers and safeguards, rather than tracking disconnected numbers. It also provides patterns for organising complex SQL and dashboard models.

Skill for Claude CodeCodex

Written for no agent in particular: nothing here depends on one.

Good fit Use it to define a north-star metric and metric tree, design Looker or LookML models, write SQL with window functions and common table expressions, plan alerts, and explain data to executives.

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Install with agentmods
npx agentmods add skills/vignesh2027/claude-agentic-skills2.0-version/business-intelligence-pro
Install

Getting it into your agent

One page per mod, every tool's command on it. A separate URL per tool would split the same page into five that compete with each other.

Any agent
npx skills add vignesh2027/Claude-Agentic-Skills2.0-version --skill business-intelligence-pro
Clone the repo
git clone --depth 1 https://github.com/vignesh2027/Claude-Agentic-Skills2.0-version

Made for: Claude Code, Codex.

Wrote this? Show the measurements

A badge with what this costs and how it scanned, read live from this page, so it follows the numbers instead of freezing them. Markdown for a README, HTML for a documentation site or a project page.

agentmods badge for business-intelligence-pro

README.md
[![agentmods](https://agentmods.dev/badge/skills/vignesh2027/claude-agentic-skills2.0-version/business-intelligence-pro/github.svg)](https://agentmods.dev/skills/vignesh2027/claude-agentic-skills2.0-version/business-intelligence-pro)
Your own site
<a href="https://agentmods.dev/skills/vignesh2027/claude-agentic-skills2.0-version/business-intelligence-pro"><img src="https://agentmods.dev/badge/skills/vignesh2027/claude-agentic-skills2.0-version/business-intelligence-pro/github.svg" alt="Measured on agentmods" height="20"></a>

Or the 80×15 button, for a site that already has a row of RSS and ATOM ones. Only the verdict fits; the numbers stay here.

agentmods 80×15 button for business-intelligence-pro

Your own site · 80×15
<a href="https://agentmods.dev/skills/vignesh2027/claude-agentic-skills2.0-version/business-intelligence-pro"><img src="https://agentmods.dev/badge/skills/vignesh2027/claude-agentic-skills2.0-version/business-intelligence-pro.svg" alt="Reviewed on agentmods" width="80" height="20"></a>
Per session 68 Skills are progressive disclosure: only the name and description are preloaded; the body loads when the skill is used.
When invoked 732 The whole file, excluding the scripts and references it only reads on demand.
Security scan A 0 findings. A grade says what 26 rules found in the file — not that it is safe.
Origin original No closer match found in the catalogue.
Token cost

What it costs to keep this loaded

Counted locally with the o200k_base tokenizer, which is exact for GPT models; Claude uses its own tokenizer and its counts differ. Treat this as one consistent yardstick across the catalogue rather than a bill. Prices are per million input tokens.

ModelPer sessionOnce invoked
Fable 5.1 $0.00068 $0.00732
Opus 5 $0.00034 $0.00366
Sonnet 5 $0.00014 $0.00146
Haiku 4.5 $0.00007 $0.00073

Measured 11d ago against content hash 53acf7eccace, method: parsed. Prices are Anthropic first-party input rates as of 2026-09-11, from the pricing page.

Security

Grade A, and why

business-intelligence-pro scanned grade A with 0 findings against 26 rules in 11 categories — prompt injection, anti-refusal, data exfiltration, privilege escalation, supply chain, agent snooping, system-prompt leakage, SSRF and excessive agency — measured 11d ago.

A static scan of the body, not an audit. Every finding is printed with the line that produced it so you can judge whether it matters here. A mod is markdown that instructs an agent; that is exactly why what it instructs is worth reading.

Nothing flagged

None of the 26 patterns this scan looks for appear in this file: no shell pipes, no recursive deletes, no credential paths, no hidden text, no instruction-override or anti-refusal phrasing, no agent-config snooping. That is not a guarantee, it is the absence of the things that are checkable.

business-intelligence-pro/SKILL.md · 83 lines

How it starts

The opening of the file, as written. The whole thing — 83 lines — stays where its author put it; the contents beside it link to each section on GitHub.

BusinessIntelligence-Pro Agent

You are BusinessIntelligence-Pro — a BI specialist designing metric frameworks, SQL-optimized data models, and executive-ready dashboards.

North Star Metric Framework

  1. North Star: single metric that captures core product value
  • Good example: 'Weekly Active Users who complete a core action'
  • Bad example: 'Revenue' (lagging indicator, doesn't capture user value)
  1. Input metrics (3-5 leading indicators that drive North Star):
  • Acquisition: new user signups
  • Activation: users reaching aha moment
  • Engagement: core action frequency
  1. Guardrail metrics: must not degrade (e.g., support ticket volume, latency)
  2. Lagging metrics: revenue, retention — validate North Star theory

KPI Hierarchy

North Star Metric
├── Input Metric A (driver)
│   ├── Sub-metric A1
│   └── Sub-metric A2
├── Input Metric B (driver)
└── Input Metric C (driver)

SQL Expert Patterns

Window Functions

-- Running total
SUM(revenue) OVER (PARTITION BY user_id ORDER BY date) AS cumulative_revenue

-- Cohort retention
COUNT(DISTINCT user_id) OVER (PARTITION BY cohort_month) AS cohort_size

-- Moving average
AVG(daily_revenue) OVER (ORDER BY date ROWS BETWEEN 6 PRECEDING AND CURRENT ROW) AS rolling_7d_avg

-- Rank within group
ROW_NUMBER() OVER (PARTITION BY customer_id ORDER BY order_date DESC) AS recency_rank

Cohort Analysis CTE Pattern

WITH first_purchase AS (
 SELECT user_id, DATE_TRUNC('month', MIN(created_at)) AS cohort_month FROM orders GROUP BY 1
),
cohort_data AS (
 SELECT f.cohort_month, DATE_TRUNC('month', o.created_at) AS order_month,
        COUNT(DISTINCT o.user_id) AS active_users
 FROM orders o JOIN first_purchase f ON o.user_id = f.user_id
 GROUP BY 1, 2
)
SELECT cohort_month, order_month,
       DATEDIFF('month', cohort_month, order_month) AS months_since_acquisition,
       active_users
FROM cohort_data ORDER BY 1, 3;

Dashboard Design Principles

  1. Answer one question per chart — no chart should require explanation
  2. Lead with the most important number (large KPI card at top)
  3. Provide context: comparison to prior period and target
  4. Drill-down hierarchy: executive → operational → diagnostic
  5. Traffic light coloring: green (on target), yellow (within 10%), red (>10% off)

Read the full file on GitHub · 83 lines

Changes

What this file has done since we first saw it

Hashed on every crawl. A supply-chain change to an agent config is a question of when, not whether, so the history is kept rather than the latest state alone.

  1. 11d ago First seen · 83 lines · 68 tokens per session scan A 53acf7eccace

Subscribe to this mod's changes

business-intelligence-pro is a skill published in the GitHub repository vignesh2027/Claude-Agentic-Skills2.0-version (6 stars, last pushed 13d ago), licensed MIT. It adds 68 tokens to every session and 732 once invoked, about $0.0003 per session on Opus 5. A static security scan graded it A with 0 findings. No closer match exists in the catalogue, so it is treated as the original; first seen 2026-08-31.