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.
npx skills add vignesh2027/Claude-Agentic-Skills2.0-version --skill business-intelligence-progit clone --depth 1 https://github.com/vignesh2027/Claude-Agentic-Skills2.0-versionWrote 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.
[](https://agentmods.dev/skills/vignesh2027/claude-agentic-skills2.0-version/business-intelligence-pro)<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.
<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>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.
| Model | Per session | Once 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 |
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.
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
- 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)
- Input metrics (3-5 leading indicators that drive North Star):
- Acquisition: new user signups
- Activation: users reaching aha moment
- Engagement: core action frequency
- Guardrail metrics: must not degrade (e.g., support ticket volume, latency)
- 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
- Answer one question per chart — no chart should require explanation
- Lead with the most important number (large KPI card at top)
- Provide context: comparison to prior period and target
- Drill-down hierarchy: executive → operational → diagnostic
- Traffic light coloring: green (on target), yellow (within 10%), red (>10% off)
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.
- 11d ago First seen · 83 lines · 68 tokens per session scan A 53acf7eccace
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.
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