postgresql-bi-agent

Name: postgresql-bi-agent
Author: digoal

38stars12forks

How to install postgresql-bi-agent?

digoal/postgres_skill/postgresql-bi-agent

$npx -y skills add digoal/postgres_skill --skill postgresql-bi-agent

Installs into the current project.

Summary

Business intelligence analysis agent for PostgreSQL that discovers database metadata, generates SQL queries for revenue/customer/product metrics, and produces comprehensive analytical reports

Files · 1

View on GitHub

SKILL.md

1	# PostgreSQL Business Intelligence Agent
2
3	This skill guides the agent in conducting comprehensive business intelligence analysis on a PostgreSQL database. It automatically discovers database metadata, samples data to understand business context, generates business-relevant SQL queries, executes them, and produces deep analytical reports for business operations insights.
4
5	## Purpose
6
7	The primary goal of this skill is to transform raw database data into actionable business intelligence. It serves as an automated data analyst that:
8
9	- Discovers database structure and metadata automatically
10	- Understands business context through data sampling
11	- Generates relevant SQL queries for business metrics
12	- Executes queries efficiently and safely
13	- Analyzes results to provide strategic insights
14	- Reports findings with actionable recommendations
15
16	## Business Intelligence Framework
17
18	The agent uses a multi-dimensional framework covering:
19
20	### 1. Business Scale Metrics
21	- Transaction volumes and values
22	- Customer base and distribution
23	- Product/service inventory and categorization
24
25	### 2. Growth Trends
26	- Year-over-year and month-over-month comparisons
27	- Daily/Monthly active user trends
28	- Revenue and order trends
29
30	### 3. User Behavior Analysis
31	- User engagement and activity levels
32	- Retention rates and cohort analysis
33	- Conversion funnel metrics
34
35	### 4. Financial Insights
36	- Revenue trends and patterns
37	- Average order value (AOV)
38	- Payment success rates and refund metrics
39
40	### 5. Inventory & Product Analysis
41	- Inventory turnover rates
42	- Product performance rankings
43	- Stock-out and overstock indicators
44
45	### 6. Operational Efficiency
46	- Order processing times
47	- Customer satisfaction indicators
48	- System performance metrics
49
50	## Workflow
51
52	When activated, this skill executes a comprehensive analysis pipeline:
53
54	1. Metadata Discovery → Scan database structure, tables, columns, relationships
55	2. Data Sampling → Analyze data patterns, value distributions, business context
56	3. SQL Generation → Generate domain-specific business intelligence queries
57	4. Query Execution → Run all queries with proper error handling
58	5. Deep Analysis → Correlate results, identify patterns, calculate insights
59	6. Report Generation → Produce comprehensive business report
60
61	## Available Skills
62
63	Each skill represents a callable analysis module that returns structured JSON output.
64
65	---
66
67	## 1. Metadata Discovery
68
69	### Skill: `discover_database_metadata`
70
71	- Description: Scans and collects comprehensive database metadata including schemas, tables, columns, data types, constraints, indexes, and relationships.
72	- Usage: `python3 business_intelligence_agent.py --skill discover_database_metadata`
73	- Expected Output:
74	```json
75	{
76	"skill": "discover_database_metadata",
77	"status": "success",
78	"data": {
79	"database_name": "ecommerce_db",
80	"schemas": ["public", "analytics", "audit"],
81	"total_tables": 45,
82	"total_columns": 380,
83	"tables": [
84	{
85	"schema_name": "public",
86	"table_name": "orders",
87	"row_count": 1500000,
88	"columns": [
89	{"name": "order_id", "type": "bigint", "is_pk": true},
90	{"name": "user_id", "type": "bigint", "is_fk": true},
91	{"name": "order_amount", "type": "decimal(12,2)", "is_nullable": false},
92	{"name": "created_at", "type": "timestamp", "is_nullable": false}
93	],
94	"indexes": ["idx_orders_user_id", "idx_orders_created_at"]
95	}
96	],
97	"relationships": [
98	{"from": "orders.user_id", "to": "users.user_id", "type": "FK"}
99	]
100	}
101	}
102	```
103
104	### Skill: `identify_business_tables`
105
106	- Description: Identifies tables likely related to core business operations based on naming conventions, column patterns, and data characteristics.
107	- Usage: `python3 business_intelligence_agent.py --skill identify_business_tables`
108	- Expected Output:
109	```json
110	{
111	"skill": "identify_business_tables",
112	"status": "success",
113	"data": {
114	"core_tables": [
115	{"name": "orders", "category": "transactions", "confidence": 0.95},
116	{"name": "users", "category": "customers", "confidence": 0.92},
117	{"name": "products", "category": "inventory", "confidence": 0.88}
118	],
119	"transaction_tables": ["orders", "payments", "refunds"],
120	"customer_tables": ["users", "customers", "accounts"],
121	"product_tables": ["products", "inventory", "categories"]
122	}
123	}
124	```
125
126	### Skill: `analyze_table_relationships`
127
128	- Description: Maps foreign key relationships and infers

People who liked this also viewed

6 picks

Type

postgresql-bi-agent

38stars12forks

View on GitHub

How to install postgresql-bi-agent?

digoal/postgres_skill/postgresql-bi-agent

$npx -y skills add digoal/postgres_skill --skill postgresql-bi-agent

Installs into the current project.

Summary

Business intelligence analysis agent for PostgreSQL that discovers database metadata, generates SQL queries for revenue/customer/product metrics, and produces comprehensive analytical reports

Files · 1

View on GitHub

SKILL.md

1	# PostgreSQL Business Intelligence Agent
2
3	This skill guides the agent in conducting comprehensive business intelligence analysis on a PostgreSQL database. It automatically discovers database metadata, samples data to understand business context, generates business-relevant SQL queries, executes them, and produces deep analytical reports for business operations insights.
4
5	## Purpose
6
7	The primary goal of this skill is to transform raw database data into actionable business intelligence. It serves as an automated data analyst that:
8
9	- Discovers database structure and metadata automatically
10	- Understands business context through data sampling
11	- Generates relevant SQL queries for business metrics
12	- Executes queries efficiently and safely
13	- Analyzes results to provide strategic insights
14	- Reports findings with actionable recommendations
15
16	## Business Intelligence Framework
17
18	The agent uses a multi-dimensional framework covering:
19
20	### 1. Business Scale Metrics
21	- Transaction volumes and values
22	- Customer base and distribution
23	- Product/service inventory and categorization
24
25	### 2. Growth Trends
26	- Year-over-year and month-over-month comparisons
27	- Daily/Monthly active user trends
28	- Revenue and order trends
29
30	### 3. User Behavior Analysis
31	- User engagement and activity levels
32	- Retention rates and cohort analysis
33	- Conversion funnel metrics
34
35	### 4. Financial Insights
36	- Revenue trends and patterns
37	- Average order value (AOV)
38	- Payment success rates and refund metrics
39
40	### 5. Inventory & Product Analysis
41	- Inventory turnover rates
42	- Product performance rankings
43	- Stock-out and overstock indicators
44
45	### 6. Operational Efficiency
46	- Order processing times
47	- Customer satisfaction indicators
48	- System performance metrics
49
50	## Workflow
51
52	When activated, this skill executes a comprehensive analysis pipeline:
53
54	1. Metadata Discovery → Scan database structure, tables, columns, relationships
55	2. Data Sampling → Analyze data patterns, value distributions, business context
56	3. SQL Generation → Generate domain-specific business intelligence queries
57	4. Query Execution → Run all queries with proper error handling
58	5. Deep Analysis → Correlate results, identify patterns, calculate insights
59	6. Report Generation → Produce comprehensive business report
60
61	## Available Skills
62
63	Each skill represents a callable analysis module that returns structured JSON output.
64
65	---
66
67	## 1. Metadata Discovery
68
69	### Skill: `discover_database_metadata`
70
71	- Description: Scans and collects comprehensive database metadata including schemas, tables, columns, data types, constraints, indexes, and relationships.
72	- Usage: `python3 business_intelligence_agent.py --skill discover_database_metadata`
73	- Expected Output:
74	```json
75	{
76	"skill": "discover_database_metadata",
77	"status": "success",
78	"data": {
79	"database_name": "ecommerce_db",
80	"schemas": ["public", "analytics", "audit"],
81	"total_tables": 45,
82	"total_columns": 380,
83	"tables": [
84	{
85	"schema_name": "public",
86	"table_name": "orders",
87	"row_count": 1500000,
88	"columns": [
89	{"name": "order_id", "type": "bigint", "is_pk": true},
90	{"name": "user_id", "type": "bigint", "is_fk": true},
91	{"name": "order_amount", "type": "decimal(12,2)", "is_nullable": false},
92	{"name": "created_at", "type": "timestamp", "is_nullable": false}
93	],
94	"indexes": ["idx_orders_user_id", "idx_orders_created_at"]
95	}
96	],
97	"relationships": [
98	{"from": "orders.user_id", "to": "users.user_id", "type": "FK"}
99	]
100	}
101	}
102	```
103
104	### Skill: `identify_business_tables`
105
106	- Description: Identifies tables likely related to core business operations based on naming conventions, column patterns, and data characteristics.
107	- Usage: `python3 business_intelligence_agent.py --skill identify_business_tables`
108	- Expected Output:
109	```json
110	{
111	"skill": "identify_business_tables",
112	"status": "success",
113	"data": {
114	"core_tables": [
115	{"name": "orders", "category": "transactions", "confidence": 0.95},
116	{"name": "users", "category": "customers", "confidence": 0.92},
117	{"name": "products", "category": "inventory", "confidence": 0.88}
118	],
119	"transaction_tables": ["orders", "payments", "refunds"],
120	"customer_tables": ["users", "customers", "accounts"],
121	"product_tables": ["products", "inventory", "categories"]
122	}
123	}
124	```
125
126	### Skill: `analyze_table_relationships`
127
128	- Description: Maps foreign key relationships and infers

People who liked this also viewed

6 picks

Type