database-schema
Analyze database schema and migrations for onboarding. Use when exploring schema folders, understanding table structures, analyzing migration files (golang-migrate, goose, sql-migrate, atlas), reviewing foreign key relationships, identifying indexes, understanding data models, and generating database documentation. Supports SQL migration files and Go-based migration tools.
What this skill does
## Purpose
Analyze database schemas and migration files to help developers understand the data model quickly. This skill focuses on Go-based migration tools and SQL schema files, identifying table structures, relationships, and dependencies.
## When to Use
Use this skill when you need to:
- **Understand database structure** - Get an overview of all tables and their relationships
- **Analyze migrations** - Review migration history and understand schema evolution
- **Find schema files** - Locate schema/, migrations/, or db/ directories
- **Map table relationships** - Identify foreign keys and dependencies between tables
- **Review indexes** - Understand query optimization through index analysis
- **Generate ER diagrams** - Create visual representations of the data model
- **Onboard to a database** - Learn the data model for a new project
## Key Information
### Schema Location Patterns
Common locations for schema and migration files:
```
project/
├── db/
│ ├── migrations/ # golang-migrate, goose
│ │ ├── 000001_create_users.up.sql
│ │ ├── 000001_create_users.down.sql
│ │ └── ...
│ └── schema.sql # Full schema dump
├── migrations/ # Alternative location
├── schema/ # Schema definitions
├── sql/
│ └── migrations/
└── internal/
└── db/
└── migrations/
```
### Go Migration Tools
#### 1. golang-migrate
**File Pattern:** `{version}_{name}.up.sql` / `{version}_{name}.down.sql`
```sql
-- 000001_create_users.up.sql
CREATE TABLE users (
id BIGSERIAL PRIMARY KEY,
email VARCHAR(255) NOT NULL UNIQUE,
created_at TIMESTAMP WITH TIME ZONE DEFAULT NOW()
);
-- 000001_create_users.down.sql
DROP TABLE IF EXISTS users;
```
**Commands:**
```bash
# List migrations
ls -la migrations/*.sql
# Check migration status
migrate -path ./migrations -database "postgres://..." version
```
#### 2. goose
**File Pattern:** `{version}_{name}.sql` with annotations
```sql
-- +goose Up
CREATE TABLE users (
id BIGSERIAL PRIMARY KEY,
email VARCHAR(255) NOT NULL UNIQUE
);
-- +goose Down
DROP TABLE users;
```
**Commands:**
```bash
# List migrations
goose -dir ./migrations status
# Show migration files
ls migrations/*.sql
```
#### 3. sql-migrate
**File Pattern:** `{version}_{name}.sql` with annotations
```sql
-- +migrate Up
CREATE TABLE users (...);
-- +migrate Down
DROP TABLE users;
```
#### 4. Atlas
**File Pattern:** `schema.hcl` or `*.sql`
```hcl
table "users" {
schema = schema.public
column "id" {
type = bigserial
}
column "email" {
type = varchar(255)
}
primary_key {
columns = [column.id]
}
}
```
### Analysis Checklist
When analyzing a database schema:
1. **Find Schema Files**
```bash
# Find migration directories
find . -type d -name "migrations" -o -name "schema" -o -name "db"
# Find SQL files
find . -name "*.sql" -type f
# Find HCL files (Atlas)
find . -name "*.hcl" -type f
```
2. **Identify Tables**
```bash
# Find CREATE TABLE statements
grep -r "CREATE TABLE" --include="*.sql"
# List all tables
grep -rh "CREATE TABLE" --include="*.sql" | sed 's/.*CREATE TABLE \(IF NOT EXISTS \)\?//' | cut -d'(' -f1
```
3. **Map Relationships**
```bash
# Find foreign keys
grep -r "REFERENCES\|FOREIGN KEY" --include="*.sql"
# Find indexes
grep -r "CREATE INDEX\|CREATE UNIQUE INDEX" --include="*.sql"
```
4. **Analyze Migration Order**
```bash
# List migrations in order
ls -1 migrations/*.sql | sort -V
```
### Table Relationship Patterns
#### One-to-Many
```sql
CREATE TABLE posts (
id BIGSERIAL PRIMARY KEY,
user_id BIGINT NOT NULL REFERENCES users(id),
title VARCHAR(255)
);
```
#### Many-to-Many
```sql
CREATE TABLE user_roles (
user_id BIGINT REFERENCES users(id),
role_id BIGINT REFERENCES roles(id),
PRIMARY KEY (user_id, role_id)
);
```
#### Self-Referencing
```sql
CREATE TABLE categories (
id BIGSERIAL PRIMARY KEY,
parent_id BIGINT REFERENCES categories(id),
name VARCHAR(255)
);
```
### Output Format
Generate a database schema report with:
1. **Schema Overview**
- Migration tool detected
- Total number of tables
- Schema version / latest migration
2. **Table Catalog**
- Table name
- Column definitions (name, type, constraints)
- Primary key
- Indexes
3. **Relationship Map**
- Foreign key relationships
- Dependency order (for inserts/deletes)
- Circular dependencies (if any)
4. **ER Diagram** (Mermaid format)
```mermaid
erDiagram
users ||--o{ posts : "has many"
users ||--o{ user_roles : "has many"
roles ||--o{ user_roles : "has many"
```
5. **Migration History**
- Chronological list of migrations
- What each migration changes
- Recommended reading order
### Common Column Patterns
| Pattern | Description |
|---------|-------------|
| `id BIGSERIAL PRIMARY KEY` | Auto-increment primary key |
| `created_at TIMESTAMP DEFAULT NOW()` | Creation timestamp |
| `updated_at TIMESTAMP` | Last update timestamp |
| `deleted_at TIMESTAMP` | Soft delete marker |
| `*_id BIGINT REFERENCES` | Foreign key reference |
| `status VARCHAR` / `status_enum` | State machine field |
| `metadata JSONB` | Flexible JSON storage |
Related in Backend & APIs
jfrog
IncludedInteract with the JFrog Platform via the JFrog CLI and REST/GraphQL APIs. Use this skill when the user wants to manage Artifactory repositories, upload or download artifacts, manage builds, configure permissions, manage users and groups, work with access tokens, configure JFrog CLI servers, search artifacts, manage properties, set up replication, manage JFrog Projects, run security audits or scans, look up CVE details, query exposures scan results from JFrog Advanced Security, manage release bundles and lifecycle operations, aggregate or export platform data, or perform any JFrog Platform administration task. Also use when the user mentions jf, jfrog, artifactory, xray, distribution, evidence, apptrust, onemodel, graphql, workers, mission control, curation, advanced security, exposures, or any JFrog product name.
cupynumeric-migration-readiness
IncludedPre-migration readiness assessor for porting NumPy to cuPyNumeric. Use BEFORE substantial porting work begins when the user asks whether code will scale on GPU, whether they should migrate to cuPyNumeric, which NumPy patterns transfer cleanly, what must be refactored before porting, or mentions pre-port assessment, scaling analysis, or refactor planning. Inspect the user's source code, look up NumPy usage, cross-reference the cuPyNumeric API support manifest, and distinguish distributed-scaling-friendly patterns from blockers such as unsupported APIs, scalar synchronization, host round-trips, Python/object-heavy control flow, shape/data-dependent branching, and in-place mutation hazards. Produce a verdict of READY, LIGHT REFACTOR, SIGNIFICANT REFACTOR, or NOT RECOMMENDED, with concrete refactor pointers.
alibabacloud-data-agent-skill
IncludedInvoke Alibaba Cloud Apsara Data Agent for Analytics via CLI to perform natural language-driven data analysis on enterprise databases. Data Agent for Analytics is an intelligent data analysis agent developed by Alibaba Cloud Database team for enterprise users. It automatically completes requirement analysis, data understanding, analysis insights, and report generation based on natural language descriptions. This tool supports: discovering data resources (instances/databases/tables) managed in DMS, initiating query or deep analysis sessions, real-time progress tracking, and retrieving analysis conclusions and generated reports. Use this Skill when users need to query databases, analyze data trends, generate data reports, ask questions in natural language, or mention "Data Agent", "data analysis", "database query", "SQL analysis", "data insights".
token-optimizer
IncludedReduce OpenClaw token usage and API costs through smart model routing, heartbeat optimization, budget tracking, and native 2026.2.15 features (session pruning, bootstrap size limits, cache TTL alignment). Use when token costs are high, API rate limits are being hit, or hosting multiple agents at scale. The 4 executable scripts (context_optimizer, model_router, heartbeat_optimizer, token_tracker) are local-only — no network requests, no subprocess calls, no system modifications. Reference files (PROVIDERS.md, config-patches.json) document optional multi-provider strategies that require external API keys and network access if you choose to use them. See SECURITY.md for full breakdown.
resend-cli
IncludedUse this skill when the task is specifically about operating Resend from an AI agent, terminal session, or CI job via the official resend CLI: installing/authenticating the CLI, sending/listing/updating/cancelling emails, batch sends, domains and DNS, webhooks and local listeners, inbound receiving, contacts, topics, segments, broadcasts, templates, API keys, profiles, or debugging Resend CLI/API failures. Trigger on mentions of Resend CLI, `resend`, `resend doctor`, `resend emails send`, `resend domains`, `resend webhooks listen`, `resend emails receiving`, or agent-friendly terminal automation.
alibabacloud-odps-maxframe-coding
IncludedUse this skill for MaxFrame SDK development and documentation navigation on Alibaba Cloud MaxCompute (ODPS). Helps answer MaxFrame API, concept, official example, and supported pandas API questions; create data processing programs; read/write MaxCompute tables; debug jobs (remote or local); and build custom DPE runtime images. Trigger when users mention MaxFrame, MaxCompute with MaxFrame, ODPS table processing, DPE runtime, MaxFrame docs/examples, DataFrame/Tensor operations, or GPU runtime setup. Works for both English and Chinese queries about Alibaba Cloud data processing with MaxFrame.