Operate seekdb via CLI commands and look up seekdb documentation. Use when: executing SQL, exploring table schemas, managing vector collections, registering AI models, answering user questions about seekdb, or looking up seekdb concepts and syntax. Triggers on: SQL queries, database operations, seekdb features, vector/hybrid/semantic search questions, or any user question about seekdb. Supports both embedded mode and remote server mode.
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---
name: seekdb
description: "Operate seekdb via CLI commands and look up seekdb documentation. Use when: executing SQL, exploring table schemas, managing vector collections, registering AI models, answering user questions about seekdb, or looking up seekdb concepts and syntax. Triggers on: SQL queries, database operations, seekdb features, vector/hybrid/semantic search questions, or any user question about seekdb. Supports both embedded mode and remote server mode."
license: MIT
---
# seekdb — AI-Agent Database CLI with Documentation
This skill lets AI Agents **operate seekdb** via `seekdb-cli` commands and **look up seekdb documentation** when needed.
> **Quick orientation**: Start with `seekdb ai-guide` to get a full JSON self-description of the CLI. Then run commands directly — no setup needed.
---
# Part 1: seekdb-cli Operations
`seekdb-cli` is purpose-built for AI Agents. All output is structured JSON, all operations are stateless, and built-in safety guardrails prevent accidental data loss.
## seekdb Deployment
seekdb supports two modes. Use this section to guide users to the right deployment path based on their OS and scenario.
### Embedded Mode
seekdb runs as a library inside the application — **no server process required**. Install via `pyseekdb`:
```bash
pip install -U pyseekdb
```
**Supported platforms**: Linux (glibc ≥ 2.28), macOS 15+ · **Architectures**: x86_64, aarch64
> Windows and older macOS versions **do not support embedded mode**. Use server mode instead.
### Server Mode
A persistent seekdb process, connectable via MySQL client or seekdb-cli (remote DSN). Choose by OS:
| OS | Recommended method | Quick start |
|----|--------------------|-------------|
| Linux (CentOS/RHEL/Anolis/openEuler) | Package manager (RPM) | `curl -fsSL https://obportal.s3.ap-southeast-1.amazonaws.com/download-center/opensource/seekdb/seekdb_install.sh \| sudo bash` |
| Linux (Debian/Ubuntu) | Package manager (DEB) | `sudo apt update && sudo apt install seekdb` |
| macOS 15+ | Homebrew | `brew tap oceanbase/seekdb && brew install seekdb` |
| Any OS with Docker | Docker | `docker run -d -p 2881:2881 oceanbase/seekdb` |
| Windows / macOS (GUI) | OceanBase Desktop | Download from [oceanbase.ai/download](https://www.oceanbase.ai/download) |
**Connect after server mode deployment** (default port 2881, user `root`, empty password):
```bash
mysql -h127.0.0.1 -uroot -P2881 -A -Dtest
# or via seekdb-cli:
seekdb --dsn "seekdb://root:@127.0.0.1:2881/test" status
```
**Minimum requirements**: 1 CPU core, 2 GB RAM, SSD storage.
For full deployment details, see the [deployment docs](https://github.com/oceanbase/seekdb-ecology-plugins/tree/main/agent-skills/skills/seekdb/seekdb-docs/400.guides/400.deploy).
## Prerequisites
Check if seekdb-cli is installed:
```bash
seekdb --version
```
If not installed, choose the method that matches your environment:
**Recommended — pipx (works globally without polluting system Python):**
```bash
# Install pipx first if needed (Ubuntu/Debian)
sudo apt install pipx && pipx ensurepath
# Then install seekdb-cli
pipx install seekdb-cli
```
**Alternative — pip (when inside a project venv or on systems without PEP 668):**
```bash
pip install seekdb-cli
```
> **Note for Ubuntu 23.04+ / Debian 12+:** Direct `pip install` at the system level is blocked by PEP 668.
> Use `pipx` instead — it creates an isolated environment while keeping the `seekdb` command globally available on your PATH.
## Connection
seekdb-cli auto-discovers the connection (env var, `.env`, `~/.seekdb/config.env`, or default `~/.seekdb/seekdb.db`). No setup needed — just run commands directly.
If the user provides a specific DSN, pass it via `--dsn` (must appear **before** the subcommand):
```bash
# Remote mode
seekdb --dsn "seekdb://user:pass@host:port/db" schema tables
# Embedded mode (local database file)
seekdb --dsn "embedded:./seekdb.db" status
seekdb --dsn "embedded:~/.seekdb/seekdb.db?database=mydb" sql "SELECT 1"
```
DSN formats:
- **Remote:** `seekdb://user:pass@host:port/db`
- **Embedded:** `embedded:<path>[?database=<db>]` (default database: `test`)
## Get a Full CLI Guide (run first)
```bash
seekdb ai-guide
```
Returns a structured JSON document with every command, parameter, workflow, safety rules, and output format. **Run this once at the start of any seekdb task** to orient yourself.
## Recommended Workflows
### SQL Database Exploration
```
1. seekdb schema tables → list all tables (name, column count, row count)
2. seekdb schema describe <table> → get column names, types, indexes, comments
3. seekdb table profile <table> → data statistics (null ratios, distinct, min/max, top values)
4. seekdb relations infer → infer JOIN relationships between tables
5. seekdb sql "SELECT ... LIMIT N" → execute SQL with explicit LIMIT
```
### Vector Collection Workflow
```
1. seekdb collection list → list all collections
2. seekdb collection info <name> → collection details and document preview
3. seekdb query <collection> --text "..." → hybrid search (default: semantic + fulltext)
4. seekdb add <collection> --data '...' → add new documents
```
### AI Model Setup Workflow
```
1. seekdb ai model list → check registered models
2. seekdb ai model create <name> --type <type> --model <model_name>
3. seekdb ai model endpoint create <ep> <model> --url <url> --access-key <key>
4. seekdb ai complete "<prompt>" --model <name> → test completion
```
## Command Reference
### seekdb sql
Execute SQL statements. Default is read-only mode.
```bash
# Read query
seekdb sql "SELECT id, name FROM users LIMIT 10"
# Read from file
seekdb sql --file query.sql
# Read from stdin
echo "SELECT 1" | seekdb sql --stdin
# Include table schema in output
seekdb sql "SELECT * FROM orders LIMIT 5" --with-schema
# Disable large-field truncation
seekdb sql "SELECT content FROM articles LIMIT 1" --no-truncate
# Write operation (requires --write flag)
seekdb sql --write "INSERT INTO users (name) VALUES ('Alice')"
seekdb sql --write "UPDATE users SET name = 'Bob' WHERE id = 1"
seekdb sql --write "DELETE FROM users WHERE id = 3"
```
**Output format:**
```json
{"ok": true, "columns": ["id", "name"], "rows": [{"id": 1, "name": "Alice"}], "affected": 0, "time_ms": 12}
```
### seekdb schema tables
```bash
seekdb schema tables
```
```json
{"ok": true, "data": [{"name": "users", "columns": 5, "rows": 1200}, {"name": "orders", "columns": 8, "rows": 50000}]}
```
### seekdb schema describe
```bash
seekdb schema describe orders
```
```json
{"ok": true, "data": {"table": "orders", "comment": "Order table", "columns": [{"name": "id", "type": "int", "comment": "Order ID"}, {"name": "status", "type": "varchar(20)", "comment": "0=pending, 1=paid"}], "indexes": ["PRIMARY(id)", "idx_status(status)"]}}
```
### seekdb schema dump
```bash
seekdb schema dump
```
Returns all `CREATE TABLE` DDL statements.
### seekdb table profile
Generate statistical summary of a table without returning raw data. Helps understand data distribution before writing SQL.
```bash
seekdb table profile <table>
```
```json
{"ok": true, "data": {
"table": "orders",
"row_count": 50000,
"columns": [
{"name": "id", "type": "int", "null_ratio": 0, "distinct": 50000, "min": 1, "max": 50000},
{"name": "user_id", "type": "int", "null_ratio": 0, "distinct": 1200, "min": 1, "max": 1500},
{"name": "amount", "type": "decimal(10,2)", "null_ratio": 0.02, "min": 0.5, "max": 9999.99},
{"name": "status", "type": "varchar(20)", "null_ratio": 0, "distinct": 4, "top_values": ["paid", "pending", "refunded", "cancelled"]},
{"name": "created_at", "type": "datetime", "null_ratio": 0, "min": "2024-01-01", "max": "2026-03-10"}
],
"candidate_join_keys": ["user_id"],
"candidate_time_columns": ["created_at"]
}}
```
### seekdb relations infer
Infer JOIN relationships between tables by analyzing column name patterns (e.g., `user_id` → `users.id`) and type compatibility.
```bash
# Infer all table relationships
seekdb relations infer
# Infer for a specific table only
seekdb relations infer --table orders
```
```json
{"ok": true, "data": [
{"from": "orders.user_id", "to": "users.id", "confidence": "high"},
{"from": "orders.product_id", "to": "products.id", "confidence": "high"},
{"from": "order_items.order_id", "to": "orders.id", "confidence": "high"}
]}
```
### seekdb collection list
```bash
seekdb collection list
```
```json
{"ok": true, "data": [{"name": "docs", "count": 1500}, {"name": "faq", "count": 200}]}
```
### seekdb collection create
```bash
seekdb collection create my_docs --dimension 384 --distance cosine
seekdb collection create my_docs -d 768 --distance l2
```
Options: `--dimension` / `-d` (default: 384), `--distance` cosine | l2 | ip (default: cosine).
### seekdb collection delete
```bash
seekdb collection delete my_docs
```
### seekdb collection info
```bash
seekdb collection info my_docs
```
```json
{"ok": true, "data": {"name": "my_docs", "count": 1500, "dimension": 384, "distance": "cosine", "preview": {"ids": ["doc1", "doc2"], "documents": ["Hello world", "Test doc"], "metadatas": [{"category": "test"}, {}]}}}
```
`dimension` and `distance` are included when available from the collection metadata.
### seekdb query
Search a collection using hybrid (default), semantic (vector), or fulltext mode.
```bash
# Hybrid search (default: semantic + fulltext, RRF ranking)
seekdb query my_docs --text "how to deploy seekdb"
# Semantic (vector) only
seekdb query my_docs --text "how to deploy seekdb" --mode semantic
# Fulltext search
seekdb query my_docs --text "deployment guide" --mode fulltext
# With metadata filter
seekdb query my_docs --text "performance tuning" --where '{"category": "tech"}'
# Limit results (--limit or -n, default: 10)
seekdb query my_docs --text "seekdb" -n 5
```
```json
{"ok": true, "data": {"results": [
{"id": "doc1", "score": 0.92, "document": "How to deploy seekdb...", "metadata": {"category": "tech"}},
{"id": "doc2", "score": 0.85, "document": "seekdb performance tuning...", "metadata": {"category": "tech"}}
], "count": 2}, "time_ms": 35}
```
### seekdb get
Retrieve documents from a collection by IDs or metadata filter.
```bash
# Get by IDs
seekdb get my_docs --ids "doc1,doc2"
# Get by metadata filter (--limit or -n, default: 10)
seekdb get my_docs --where '{"category": "tech"}' -n 20
```
### seekdb add
Add data to a collection. Exactly one source is required: `--file`, `--stdin`, or `--data`. The collection is auto-created if it does not exist.
```bash
# From file (JSON array, JSONL, or CSV)
seekdb add my_docs --file data.jsonl
seekdb add my_docs --file articles.csv --vectorize-column content
# Inline: single object or array
seekdb add my_docs --data '{"id":"1","document":"Hello world","metadata":{"source":"cli"}}'
seekdb add my_docs --data '[{"id":"a","document":"Doc A"},{"id":"b","document":"Doc B"}]'
# From stdin (JSON array or JSONL; use with pipes)
echo '{"id":"1","document":"from pipe"}' | seekdb add my_docs --stdin
some_script | seekdb add my_docs --stdin
```
**Record format**: Each record may have `id` (optional), `document`/`text`/`content` (text to vectorize), and any other fields become metadata. If `embedding` is present, it is used directly.
### seekdb export
Export collection data to a file.
```bash
seekdb export my_docs --output backup.json
seekdb export my_docs --output backup.jsonl -n 5000
```
Options: `--output` (required), `--limit` / `-n` (default: 10000).
### seekdb ai model list
List AI models registered in the database (from `DBA_OB_AI_MODELS` / DBMS_AI_SERVICE). Works in both remote and embedded mode.
```bash
seekdb ai model list
```
```json
{"ok": true, "data": [{"name": "my_llm", "type": "completion", "model_name": "THUDM/GLM-4-9B-0414", "model_id": 1}]}
```
### seekdb ai model create
Register an AI model via `DBMS_AI_SERVICE.CREATE_AI_MODEL`. Create an endpoint separately to use it for completion.
```bash
seekdb ai model create my_llm --type completion --model "THUDM/GLM-4-9B-0414"
seekdb ai model create my_embed --type dense_embedding --model "BAAI/bge-m3"
seekdb ai model create my_rerank --type rerank --model "<rerank_model>"
```
Types: `completion`, `dense_embedding`, `rerank`.
### seekdb ai model delete
Drop an AI model. Drop any endpoints that use it first.
```bash
seekdb ai model delete my_llm
```
### seekdb ai model endpoint create / delete
Create or drop an endpoint that binds an AI model to a URL and API key (so the database can call the model).
```bash
seekdb ai model endpoint create my_ep my_llm \
--url "https://api.siliconflow.cn/v1/chat/completions" \
--access-key "<YOUR_API_KEY>" \
--provider siliconflow
seekdb ai model endpoint delete my_ep
```
**Supported `--provider` values:**
| Provider | Vendor |
|----------|--------|
| `siliconflow` | SiliconFlow (OpenAI-compatible) |
| `openAI` | OpenAI |
| `deepseek` | DeepSeek (OpenAI-compatible) |
| `aliyun-openAI` | Alibaba Cloud (OpenAI-compatible) |
| `aliyun-dashscope` | Alibaba Cloud DashScope |
| `hunyuan-openAI` | Tencent Hunyuan (OpenAI-compatible) |
**Common `--url` values (use the specific interface URL, not the base URL):**
| Vendor | completion | embedding | rerank |
|--------|-----------|-----------|--------|
| SiliconFlow | `https://api.siliconflow.cn/v1/chat/completions` | `https://api.siliconflow.cn/v1/embeddings` | `https://api.siliconflow.cn/v1/rerank` |
| DeepSeek | `https://api.deepseek.com/chat/completions` | — | — |
| Alibaba (OpenAI) | `https://dashscope.aliyuncs.com/compatible-mode/v1/chat/completions` | `https://dashscope.aliyuncs.com/compatible-mode/v1/embeddings` | — |
| Tencent Hunyuan | `https://api.hunyuan.cloud.tencent.com/v1/chat/completions` | `https://api.hunyuan.cloud.tencent.com/v1/embeddings` | — |
### seekdb ai complete
Run text completion using the database `AI_COMPLETE` function. Requires a registered **completion** model and an endpoint. Supported in both remote and embedded mode.
```bash
seekdb ai complete "Summarize this table structure" --model my_llm
```
```json
{"ok": true, "data": {"model": "my_llm", "response": "The table has..."}, "time_ms": 1200}
```
### seekdb ai-guide
Output a structured JSON guide for AI Agents containing all commands, parameters, workflow, and safety rules. Execute once to learn the full CLI.
```bash
seekdb ai-guide
```
### seekdb status
```bash
seekdb status
```
Returns CLI version, server version, database name, and connectivity.
## Safety Features
### Row Protection
Queries without `LIMIT` are automatically probed. If result exceeds 100 rows, execution is blocked:
```json
{"ok": false, "error": {"code": "LIMIT_REQUIRED", "message": "Query returns more than 100 rows. Please add LIMIT to your SQL."}}
```
**Action**: Add an explicit `LIMIT` clause and retry.
### Write Protection
Write operations (INSERT/UPDATE/DELETE) are blocked by default:
```json
{"ok": false, "error": {"code": "WRITE_NOT_ALLOWED", "message": "Write operations require --write flag."}}
```
**Action**: Add `--write` flag to enable write operations.
Even with `--write`, these are always blocked:
- `DELETE` / `UPDATE` without `WHERE` clause
- `DROP` / `TRUNCATE` statements
### Error Auto-Correction
On SQL errors, the CLI automatically attaches schema hints:
**Column not found** → returns the table's column list and indexes:
```json
{"ok": false, "error": {"code": "SQL_ERROR", "message": "Unknown column 'username'"}, "schema": {"table": "users", "columns": ["id", "name", "email"], "indexes": ["PRIMARY(id)"]}}
```
**Table not found** → returns available table names:
```json
{"ok": false, "error": {"code": "SQL_ERROR", "message": "Table 'user' does not exist"}, "schema": {"tables": ["users", "orders", "products"]}}
```
**Action**: Use the schema info to correct the SQL and retry.
### Large Field Truncation
TEXT/BLOB fields are truncated to 200 characters by default, with original length noted:
```json
{"content": "First 200 characters of content...(truncated, 8520 chars)"}
```
Use `--no-truncate` to get full content when needed.
### Sensitive Field Masking
Columns matching sensitive patterns are automatically masked:
| Pattern | Example Output |
|---------|---------------|
| phone/mobile/tel | `138****5678` |
| email | `z***@gmail.com` |
| password/secret/token | `******` |
| id_card/ssn | `110***********1234` |
## Output Formats
Default is JSON. Switch with `--format` / `-f`:
```bash
seekdb -f table sql "SELECT id, name FROM users LIMIT 5"
seekdb --format csv sql "SELECT id, name FROM users LIMIT 5"
seekdb -f jsonl sql "SELECT id, name FROM users LIMIT 5"
```
All formats now work with non-row data (e.g., `schema tables`, `collection list`). CSV and JSONL will auto-detect list-of-dict data in the `data` field.
## Exit Codes
| Code | Meaning |
|------|---------|
| 0 | Success |
| 1 | Business error (SQL error, connection error, etc.) |
| 2 | Usage error (missing arguments, invalid options) |
## Operation Logging
All commands are logged to `~/.seekdb/sql-history.jsonl` (seekdb-cli SQL execution history) for audit:
```json
{"ts": "2026-03-12T14:23:01", "command": "sql", "sql": "SELECT id FROM users LIMIT 10", "ok": true, "rows": 10, "time_ms": 12}
```
---
# Part 2: Documentation Lookup
Use documentation lookup when you need to understand a seekdb concept, look up SQL syntax, find configuration details, or answer user questions about seekdb.
> **Tip**: For live database state (tables, schemas, data), run CLI commands directly. For concepts, syntax, and how-to guidance, search the docs.
## When to Use Documentation Lookup
- Need to understand a seekdb concept (vector search, hybrid search, HNSW index, etc.)
- Need SQL or PL syntax reference not answerable by `seekdb schema` commands
- Need deployment, configuration, or integration guidance
- CLI returned an error and you need to understand why from the docs
## Path Resolution
1. Read this SKILL.md to get its absolute path and extract the parent directory as `<skill_dir>`
2. Catalog: `<skill_dir>references/seekdb-docs-catalog.jsonl`
If missing locally, load from: `https://raw.githubusercontent.com/oceanbase/seekdb-ecology-plugins/main/agent-skills/skills/seekdb/references/seekdb-docs-catalog.jsonl`
## Documentation Workflow
### Step 1: Search Catalog
Search the catalog file for lines containing the query keywords. Each line is one JSON object with `path`, `description`, and `branch`.
```bash
# Example: search for "vector search" in the catalog
grep -i "vector search" <skill_dir>references/seekdb-docs-catalog.jsonl
```
### Step 2: Match Query
- Extract `path`, `description`, and `branch` from search results
- Select entries whose descriptions best match the query semantically
- Consider multiple matches for comprehensive answers
### Step 3: Fetch Document
Fetch the document from the public docs URL:
- URL: `https://raw.githubusercontent.com/oceanbase/seekdb-doc/[branch]/en-US/[path]`
- `[branch]` and `[path]` come from the catalog entry (e.g., `V1.0.0`, `V1.1.0`)
## Example
```
Query: "How to integrate with Claude Code?"
1. Search catalog for "claude code"
2. Found: {"path": "300.integrations/300.developer-tools/700.claude-code.md",
"description": "This guide explains how to use the seekdb plugin with Claude Code...",
"branch": "V1.0.0"}
3. Fetch: https://raw.githubusercontent.com/oceanbase/seekdb-doc/V1.0.0/en-US/300.integrations/300.developer-tools/700.claude-code.md
```
See [references/doc-examples.md](references/doc-examples.md) for more workflow examples.
---
> If the information you need cannot be found in the catalog or the CLI output, visit the official seekdb documentation at **[oceanbase.ai/docs](https://www.oceanbase.ai/docs/)** for the most complete and up-to-date reference.Scanned 6/6/2026
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