Awesome-omni-skill catalyzed
Help with Catalyzed API - datasets, tables, pipelines, queries, vector search. Use when building Catalyzed integrations.
install
source · Clone the upstream repo
git clone https://github.com/diegosouzapw/awesome-omni-skill
Claude Code · Install into ~/.claude/skills/
T=$(mktemp -d) && git clone --depth=1 https://github.com/diegosouzapw/awesome-omni-skill "$T" && mkdir -p ~/.claude/skills && cp -r "$T/skills/data-ai/catalyzed" ~/.claude/skills/diegosouzapw-awesome-omni-skill-catalyzed && rm -rf "$T"
manifest:
skills/data-ai/catalyzed/SKILL.mdsource content
Catalyzed API Assistant
You are helping a developer integrate with the Catalyzed data platform.
Live Documentation (fetched at load time)
!
curl -sf https://docs.catalyzed.ai/llms.txt 2>/dev/null
Quick Reference (fallback if above is empty)
Base URL:
https://api.catalyzed.ai
Docs: https://docs.catalyzed.ai
Auth: Authorization: Bearer <API_TOKEN>
Core Endpoints
| Resource | Method | Endpoint | Description |
|---|---|---|---|
| Teams | GET | /teams | List user's teams |
| Teams | GET | /teams/:teamId | Get team by ID |
| Datasets | GET | /datasets | List datasets |
| Datasets | POST | /datasets | Create dataset |
| Datasets | GET | /datasets/:datasetId | Get dataset by ID |
| Datasets | PUT | /datasets/:datasetId | Update dataset |
| Datasets | DELETE | /datasets/:datasetId | Delete dataset |
| Tables | GET | /dataset-tables | List tables |
| Tables | POST | /dataset-tables | Create table with schema |
| Tables | GET | /dataset-tables/:tableId | Get table by ID |
| Tables | PUT | /dataset-tables/:tableId | Update table metadata |
| Tables | DELETE | /dataset-tables/:tableId | Delete table |
| Rows | POST | /dataset-tables/:tableId/rows?mode=append | Insert rows |
| Rows | POST | /dataset-tables/:tableId/rows?mode=upsert | Upsert rows |
| Rows | POST | /dataset-tables/:tableId/rows?mode=delete | Delete rows by PK |
| Queries | POST | /dataset-tables/:tableId/query | Execute SQL query |
| Schema | GET | /dataset-tables/:tableId/schema | Get table schema |
| Pipelines | GET | /pipelines | List pipelines |
| Pipelines | POST | /pipelines | Create pipeline |
| Pipelines | GET | /pipelines/:pipelineId | Get pipeline by ID |
| Pipelines | PUT | /pipelines/:pipelineId | Update pipeline |
| Pipelines | POST | /pipelines/:pipelineId/trigger | Trigger pipeline execution |
| Executions | GET | /pipeline-executions | List executions |
| Executions | GET | /pipeline-executions/:executionId | Get execution status |
| Knowledge Bases | GET | /knowledge-bases | List knowledge bases |
| Knowledge Bases | POST | /knowledge-bases | Create knowledge base |
| Knowledge Bases | GET | /knowledge-bases/:kbId | Get knowledge base |
| Knowledge Bases | POST | /knowledge-bases/:kbId/sources | Add source (file or table) |
| Knowledge Bases | POST | /knowledge-bases/:kbId/query | Vector search query |
| Files | POST | /files | Upload file |
| Files | GET | /files/:fileId | Get file metadata |
| API Tokens | GET | /api-tokens | List API tokens |
| API Tokens | POST | /api-tokens | Create API token |
Authentication
All API requests require a Bearer token in the Authorization header:
curl -H "Authorization: Bearer cat_YOUR_API_TOKEN" \ https://api.catalyzed.ai/teams
API tokens are created via the Catalyzed dashboard or API. Tokens have a
cat_ prefix.
Common Patterns
Create a dataset and table:
# Create dataset curl -X POST https://api.catalyzed.ai/datasets \ -H "Authorization: Bearer $TOKEN" \ -H "Content-Type: application/json" \ -d '{"teamId": "...", "name": "My Dataset"}' # Create table with schema curl -X POST https://api.catalyzed.ai/dataset-tables \ -H "Authorization: Bearer $TOKEN" \ -H "Content-Type: application/json" \ -d '{ "datasetId": "...", "tableName": "events", "fields": [ {"name": "id", "arrowType": "utf8", "nullable": false}, {"name": "timestamp", "arrowType": "timestamp[us]", "nullable": false}, {"name": "data", "arrowType": "utf8", "nullable": true} ], "primaryKeyColumns": ["id"] }'
Insert data:
curl -X POST "https://api.catalyzed.ai/dataset-tables/:tableId/rows?mode=append" \ -H "Authorization: Bearer $TOKEN" \ -H "Content-Type: application/json" \ -d '[ {"id": "1", "timestamp": "2025-01-01T00:00:00Z", "data": "hello"}, {"id": "2", "timestamp": "2025-01-02T00:00:00Z", "data": "world"} ]'
Query data:
curl -X POST https://api.catalyzed.ai/dataset-tables/:tableId/query \ -H "Authorization: Bearer $TOKEN" \ -H "Content-Type: application/json" \ -d '{"sql": "SELECT * FROM events WHERE timestamp > '\''2025-01-01'\''", "maxRows": 100}'
Fetching Detailed Documentation
When the user needs details on a specific topic, use WebFetch to get the markdown version:
- Quickstart:
https://docs.catalyzed.ai/getting-started/quickstart.md - Querying Data:
https://docs.catalyzed.ai/guides/querying-data.md - Ingesting Data:
https://docs.catalyzed.ai/guides/ingesting-data.md - Pipelines:
https://docs.catalyzed.ai/concepts/pipelines.md - Tables:
https://docs.catalyzed.ai/concepts/tables.md - Knowledge Bases:
https://docs.catalyzed.ai/concepts/knowledge-bases.md - Vector Search:
https://docs.catalyzed.ai/guides/vector-search.md - Full index:
https://docs.catalyzed.ai/llms.txt
For code examples, see examples.md. For full API reference, see api-reference.md.