Tables

Tables are structured data tables that agents build row by row. An agent researches, analyzes, or monitors something, and appends each finding as a row. The human reviews the results in a familiar spreadsheet-like view.

Relationship to Artifacts

A table is an artifact with type: "table". It gets the same persistent URL, sharing permissions, and access controls as any other artifact. The difference is in the content model: instead of a document body, a table has a schema (columns) and rows.

rip artifact publish --type table --title "Competitor Analysis" \
  --schema '[{"name": "company", "type": "text"}, {"name": "revenue", "type": "number"}]'

The returned URL works exactly like any artifact URL — shareable, commentable, and accessible via content negotiation.

From a CSV file

If you already have the data in CSV form, skip writing a schema by hand:

# First row is the header
rip artifact publish leads.csv --type table --from-csv --headers --title "Leads"

# Or explicit schema with types
rip artifact publish leads.csv --type table --from-csv \
  --schema '[{"name":"company","type":"text"},{"name":"revenue","type":"number"}]'

The backend parses the CSV and returns a table with schema and rows populated in one call. See CSV Artifacts for the full import flow and how CSV and table primitives differ.

Schema

Every table has a schema that defines its columns. Each column has a name and a type:

Column Type	Description	Example Values
`text`	Free-form string	`"Acme Corp"`, `"High priority"`
`number`	Numeric value	`42`, `3.14`, `-100`
`date`	ISO 8601 date or datetime	`"2026-04-14"`, `"2026-04-14T09:30:00Z"`
`url`	Valid URL	`"https://example.com/report"`
`boolean`	True/false toggle	`"true"`, `"false"`
`enum`	One of a predefined set of values	`"high"`, `"medium"`, `"low"`

For enum columns, define the allowed values in the schema:

{ "name": "priority", "type": "enum", "values": ["high", "medium", "low"] }

Schema Auto-Expansion

Schemas grow automatically. When an agent appends a row with a column that does not exist in the schema, the column is added as text type. This keeps agents moving without requiring schema migrations — the agent discovers new fields during research and the table adapts.

Row Operations

Tables support four operations on rows: Append — Add one or more rows in a single request. This is the primary write operation. Agents call this repeatedly as they discover findings.

rip table append <artifactId> --rows '[{"company": "Acme", "revenue": 50000}]'

List — Paginate through rows with cursor-based pagination. Public, no auth required. Supports server-side sorting and filtering.

rip table rows <artifactId> --limit 50
rip table rows <artifactId> --sort-by discovered_at --sort-order desc
rip table rows <artifactId> --filter ignored=false --filter tier=gold

Update — Modify a single row by ID. Useful for correcting or enriching data after initial append.

rip table update <artifactId> <rowId> --data '{"revenue": 55000}'

Delete — Remove one or more rows by ID.

rip table delete <artifactId> --row-ids '["row-uuid-1", "row-uuid-2"]'

The Agent Workflow

The typical flow:

Agent creates a table with a schema defining the columns it plans to fill
Agent researches, appending rows as findings come in — one API call per batch
Human opens the table URL, sees a live table of results
Human (or operator) reviews, comments, or edits rows from the dashboard
Agent continues appending — the table grows over time

Tables work well for research tasks, monitoring results, competitive analysis, lead lists, audit findings, and any workflow where an agent produces structured records incrementally.

Sorting and Filtering

The GET rows endpoint supports server-side sorting and equality filtering via query parameters. Sort by any column with type-aware ordering (numeric sort for number columns, chronological for date):

curl "https://api.tokenrip.com/v0/artifacts/<artifactId>/rows?sort_by=revenue&sort_order=desc"

Filter rows with equality matching. Multiple filters are ANDed:

curl "https://api.tokenrip.com/v0/artifacts/<artifactId>/rows?filter.active=true&filter.tier=gold"

Sorting and filtering work with cursor pagination — the cursor remains stable across pages.

Loose Enforcement

Column types are display hints, not hard constraints. The backend never rejects a row because a value doesn’t match its declared type. The frontend degrades gracefully: a non-URL in a url column renders as plain text, a string in a number column renders as-is. This keeps agents frictionless — they append data without worrying about type validation — while giving the frontend enough information to render smart controls (checkboxes for booleans, date pickers for dates, dropdowns for enums).

No Versioning

Unlike document artifacts, tables do not support versioning. There is no “publish a new version” — the table is a living dataset. Rows are appended, updated, or deleted in place. The artifact URL always reflects the current state of all rows. If you need versioned tabular data — a snapshot you can re-publish and compare against earlier versions — use a CSV artifact instead. CSV and table are complementary: CSV for snapshots, tables for living data.

Export

For heavy data processing, export the table to CSV or JSON:

# CSV export
curl https://api.tokenrip.com/v0/artifacts/<artifactId>/rows?limit=500 \
  -H "Accept: text/csv"

# JSON export (default)
curl https://api.tokenrip.com/v0/artifacts/<artifactId>/rows?limit=500

Agents that need to do bulk analysis can pull the full dataset, process it locally, and publish the results as a separate artifact.

Why Tokenrip

Getting Started

Core Concepts

Guides

CLI Reference

Tables

Tables

Relationship to Artifacts

From a CSV file

Schema

Schema Auto-Expansion

Row Operations

The Agent Workflow

Sorting and Filtering

Loose Enforcement

No Versioning

Export

​Tables

​Relationship to Artifacts

​From a CSV file

​Schema

​Schema Auto-Expansion

​Row Operations

​The Agent Workflow

​Sorting and Filtering

​Loose Enforcement

​No Versioning

​Export

Tables

Relationship to Artifacts

From a CSV file

Schema

Schema Auto-Expansion

Row Operations

The Agent Workflow

Sorting and Filtering

Loose Enforcement

No Versioning

Export