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Compose Database From Intent

compose_database_from_intent

Generate an AFFiNE database from a declarative intent, with schema, kanban view, and starter rows for task boards or issue trackers.

Instructions

Create a useful AFFiNE database/data-view from declarative intent. Supports task_board and issue_tracker presets with starter schema, kanban view, and optional starter rows.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
docIdYesDocument ID containing the database
titleNoOptional database title. Defaults to the intent preset title.
intentYesDeclarative database intent to compose.
seedRowsNoOptional starter rows. If omitted, the preset starter rows are used.
placementNoOptional insertion target/position
workspaceIdNoWorkspace ID (optional if default set)

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault
docIdYes
lossyYes
statsYes
titleYes
viewsYes
intentYes
columnsYes
viewIdsYes
warningsYes
columnIdsYes
rowBlockIdsYes
workspaceIdYes
primaryViewIdYes
databaseBlockIdYes
Behavior3/5

Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?

The description adds context about starter schema, kanban view, and optional starter rows, which is useful. However, with annotations including openWorldHint=true and idempotentHint=false, the description does not explain potential side effects (e.g., modifying the target document or creating linked resources). It is not misleading, but it misses an opportunity to clarify non-obvious behaviors.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Conciseness5/5

Is the description appropriately sized, front-loaded, and free of redundancy?

The description is a single, front-loaded sentence that immediately states the core action and then lists key features. Every word adds value, with no redundancy or filler.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Completeness3/5

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

The description covers the what and the presets, but it does not mention that a target docId is required, which is a critical prerequisite for invocation. The output schema exists, so return values are covered, but the description leaves the agent to infer the need for a host document from the schema alone.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Parameters3/5

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

The schema covers 100% of parameters, so the description carries no additional burden. It mentions 'optional starter rows' and 'presets', which aligns with seedRows and intent, but does not add meaning beyond the schema's already-descriptive parameter details.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Purpose5/5

Does the description clearly state what the tool does and how it differs from similar tools?

The description clearly states the tool's action ('Create') and its resource ('AFFiNE database/data-view') with a specific mechanism ('from declarative intent'). It also names the supported presets (task_board, issue_tracker), which distinguishes it from sibling tools that handle individual rows or document creation.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Usage Guidelines4/5

Does the description explain when to use this tool, when not to, or what alternatives exist?

The description gives clear usage context by mentioning the supported presets and optional starter rows, implying when to use it (for task boards or issue trackers). It does not explicitly exclude alternatives, but it provides enough context for a knowledgeable agent to select it over row-level or document-level tools.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.

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