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Save Talonic Schema

talonic_save_schema

Save a reusable schema to the workspace for consistent data extraction across documents. Provide a name and definition as JSON Schema or flat field-type map.

Instructions

Save a reusable schema to the workspace for use across future extractions.

USE WHEN: the user confirms a schema/template they want to reuse across documents. NOT FOR: a single one-off extraction (pass the schema inline to talonic_extract instead). ARGS: name; definition — a JSON Schema ({type:'object',properties:{...}}) or a flat {field:'type'} map. RETURNS: the saved schema with id and short_id. Pass either to talonic_extract as schema_id.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
nameYesHuman-readable name for the schema, e.g. 'Standard Invoice'.
definitionYesSchema definition. Most reliable: full JSON Schema {type:'object', properties:{...}}. Also accepted: a flat key-type map {field_name:'string', amount:'number'} which the API normalises.
descriptionNoOptional description of what this schema extracts and when to use it.

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault
idYesUUID of the newly saved schema.
short_idNoHuman-readable short id (SCH-XXXXXXXX).
nameYes
descriptionNoSchema description, or null when the schema was saved without one. The API explicitly maps the absent case to null (see SchemaResponse in openapi.yaml).
definitionNoFinal schema definition as stored, normalised by the API.
field_countNo
versionNoSchema version (1 for new schemas; increments on update).
created_atNo
updated_atNo
linksNo
Behavior4/5

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

Annotations indicate destructiveHint=false, which aligns with saving non-destructive. Description adds that it saves to workspace and returns id/short_id. Could mention if same name overwrites, but overall sufficient.

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?

Extremely concise: one sentence purpose, then usage, then args, then returns. No wasted words.

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

Completeness5/5

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

All necessary context provided given schema coverage and output description. Parameter count, required fields, and return value all addressed.

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

Parameters4/5

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

Input schema has 100% coverage. Description adds value by explaining definition accepts JSON Schema or flat map, and that return includes id and short_id for later use.

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?

Clear verb 'Save' with specific resource 'a reusable schema to the workspace'. Distinguishes from sibling talonic_extract by stating it's for reuse across documents, not one-off extractions.

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

Usage Guidelines5/5

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

Explicitly states 'USE WHEN' and 'NOT FOR' with direct alternative (talonic_extract). Provides clear context for when to choose this tool.

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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