basic-memory

Infer Schema

schema_infer

Read-only

Analyzes existing notes of one type and suggests a Picoschema definition to standardize fields and note structure.

Instructions

Analyze existing notes of one type and suggest a Picoschema definition. A schema is a note with type: schema whose entity field names the note type it describes.

Input Schema

Name	Required	Description	Default
`project`	No	Project name. Optional -- server will resolve.
`note_type`	Yes	The note type to analyze (e.g., "person", "meeting").
`threshold`	No	Minimum frequency (0-1) for a field to be suggested as optional. Default 0.25 (25%). Fields above 95% become required.
`project_id`	No	Project external_id (UUID). Prefer this over `project` when known — it routes to the exact project regardless of name collisions across cloud workspaces. Takes precedence over `project`. Get from list_memory_projects().
`output_format`	No		text

Output Schema

Name	Required	Description	Default
`result`	Yes

Schema Changelog

Changes observed during successful MCP inspections.

Addedv0.24.1Oct 23, 2026

TDQS

A3.5/5.0

Behavior3/5

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

Annotations already declare readOnlyHint=true and destructiveHint=false, so safety is covered. The description adds conceptual context (what a schema note is) but does not disclose requirements such as minimum note counts, performance, or what the suggestion entails beyond the schema itself.

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

Conciseness4/5

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

Two sentences with the core purpose front-loaded and a useful definitional follow-up. No wasted text, though slightly sparse.

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

Completeness4/5

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

With an output schema, annotations, and 80% param coverage, the description is largely complete. The only gap is lack of guidance on prerequisites (e.g., needing enough example notes) or how the suggestion should be interpreted.

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?

Schema coverage is 80%, so the schema documents note_type, threshold, project, project_id, and output_format adequately. The description adds no parameter-level meaning beyond what the schema provides, so baseline 3 applies.

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

Purpose4/5

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

States a specific verb+resource: 'Analyze existing notes of one type and suggest a Picoschema definition.' This clearly distinguishes it from sibling schema tools (schema_validate, schema_diff), though it doesn't name an alternative explicitly. The second sentence clarifies what a schema is, aiding understanding.

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

Usage Guidelines3/5

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

Implies usage (analyze notes to derive a schema) but offers no explicit when-to-use guidance versus schema_validate, schema_diff, or manual schema creation, and no prerequisite conditions like having sufficient notes of that type.

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