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mimir_embed

Destructive

Generate and store dense vector embeddings for entities via Ollama, supporting single entity or batch mode.

Instructions

Generate and store dense vector embeddings for entities via Ollama /api/embed. Supports single entity (category+key) or batch mode (batch_category). Requires --llm-endpoint to be set.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
keyNoEntity key for single mode
textNoText to embed (omit to use entity body_json)
categoryNoEntity category for single mode
batch_limitNoMax entities in batch mode
batch_categoryNoEmbed all entities in this category lacking embeddings

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault
embeddedNoNumber of entities embedded
dimensionsNoVector dimensions
Behavior3/5

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

Annotations already indicate destructiveHint=true, so the description's addition of 'Generate and store' and the dependency on Ollama adds some context. But it doesn't detail what gets overwritten or the exact side effects.

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?

Two sentences that front-load the purpose and then detail modes and requirements. Every sentence adds value with no redundancy.

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?

For a tool with 5 optional parameters and an output schema, the description covers operation modes and prerequisites. It doesn't describe return values, but the output schema likely handles that. It's mostly complete.

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 description coverage is 100%, so the description adds minimal value beyond the overview of modes. It reiterates the mode logic but doesn't enhance parameter understanding significantly.

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 it generates and stores dense vector embeddings for entities, distinguishes between single and batch modes, and mentions the Ollama endpoint. This differentiates it from sibling tools like mimir_recall or mimir_remember.

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?

It explains when to use single mode (category+key) vs batch mode (batch_category) and notes the requirement for --llm-endpoint. However, it lacks explicit exclusions or alternatives, so it's not a 5.

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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