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marerem

longmem

rebuild_index

Build an ANN index after adding 256+ entries to accelerate vector searches. Safe to call anytime without modifying existing data.

Instructions

Rebuild the vector search index for faster similarity search.

LanceDB falls back to brute-force scan when the table has fewer than 256 rows. Once you have 256+ entries, call this once to build an ANN index — subsequent searches will be significantly faster.

Safe to call at any time; existing data is not modified.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault

No arguments

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault
resultYes
Behavior4/5

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

Without annotations, the description takes full responsibility for behavioral disclosure. It states the tool is safe, does not modify data, and explains the threshold for benefits. It could elaborate on potential side effects like temporary performance impact or whether the call is idempotent, but overall it provides sufficient transparency.

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 extremely concise, consisting of three short sentences. The main purpose is front-loaded, followed by specific conditions and safety reassurance. Every sentence adds value without 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?

Given the tool's simplicity (no parameters), the description covers the essential points: purpose, optimal use case, and safety. It could mention if the tool is idempotent or what the output indicates, but overall it's sufficiently complete for an agent to decide when to invoke it.

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?

The tool has zero parameters, so the input schema is fully covered. The description does not need to add parameter details, and the baseline score of 4 applies as per guidelines. No enrichment is necessary.

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 specifies the tool's function: rebuilding the vector search index to accelerate similarity search. It distinguishes itself from sibling tools like search_by_project and search_similar, which are search tools, and list_recent, which is for listing. The verb+resource combination is precise and unambiguous.

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 provides clear usage context: call after having 256+ rows for ANN index benefit, and note that it's safe and non-destructive. However, it lacks explicit when-not-to-use guidance (e.g., don't call if index already built) and does not name alternative tools for similar functionality.

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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