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akai_vec

Perform local vector search using sqlite-vec. Accepts .bf files and outputs .bfvec files for efficient embedding retrieval.

Instructions

AkaiVec — local vector search via sqlite-vec. Accepts: .bf. Produces: .bfvec. (category: knowledge)

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
argsNoCLI arguments to pass to the operator
stdinNoOptional stdin data
Behavior2/5

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

With no annotations, the description must disclose behavioral traits. It mentions 'local vector search' but doesn't specify if it modifies state, requires prior indexing, or has side effects. The output production implies creation, but safety profile is unclear.

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

Conciseness3/5

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

The description is extremely concise, but it lacks structure and front-loading of key information. While no words are wasted, the brevity sacrifices clarity and completeness.

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

Completeness2/5

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

Given the complexity of a vector search tool (likely involving database state, queries, and output format), the description is insufficient. No output schema exists, and behavioral details are missing, making it hard for an agent to use correctly.

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

Parameters2/5

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

Input schema has 100% coverage, but parameter descriptions are generic ('CLI arguments', 'Optional stdin data'). The tool description adds no extra meaning about expected arguments or usage patterns, failing to compensate for schema brevity.

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?

The description states it's for local vector search via sqlite-vec, which is clear. It mentions input (.bf) and output (.bfvec), providing a basic understanding of data flow. However, the cryptic abbreviations may confuse agents without further context.

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

Usage Guidelines2/5

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

No guidance on when to use this tool versus siblings like akai_embed, akai_query, or akai_index. The description fails to specify context, prerequisites, or alternatives, leaving the agent to guess.

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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