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sujkh85

Infinite Context Keeper

by sujkh85

semantic_search_memory

Search through stored memory chunks by semantic similarity to return the most relevant context for your query.

Instructions

관련 메모리 청크를 반환합니다. sqlite-vec(vec0) KNN이 켜지면 DB 내 벡터 인덱스로 검색하고, 아니면 JS 코사인으로 폴백합니다.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
queryYes
project_idYes
limitNo
session_idNo
Behavior3/5

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

Discloses important runtime behavior: vector index (sqlite-vec) vs. JS cosine fallback. But with no annotations, it omits other traits like idempotency, error handling, or permission requirements.

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 short sentences, no filler. Purpose and key behavioral detail front-loaded. Could benefit from structured sections but remains efficient.

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?

Missing critical context: no output schema, no explanation of return format, no human-friendly description of what a 'memory chunk' contains. Does not mention optional session_id filtering or limit semantics.

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

Parameters1/5

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

Schema coverage is 0% and description adds zero information about any parameter (query, project_id, limit, session_id). The agent must rely entirely on parameter names and types, which are insufficient.

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 clearly states the tool returns relevant memory chunks using semantic search (vector index or cosine fallback), distinguishing it from non-semantic siblings like memory_search. However, it doesn't explicitly contrast with search_and_inject_memory, and the Korean text may be less accessible.

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 (e.g., memory_search, search_and_inject_memory). No prerequisites, context, or alternatives mentioned.

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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