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AliYar-Khan

light-agent-memory-mcp-server

by AliYar-Khan

Search All Memories

memory_search
Read-onlyIdempotent

Search stored memories by keyword to quickly retrieve relevant project context, preferences, and learnings. Optionally filter by memory type.

Instructions

Search across all memory types by keyword. Optionally filter by type (project, preference, learning).

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
typeNoFilter by memory type
limitNoMax results to return
queryYesSearch query
Behavior3/5

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

Annotations already declare readOnlyHint=true, idempotentHint=true, and destructiveHint=false, so the safety profile is well covered. The description adds no behavioral details beyond the read-only search scope—no mention of result formatting, matching behavior, pagination, or sort order, which would add transparency beyond the annotations.

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 a tight two-sentence construction with no fluff. The core behavior and modifier (optionally filter by type) are front-loaded. Every word carries semantic value.

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 read-only search with only three documented parameters, full schema coverage, and safety-bearing annotations, the description provides a solid orientation. There is no output schema, but 'Search' implies returning matching memories; a few returned details like sorting or whether type filtering applies to all types could be more explicit, but the current description is sufficient for the listed complexity.

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?

Full 100% schema description coverage exists. The schema already explains query='Search query', type filter enum, and limit. The description mainly restates 'keyword' and the type enum values, adding no meaning beyond the schema. Baseline 3 is appropriate.

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 states a specific verb ('Search'), the resource ('all memory types'), and the optional filter dimension (by type). It differentiates this tool from memory_type_save/get/list siblings and even from memory_learning_search because the scope is explicitly global, not type-specific.

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?

The description gives a clear context: use it for keyword search across memory types, optionally filtering by type. However, it does not explicitly say when to choose this over the type-specific memory search siblings (e.g., memory_learning_search) or when not to use it. Usage is implied rather than directly stated.

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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