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memory_search

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Search agent memory files using natural language queries to find relevant information with TF-IDF ranking. Retrieve matching sections with relevance scores for efficient context retrieval.

Instructions

Search agent memory using TF-IDF ranking. Returns a compact index of matching sections with relevance scores. Use memory_detail to fetch full content of interesting results. Searches MEMORY.md + memory/*.md files.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
queryYesNatural language search query (e.g. 'SDK version fix', '상표 출원')
memory_dirNoPath to memory directory (default: ./memory)
limitNoMax results (default: 10)
enhancedNoIf true, includes full snippets for top results (uses more tokens). Default: compact index only.
Behavior4/5

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

Annotations already declare readOnlyHint=true, indicating a safe read operation. The description adds valuable context beyond this: it specifies the ranking method ('TF-IDF ranking'), output format ('compact index'), token usage implications ('uses more tokens' for enhanced mode), and file scope. No contradiction with annotations exists.

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 front-loaded with core functionality and efficiently structured in three sentences with zero waste. Each sentence adds distinct value: the first defines the tool's purpose, the second guides usage with alternatives, and the third clarifies scope. It is appropriately sized for the tool's complexity.

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 moderate complexity, rich annotations (readOnlyHint), and full schema coverage, the description is mostly complete. It covers purpose, usage, and behavioral context well. However, without an output schema, it could benefit from more detail on return values (e.g., format of 'compact index'), slightly limiting completeness.

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 schema fully documents all parameters. The description adds minimal semantic value beyond the schema, such as hinting at the enhanced parameter's token impact, but does not provide significant additional meaning. Baseline 3 is appropriate given high schema coverage.

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 the specific action ('Search agent memory using TF-IDF ranking'), the resource ('MEMORY.md + memory/*.md files'), and the output format ('compact index of matching sections with relevance scores'). It explicitly distinguishes from sibling 'memory_detail' by stating 'Use memory_detail to fetch full content of interesting results,' showing clear differentiation.

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

Usage Guidelines5/5

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

The description provides explicit guidance on when to use this tool ('Search agent memory') versus alternatives ('Use memory_detail to fetch full content of interesting results'). It also implies context by specifying the scope ('Searches MEMORY.md + memory/*.md files'), giving clear direction for usage.

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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