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search_by_category

Filter and retrieve stored information by specific categories like decisions, preferences, or facts to organize and access relevant workspace memories.

Instructions

Search memories by category (e.g. 'decision', 'preference', 'fact'). Use memory_categories first to see available categories.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
categoryYes

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault
resultYes
Behavior2/5

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

No annotations are provided, so the description carries full burden. It mentions the need to check available categories first, which is useful context about prerequisites. However, it doesn't disclose behavioral traits like whether this is a read-only operation, what the search returns, performance characteristics, or error conditions.

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 perfectly concise with two sentences that each serve a clear purpose: the first states what the tool does, the second provides essential usage guidance. There's zero wasted text and it's front-loaded with the core functionality.

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

Completeness3/5

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

Given that there's an output schema (which handles return values), no annotations, and only one parameter with 0% schema coverage, the description provides basic but incomplete context. It covers the purpose and prerequisite, but lacks behavioral details about how the search works, what results to expect, or error handling.

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 0%, so the schema provides no parameter documentation. The description adds some semantic meaning by explaining that 'category' should be values like 'decision', 'preference', or 'fact', and references 'memory_categories' for available options. However, it doesn't fully document the parameter's format, constraints, or examples beyond the brief mention.

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's purpose: 'Search memories by category' with examples of categories. It specifies the resource (memories) and action (search), but doesn't distinguish it from sibling tools like 'search_by_tag' or 'unified_search' beyond mentioning the category parameter.

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 explicit guidance: 'Use memory_categories first to see available categories.' This tells the agent when to use this tool (after checking categories) and references a specific sibling tool. However, it doesn't mention when NOT to use it or alternatives like 'search_by_tag' or 'unified_search'.

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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