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search_memory

Search stored agent memories by text query to retrieve relevant coding context, decisions, procedures, or feedback for development tasks.

Instructions

Search memories by text query. Returns ranked results.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
queryYes
typeNo
limitNo
Behavior2/5

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

No annotations are provided, so the description carries the full burden. It mentions 'ranked results' which adds some behavioral context, but doesn't disclose critical details like whether this is a read-only operation, what permissions are needed, how ranking works, or if there are rate limits. For a search tool with zero annotation coverage, this is insufficient.

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 extremely concise and front-loaded: two short sentences that directly state the tool's function and output. Every word earns its place with zero waste or redundancy.

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 (3 parameters, 0% schema coverage, no annotations, no output schema), the description is incomplete. It doesn't explain parameter meanings, behavioral constraints, or how results are structured. For a search tool with multiple parameters and no structured support, more context is needed.

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 description must compensate. It only mentions 'text query' for the 'query' parameter, but doesn't explain the 'type' enum values or 'limit' parameter. Since it doesn't add meaningful semantic details beyond the bare schema, it meets the baseline but doesn't compensate for the coverage gap.

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 text query. Returns ranked results.' It specifies the verb ('search') and resource ('memories'), and mentions the output behavior ('ranked results'). However, it doesn't explicitly differentiate from sibling tools like 'list_memories' or 'recall_memory', which prevents a perfect score.

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?

The description provides no guidance on when to use this tool versus alternatives. With multiple sibling tools like 'list_memories', 'recall_memory', and 'memory_conflicts', there's no indication of when this search function is preferred, what its scope is, or any prerequisites for use.

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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