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dedsxc
by dedsxc

search_memory

Search long-term memory for entries relevant to a query, recalling what was learned in earlier sessions to provide context for the current task.

Instructions

Search long-term memory for entries relevant to a query.

Call this at the start of a task (or whenever prior context would help) to recall what was learned in earlier sessions.

The memory bucket is determined automatically from your authenticated identity; you cannot and need not specify whose memory to read.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
limitNoMaximum number of memories to return (default from config).
queryYesNatural-language description of what to recall.

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault
resultYes
Behavior4/5

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

With no annotations, the description carries the burden. It discloses that memory bucket is auto-determined from authenticated identity and cannot be specified, adding important behavioral context. It implies a read-only operation through the verb 'search', though it does not explicitly state that no modifications occur. This is sufficient for a search tool.

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?

Three concise, well-structured sentences. The purpose is front-loaded, usage guidance follows, and the identity constraint is clearly stated. No verbose or redundant language.

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?

The tool is simple with full schema coverage and an output schema, so the description need not explain return values. It covers purpose, usage timing, and a key identity constraint. It could have briefly mentioned strategies for effective queries, but overall it is complete for the tool's 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?

Schema description coverage is 100%, with query and limit already described in the schema. The description adds no additional parameter-level detail, so the baseline of 3 is appropriate. The auto-bucket note clarifies that no identity parameter is needed, but that is a behavioral clarification rather than parameter semantics.

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 opens with a clear verb+resource statement: 'Search long-term memory for entries relevant to a query.' It specifically focuses on recall from earlier sessions, distinguishing it from sibling tools like add_memory, list_memories, and delete_memory.

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?

Explicitly states when to use: 'Call this at the start of a task (or whenever prior context would help) to recall what was learned in earlier sessions.' It provides clear context but does not explicitly name alternatives or when-not-to-use scenarios, such as using list_memories for browsing without a query.

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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