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search_memory

Read-only

Search team knowledge to recall past decisions, patterns, and discussions before proposing architecture or making changes.

Instructions

Search team knowledge before proposing architecture, creating files, refactoring, or answering "how should we..." questions.

Also search when the user says: "we decided", "last time", "previously", "remember when", "what's our pattern for".

Returns compact index (~30 tokens/result). Use get_memories to fetch full content for relevant IDs only (not all results). Optionally filter by repo name, agent_id, and/or date range (after/before as ISO 8601 strings, e.g. "2025-01-01").

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
queryYes
top_kNo
repoNo
agent_idNo
afterNo
beforeNo

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault
resultYes
Behavior4/5

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

Annotations already indicate read-only and non-destructive. Description adds that it returns compact index (~30 tokens/result) and recommends get_memories for full content, providing useful behavioral context beyond annotations.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Conciseness4/5

Is the description appropriately sized, front-loaded, and free of redundancy?

Description is front-loaded with primary use case and well-structured, though slightly verbose. Every sentence adds value.

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

Completeness5/5

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

Given presence of output schema, description covers when to use, what it returns, and optional filters. Sibling tools are listed. Complete for its purpose.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Parameters4/5

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

Schema coverage is 0%, but description explains optional parameters (repo, agent_id, after, before) with format example. query and top_k are not described, but top_k has default in schema. Overall compensates well for low 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 tool searches team knowledge and specifies use cases like before proposing architecture or when user says 'we decided'. It distinguishes from siblings by recommending get_memories for full content.

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?

Explicitly tells when to use (before creating files, refactoring, etc.) and when not to (use get_memories for full content). Also provides optional filter guidance.

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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