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search_agent_memory

Search stored agent learnings, mistake autopsies, and project rules by keyword to retrieve relevant context.

Instructions

Searches through learned preferences, mistake autopsies, and scouted project rules by keyword.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
queryYesSearch keyword or topic query
Behavior3/5

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 implies a read-only operation through 'Searches', but doesn't explicitly state that no modifications occur. It also doesn't disclose any specifics about result format, pagination, or rate limits. The description is minimally transparent but doesn't contradict anything.

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 a single, efficient sentence that states the essential information with zero filler. The content types are listed right after the verb, making it scannable and easy to parse for an agent.

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?

For a one-parameter search tool, the description covers the core function well but omits details about the return value or how results are presented. Since there is no output schema, the description should at least hint at what the agent can expect back (e.g., matching memories). This is a notable gap that leaves some ambiguity.

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?

With 100% schema description coverage, the schema already documents the single parameter 'query' as 'Search keyword or topic query'. The tool description adds no additional detail about accepted formats or behaviors beyond what the schema provides, so it meets the baseline but doesn't exceed it.

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 a verb ('Searches'), a resource ('learned preferences, mistake autopsies, and scouted project rules'), and the method ('by keyword'). It names three specific memory categories, which distinguishes it from generic memory retrieval tools like get_agent_memory. However, it doesn't explicitly compare it to any sibling, so it lacks strong differentiation.

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?

No guidance is provided on when to use this tool versus alternatives like get_agent_memory or log_user_preference. There is no mention of prerequisites, recommended use cases, or exclusions. The agent must infer usage from the name and description alone.

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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