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memory_context

Generates a compressed context summary that combines top L4 and L3 memories, recent interactions, and wiki content to support prompt injection management.

Instructions

Return compressed context summary for prompt injection (L4 top-10 + L3 top-3 + recent + wiki).

Args: layer: "user" or "agent" user_id: User identifier

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
layerNouser
user_idNodefault
Behavior2/5

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

No annotations provided, so description must disclose behavior. It states 'Return compressed context summary' (read-only implication) but omits any side effects, permissions, or cost implications. No mention of whether context is snapshot or live.

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?

One sentence plus two parameter lines. No wasted words, front-loaded with purpose. Efficient and clear.

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?

Despite conciseness, the description lacks details about return format, what 'compressed context' entails, or how the output should be used. Without output schema or annotations, this leaves the agent underinformed.

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 has 0% description coverage. Description clarifies that 'layer' is expected to be 'user' or 'agent' (implicit enum values) and that 'user_id' is a user identifier. This adds some value but does not explain the meaning of each layer or format of user_id.

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?

Description clearly states the tool returns a compressed context summary for prompt injection, specifying components: 'L4 top-10 + L3 top-3 + recent + wiki'. Verb+resource is specific, and it distinguishes from siblings like memory_context_inject.

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 on when to use this tool versus alternatives like memory_recall or memory_data. The description only mentions 'for prompt injection' without explaining prerequisites or exclusion criteria.

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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