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memory_condense

Condense old memories using agent-generated summaries while preserving original content for restoration. Ideal after consolidation reports flag candidates.

Instructions

Apply agent-generated summaries to condense old memories. Preserves original content for later restoration. Use after consolidation reports flag condensation candidates.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
memoriesYesBatch of memories with agent-generated summaries
target_levelNoTarget condensation levelsummary
Behavior4/5

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

The description adds important behavioral detail: 'Preserves original content for later restoration.' This goes beyond the minimal annotations (only title and openWorldHint=false) by clarifying the non-destructive nature of the operation. It also mentions that it is for old memories and after consolidation reports, providing context.

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 two sentences with no wasted words. The first sentence clearly states the primary action, and the second adds important context. It is front-loaded and efficient.

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?

For a tool with 2 well-documented parameters and no output schema, the description covers the core purpose, usage trigger, and a key behavioral aspect (preservation). It is sufficiently complete for an agent to understand when and how to use it, though it omits potential return values or error states.

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?

The input schema has 100% coverage, with detailed descriptions for all parameters including the batch structure and target_level enum. The tool description does not add significant new meaning beyond summarizing what the schema already states, so a baseline score of 3 is appropriate.

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 indicates the tool applies agent-generated summaries to condense old memories, with the specific verb 'condense' and resource 'old memories'. It also distinguishes itself by noting it preserves original content for later restoration, setting it apart from destructive operations like memory_delete.

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?

The description provides explicit guidance: 'Use after consolidation reports flag condensation candidates.' This clearly indicates when to use the tool. However, it does not explicitly list alternatives or when not to use it, though the context implies it is for condensing rather than other operations.

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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