get_context_brief

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 correctly implies the tool is read-only (synthesizing memories) and mentions pulling memories via top_k parameter, but does not disclose edge cases (e.g., behavior on unknown topics) or potential side effects. This is adequate for a simple read query.

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

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

Two sentences with no fluff: first sentence defines the function, second sentence provides usage guidance. Every word earns its place.

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

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

Given the tool's simplicity (two parameters, no output schema), the description explains the purpose and usage context well. It could mention output format, but not required since no output schema exists. Overall, it is nearly complete for an agent's decision-making.

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

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

Schema description coverage is 100%, so baseline is 3. The description adds examples for the topic parameter but does not elaborate on top_k beyond what the schema provides (default value). The schema itself is clear, so the description adds marginal value.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Does the description clearly state what the tool does and how it differs from similar tools?

The description clearly states it synthesizes a brief on a topic covering known information, evolution of thinking, and open questions, with concrete examples like 'web onboarding tests' and 'stock portfolio'. This is specific and distinguishes from sibling tools like search_memory which retrieves raw memories.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Does the description explain when to use this tool, when not to, or what alternatives exist?

The description advises 'Use before deep-diving into any recurring topic', providing clear context and intent. While it does not explicitly exclude use cases or name alternatives, the guidance is sufficient for an agent to understand when to invoke this tool.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.