更新用户认知记忆

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

Beyond annotations, the description discloses key behavioral details: the operation is a partial update, returns an error when the memory is missing, and returns the full updated entry or null. This adds meaningful context without contradicting the idempotentHint annotation.

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?

The description is compact and well-structured, with a clear opening statement followed by Args and Returns sections. The Args list is slightly redundant with the schema, but the Returns section is essential since no output schema exists.

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?

For an 8-parameter mutation tool with no output schema, the description covers the essential contract: update behavior, error case, return shape, and updatable fields. It could go further with an example, but nothing critical is missing.

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 coverage is 100%, so the baseline is 3. The description adds value by clarifying partial-update semantics (only provided fields are updated) and by pointing out that memory_id can be sourced from cognitive_search/cognitive_list.

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 states a precise operation—partial update of an existing memory—and explicitly notes the error case when the memory is not found. This clearly distinguishes it from sibling tools like cognitive_write or cognitive_forget.

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 clearly implies this tool is for updating an already-existing memory, and even tells the agent where to obtain the memory_id (cognitive_search / cognitive_list). However, it does not explicitly state when to prefer this over cognitive_write or avoid using it for creation.

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