memory_write

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

Annotations cover readOnlyHint=false, openWorldHint=true, etc., but the description adds crucial behavioral detail: 'an importance gate may filter low-value writes, so the result tells you whether the memory was stored or filtered.' It also sets content standards (self-contained statement) and security boundaries, going well beyond the structured metadata.

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 longer than typical but every sentence carries meaningful instruction: proactive triggers, prohibited content, behavior note, and content formatting. It is front-loaded with the core purpose and uses a clear 'Behavior:' section. Slightly verbose, but no wasted words.

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 a write tool with no output schema, the description sufficiently covers return behavior ('result tells you whether the memory was stored or filtered') and usage constraints. It addresses cross-session/cross-tool persistence, importance filtering, and content quality—making the description complete for the tool's complexity.

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 all three parameters are described. The description adds semantic guidance on how to format `content` ('self-contained statement that still makes sense when recalled out of context'), which supplements the schema examples. This extra nuance improves parameter understanding beyond the schema alone.

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 a specific verb and resource: 'Store a long-term memory that persists across sessions AND across every AI tool.' It distinguishes from siblings by emphasizing cross-tool persistence and proactive recall, which sets it apart from memory_read or memory_list_recent.

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?

Explicit when-to-use guidance is provided: 'Call this PROACTIVELY the moment the user states a preference, makes a decision, or you learn a durable fact.' It also lists exclusions ('Never store passwords... skip transient chatter') and instructs not to wait to be asked, giving clear context for when to use this vs. other memory tools.

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