memory_write

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

With no annotations, the description carries the full burden, and it does disclose genuine behavior: the write persists across sessions and is visible to any connected AI tool, which materially raises the stakes of a bad write. It is silent on duplicate handling, overwrite/replace semantics, whether the write can be revoked, and what confirmation comes back — significant gaps for an irreversible-looking mutation.

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, no filler, with the core action front-loaded and the usage criterion following immediately. Every clause earns its place by adding either scope or selection guidance.

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 four-parameter, one-required write tool with fully documented schema and no output schema, the description covers purpose, target content, and cross-session effect well enough to call it correctly. The only real remaining gap is write semantics — duplicate handling and what is returned on success — which a mutation tool without annotations ideally would state.

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 all four parameters are already documented, including the type enum values and the required content. The description's example categories loosely mirror the type enum and hint at what content should look like (durable, specific facts), but add nothing about tag syntax, project scoping, or defaults beyond the schema. Baseline 3 applies.

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?

States a specific verb (store) and resource (item into shared memory) plus the downstream purpose (retrievable in future sessions and by other connected AI tools). Against siblings memory_search and memory_stats, this is unmistakably the write counterpart, so an agent can select it without opening schemas.

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?

"Use it for durable facts" gives an explicit positive selection criterion, reinforced by the enumerated categories (decisions, discoveries, insights, user preferences). It never states what should NOT be stored (transient chatter, secrets) or points to memory_search as the retrieval partner, so exclusions and named alternatives are absent.

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