zerodb_store_memory

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

No annotations are provided, so the description must carry the behavioral burden. It does disclose some behaviors: automatic importance scoring, embedding, multi-session tracking, and decay. However, it does not mention side effects like whether writes are idempotent, whether existing memories are overwritten, or what output/confirmation is returned.

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 two concise sentences, front-loaded with the core purpose, and each sentence adds value without redundancy. It is appropriately sized for the tool's complexity.

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?

With no output schema and no annotations, the description should explain what happens after storage, including return values or how to reference memories later. It covers key behaviors but omits practical details like confirmation or error scenarios, leaving the agent with some ambiguity.

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 parameters are already well-documented with descriptions and defaults. The tool description adds no parameter-specific guidance beyond what the schema already provides, so the baseline of 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?

The description uses a specific verb ('Store') and resource ('conversation context in agent memory'), and adds distinctive details like 'automatic importance scoring and embedding'. It clearly differentiates from sibling tools like search_memory and semantic_search.

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 implies usage through 'Store conversation context' and mentions 'multi-session tracking and memory decay', but it does not explicitly state when to use this vs alternatives or provide exclusions. No comparison with sibling tools is offered.

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