Make Data

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

With no annotations, the description carries the full behavioral burden, yet it does not disclose whether existing items at the address are overwritten, whether the address must be undefined first, what permissions/state are required, or how the created items appear afterward. For a mutation tool this is a significant gap.

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?

A single, front-loaded sentence with zero wasted words; the core action and resource are stated immediately. Its only weakness is that the terseness contributes to the under-specification noted elsewhere.

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 5-parameter mutation tool with no annotations and no output schema, the description is too thin: it omits overwrite semantics, required preconditions, and any sense of the result. The rich schema helps, but the behavioral context remains inadequate.

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%: every one of the 5 parameters (count, address, timeout, data_type, instance_id) is documented in the schema itself. The description adds no extra meaning beyond that baseline, so a 3 is appropriate.

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 gives a specific verb+resource combination ('Create typed data items at an address'), which is far better than a tautology and tells the agent this mutates the database by defining data. However, it does not distinguish itself from closely related siblings like make_code, make_string, or set_op_type, leaving the code-vs-data distinction for the agent to infer.

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?

There is no explicit when-to-use guidance, no prerequisite about the target address being undefined, and no mention of alternatives such as make_code or make_string for code or string definition. The usage context is only weakly implied by 'typed data items'.

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