clone_table

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

With no annotations, the description carries the disclosure burden, and it does disclose the key behavioral traits: zero-copy semantics, point-in-time behavior, the 30-day retention window, and default to current state when `at` is omitted. It does not cover permissions or failure behavior, but the essential operational traits are present.

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 front-loaded with the core purpose, followed by the essential platform caveat and an Arg list that uses compact line-per-parameter formatting. No wasted words; the structure makes scanning easy.

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?

The description covers purpose, platform restriction, and all parameter semantics, and an output schema exists so return values need not be described. It omits edge-case behavior such as whether `new_table` must not already exist, but the overall calling context is sufficiently complete.

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 0%, but the Args block fully compensates: workspace/item are clarified as name or GUID, source/new_table get qualified-name examples, and `at` gets an ISO-8601 format, a retention-window constraint, and default behavior. This is more useful than a typical schema description.

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 opening line names a specific operation ('Create a zero-copy clone of a table') and the exact SQL construct used (`CREATE TABLE … AS CLONE OF …`). This clearly separates it from sibling table tools like create_table or create_empty_table, even without naming them.

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 gives a clear platform constraint ('Only supported on Fabric Data Warehouses (not SQL Analytics Endpoints)'), which helps an agent avoid misuse. However, it never explicitly directs when to choose clone_table over create_table/create_empty_table/import_table_from_url; the usage is implied by the 'zero-copy clone' wording.

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