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

Annotations already cover read-only, idempotent, non-destructive and open-world, so the description is not obligated to repeat them. It instead adds genuinely new behavior: an 'Owner or admin only' authorization requirement, the empty-list case ('Returns [] for sources that do not support mapping'), and the incident rationale for why name-based inference was removed. It does not describe the item shape of the returned list, which is the remaining 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?

The purpose is front-loaded, then the human-in-the-loop directive, then the anti-inference warning with its justification, then the edge case and permission note. Every sentence earns its place. The all-caps warning is loud and slightly bulky, but it is load-bearing given the described silent-failure incident.

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 three-parameter, fully documented read tool with rich annotations and no output schema, the description covers authorization, the empty-result case, and the required human interaction. It stops short only of describing the shape of each returned column entry, which an agent needs in order to pose the column-by-column question well.

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%: auth, source and targetRef are each documented, including provenance ('authFields from list_import_sources', 'id from list_import_targets'). The description adds no parameter-level meaning beyond what the schema already says, so the 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?

The description states the resource concretely: 'The chosen target's columns, so each one can be mapped to a Retasc status,' which tells an agent exactly what is returned and why. It implicitly distinguishes itself from list_import_sources and list_import_targets by referring to the chosen target. The only weakness is that the noun-phrase opening never names the verb 'list', and the tool name ('list_import_statuses') mismatches the title and body ('columns'), which creates a moment of ambiguity.

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?

It gives an explicit downstream procedure: relay the list to the human and ask column by column, and explicitly forbids inferring the mapping from column names. That is strong 'how and when' guidance tied to the import workflow. What is missing is an explicit sequencing statement (call after list_import_targets, before run_import) and any exclusion of alternatives.

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