list_application_provenance

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

Annotations already declare readOnlyHint, openWorldHint, and idempotentHint, so the safety profile is covered. The description adds useful behavioral context by explaining that classification is based on appOwnerOrganizationId rather than name heuristics, and by defining the provenance values. It does not describe output format or pagination, but that is a minor gap given the annotations.

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 distinction, then gives the authoritative classification detail, the provenance values, and finally example questions. Every section earns its place and there is no wasted wording.

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 simple read-only list tool with three optional parameters, the description covers purpose, classification logic, parameter values, and example queries. It does not explicitly state the return shape, but with no output schema present, a slightly more explicit note about the returned list would improve completeness.

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?

The schema has 0% description coverage, but the description fully explains the key provenance parameter with its five allowed values and their meanings. The limit and include_managed_identities parameters are not elaborated, though their names and defaults make their semantics reasonably clear.

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 clearly states the tool's purpose: to differentiate app registrations created by users in the tenant from Microsoft first-party apps and third-party consented apps. It also names the authoritative classification signal (appOwnerOrganizationId) and provides concrete example questions, making the purpose specific and distinguishable from siblings.

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 explicit usage context with example questions like 'Quais aplicações foram criadas pelos usuários?' and states it is for distinguishing provenance types. However, it does not explicitly mention when not to use it or contrast it with the sibling summarize_application_provenance tool.

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