A team has a useful C# calculation, a passing build, and an assistant that has helped with the implementation. Another team now wants to use it. Their first experience will be restoring a package, calling its public API, and deciding whether the result means what they expect.
That handoff changes the review. The consumer may have a different application, framework target, dependency graph, or release schedule. They will not necessarily have the producer's solution open or the conversation that explained why an empty value behaves a particular way.
AI can help prepare the package, inspect a public surface, and write a consumer example. The release still needs evidence from the path the other team will actually use. A small, independent consumer makes that path inspectable.
Start with the consumer's job
Use the fictional measurement summary from the companion article. The consuming application needs to distinguish two observed readings and one missing reading from three observed readings. For 2, missing, and 4, it expects a mean of 3.
That behavior belongs in the handoff because the type declarations alone cannot explain every meaningful choice. The consumer also needs to know what an entirely missing collection returns, which inputs are rejected, and which framework the package targets.
Write a short usage example before making the release process elaborate. It reveals whether the public API gives the consumer enough information to complete the task. A type that returns only a mean may force the consumer to reconstruct coverage that the library already knew.
Make the package a real input to verification
Microsoft documents that dotnet pack produces a NuGet package from a project. That artifact becomes the input to the consumer check in this example.
For a library using the measurement calculation, package validation can be enabled in its project configuration:
<PropertyGroup>
<EnablePackageValidation>true</EnablePackageValidation>
</PropertyGroup>Package validation is enabled. This first-version example has no earlier release baseline, so it does not demonstrate backward compatibility with a previous release. That distinction should remain visible in a real release record as well.
An assistant can draft the project file and commands, but review the actual package contents and dependency declarations. A file that happens to be present in the producer's working directory is not automatically available to a consumer.
Give the consumer only its declared dependencies
The consumer project references the package by ID and version. It has no project reference to the library:
<ItemGroup>
<PackageReference Include="Example.Measurements" Version="1.0.0" />
</ItemGroup>Check the handoff from a separate consuming application. Restore the candidate package through the intended feed and verify the resolved dependency. An isolated package directory can help reveal assumptions hidden by a development cache. A short consuming check can then exercise the public behavior:
using Editorial.Measurements;
var actual = MeasurementMath.Summarize([2m, null, 4m]);
var expected = new MeasurementSummary(2, 1, 3m);
if (actual != expected)
throw new InvalidOperationException(
$"Consumer expected {expected}; received {actual}.");
Console.WriteLine("PASS: the installed package preserves missing values.");The expected result is specified independently of the library. If missing readings enter the denominator, the assertion fails even though the method can still be called successfully.
This creates useful evidence for a narrow statement: this consuming program restored the candidate package and observed the required behavior in the checked setting. It does not establish every consumer, target framework, or deployment environment.
Separate API compatibility from behavior
A library can keep the same public method and still return a result with a changed meaning. It can also introduce a source or binary incompatibility that prevents a caller from using the method at all.
Microsoft's breaking-change guidance distinguishes these categories, including behavior changes that affect consumers. A release review needs to identify which commitments changed rather than summarize everything as a successful compilation.
For the measurement library, a change that counts missing values as observed zeros can leave the public declarations unchanged. The consuming program still compiles, but its expected counts and mean disagree with the candidate's output.
Versioning should communicate the supported contract. A version label cannot establish compatibility by itself. Keep the migration question specific: which callers are affected, what assumptions need revisiting, and what evidence supports accepting the change?
Use package validation for the checks it provides
.NET package validation provides validators for a prior baseline, compatible runtime assets, and compatible framework assets. The checks depend on the package and configuration supplied.
For an existing package, choose and retain the intended prior baseline. For a package with several framework or runtime assets, verify the supported combinations. A blanket green result is hard to interpret when nobody can explain which comparison ran.
Behavior still needs its own evidence. The tooling cannot infer that the person reading a measurement summary needs missing values to remain distinguishable from zero. A consuming example and domain review address questions outside a public-API comparison.
Check the framework you promise to support
The example library and consumer target net10.0. A target framework selects an API surface; Microsoft's framework documentation explains how those targets are declared.
An application targeting a different framework is a separate compatibility question. Adding targets can require additional references, conditional implementation, and tests. Choose them from actual consumer needs and verify the combinations the package claims to support.
The same principle applies to configuration and optional integrations. A small pure calculation may need little setup, while a library with storage, network clients, or dependency injection needs a useful startup example. Check that the consumer can configure the intended capability using the package's public surface.
Ask AI to examine the consumer's view of the API as part of review. It can identify an undocumented dependency or confusing usage pattern. Verify the concern by changing or running the consumer, so the review remains attached to something another developer can reproduce.
Demonstrate that a meaningful mistake is caught
A useful negative control changes the local library so a missing reading increases the observed count. Pack that deliberately wrong implementation as a separate candidate, then run the same consuming expectation against it.
The candidate package builds, but the consumer must reject its behavior. This establishes that this particular requirement is checked through the package path. It is not a claim that every possible breaking change will be detected.
Keep that experiment separate from a real release, using a local candidate feed or another disposable setup. Its purpose is to establish whether the check detects the selected mistake. Restore the intended implementation before assessing a release candidate.
Leave the next team an understandable release
A useful release handoff names the candidate package, supported targets, required configuration, behavior commitments, checks performed, and changes the consumer may need to make. Link that account to the actual artifact the team will install.
Keep code-review claims narrow enough to assess. “The package restores and these examples pass” is useful evidence. A larger compatibility claim needs the appropriate baseline, consumers, and environment checks behind it.
AI-assisted development can carry a change through this whole path: shaping the API, implementing a bounded behavior, drafting examples, and investigating failed consumer checks. The resulting package should leave another team able to understand what it promises and verify the part their application depends on.
Protabyte works with teams building shared .NET libraries and product platforms. Talk with us about a package boundary, consumer integration, or release your team needs to make easier to verify.