docs: Improve documentation to contribute benchmarks for beginner and advanced ado users

[mgazz]

Different readers will approach the documentation with varying requirements and levels of familiarity with ADO. This makes it difficult to provide a single set of ADO commands that suits every use case. Below are two common scenarios and possible approaches:

Case 1 - Readers already familiar with ADO: These users are typically capable of configuring and validating their own benchmarks. For this audience, a brief reminder together with a link to the ADO documentation should be sufficient.
Case 2 - Readers with no prior ADO experience: For users new to both Nexus and ADO:

• The project already provides examples that can serve as a starting point (for example, the Random Walk example: https://ibm.github.io/ado/examples/random-walk/).
• If an example is added to the Nexus project, it should be fully self-contained and executable from start to finish, allowing users to reproduce the workflow

algorithm-nexus/docs/contributing/add_benchmark.md

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	## Step 4: Run the benchmark
	Install the benchmark package and run the benchmark instance locally using the
	`ado` CLI. First save the following operation configuration to a file `op.yaml`.
	It will execute the experiment on all points in your space.
	```yaml
	metadata:
	name: randomwalk-all
	spaces:
	- dynamically_inserted
	operation:
	module:
	operatorName: random_walk
	operationType: search
	parameters:
	numberEntities: all
	samplerConfig:
	samplerType: generator
	mode: random
	```
	Then,
	```bash
	uv pip install packages/<package-name>/benchmark_packages/<experiment-package-name>
	ado create space -f <space-yaml-path>
	ado create operation -f op.yaml --use-latest space
	```

Done when:

• the page describes only commands that terminate with success
• (optional) If deemed necessary, the documentation provides a working example of how to create a benchmark where all commands work start to finish. This could reuse example from from ado if suitable