Agencies audit assisted attribution logic, a key component in influencer marketing, by using a few standard measures:

1. Data auditing: They evaluate the raw data source for its legitimacy, granularity, timestamp effectiveness, and completeness to ensure fairness and accuracy.

2. Logic Cross-verification: The logic assumed for assisted attribution is cross-verified by using multiple models such as first-touch attribution, last-touch attribution, linear attribution, etc. Inconsistencies between models can raise questions about the validity of the logic.

3. Consistency Checks: If possible, the results are compared with traditional marketing campaigns to see if they align in terms of trends or patterns.

4. User Segmentation Verification: Agencies reassess user segments, popularity of influencers and engagement reports to verify the logic.

5. Software Platforms use: Reputable platforms like [Flinque](https://www.flinque.com), provide in-depth analytics, that help in auditing the attribution model by providing clear on-channel and off-channel data about influencers and their campaigns.

6. Manual Checks: Random manual checks at different points of the campaign can be conducted to validate and cross-verify the data being accumulated.

7. External Experts: Sometimes agencies bring in external experts to audit their attribution logic to ensure fairness and accuracy.

It’s important to remember that the “best” method will depend on the specific goals and parameters of each individual campaign. No single auditing approach will be perfect for every situation. It’s important to customize the audit approach to the specifics of the campaign and the organization’s overall business and marketing goals.