Smart Jobs

A Smart Popular job starts with a provider’s popular movies or shows. It then gives titles with more votes a lower minimum rating and asks titles with fewer votes to meet a higher one. Choose it when you want mainstream hits to have an easier path into your library.

For a fixed rule such as “science-fiction rated at least 6,” use a regular Popular job. Smart Popular is optional; you do not need it to automate discovery.

Create your first Smart Popular job

First connect a discovery provider and a delivery service using the quickstart. Start with BLOCKBUSTERR_DRY_RUN=true: custom jobs are enabled on creation and can execute before you finish tuning them.

1. Open Rules and create a Movie rule set from Empty rule set. Name it Smart mainstream movies.
2. Under Boundaries, set a minimum of 100 votes as a starting point. Save. This excludes very small audience samples; it is a preference, not a guarantee of quality.
3. Open Jobs → New job → Custom Job.
4. Name the job Popular with a flexible rating, choose Smart Popular, Movie, and TMDB.
5. Assign Smart mainstream movies. Set Discovery limit to 100, Job delivery cap to 5, Base Minimum Rating to 6.5, and Adjustment Factor to 2.
6. Create the job, disable it while tuning, open its editor, and expand Delivery & schedule. Set Custom Sync Interval to 24h and choose the delivery mode you configured.
7. Save and Preview. Read the rating decisions for both accepted and rejected titles. Restore normal delivery after reviewing all enabled jobs, then enable this job when ready.

TMDB is one supported source; Trakt and Simkl also support Smart Popular when configured. The rating and vote data come from the source, so switching providers can change the decisions.

What those numbers mean

Popularity here means vote-count rank within the candidates fetched for this run. It is not box-office revenue, critic acclaim, or an absolute popularity threshold across the provider’s entire catalog.

With a baseline of 6.5 and adjustment factor of 2:

Position by vote count in this batch	Required rating
Fewest votes	7.5
Middle	6.5
Most votes	5.5

The calculation is baseline - (percentile - 0.5) × adjustment factor, rounded to one decimal place and limited to 0–10. A batch containing only one title uses the baseline. Changing the discovery limit can change a title’s position and therefore its threshold.

Raising the factor widens the gap between the least-voted and most-voted titles. Raising the baseline makes the whole job stricter. Use a regular Popular job for a fixed rating threshold: in the current Smart Popular implementation, an adjustment factor of 0 falls back to 0.5, and a baseline of 0 falls back to 6.

How Smart Popular interacts with rules

The adaptive threshold replaces the assigned rule set’s minimum-rating boundary for this job. A separate minimum rating of 8 in that rule set does not impose an additional floor of 8. The saved rule set itself is not changed.

Other rules still apply: minimum votes, required genres, languages, years, runtime, content ratings, and title exceptions. Allow overrides and universal title exceptions retain their normal behavior; see Rules before using them to bypass checks.

For example, add required genre science-fiction to make the previous job accept only science-fiction candidates. A widely voted action film with no matching genre still fails. Use Required matches, not Allow overrides, when the genre must be mandatory.

Smart filtering versus ranked selection

Smart Popular determines whether a title passes its adaptive rating check. Ranked selection compares qualifying candidates across participating jobs and chooses winners for a shared cycle. They are different settings and can be used together.

Neither setting discovers films outside the fetched source results. A little-known indie film absent from the popular chart never reaches the adaptive check. An audience score of 8.7 also does not mean critics awarded it 8.7; use a curated source when critic selection is the actual requirement.

Tune one thing at a time

What the preview shows	Change to try
Too many weak mainstream titles pass	Raise the baseline or reduce the adjustment factor
Low-vote titles dominate	Raise minimum votes in the assigned rules
Nothing passes	Read rejection reasons; a genre, language, or vote rule may be responsible
A desired title never appears	Check the source and discovery limit before relaxing rules
Too many titles would be delivered	Lower the job delivery cap; keep discovery broad enough to find matches

After enabling, use Activity → Job Runs to inspect each execution and Activity Entries to understand an individual title. Preview again after changing the provider, limits, or rules.