An ad block list API needs to tell clients what a rule means, which evidence supports it, and how to recover when an update goes wrong. Returning a collection of domain names is only one part of that contract. This guide proposes an architecture for teams designing their own service, from a small internal feed to a more demanding distribution system. The endpoints and record shapes discussed here are design examples. AdBlockList.com provides educational guidance; this article does not describe an available commercial API.
Define the consumer before the response format
Start with the component that will enforce the rules. A network resolver needs a different representation from a browser extension. A review dashboard needs evidence and revision history that an enforcement engine may never use. Write down the clients, their supported syntax, their update method, and the maximum delay they can tolerate after a correction.
Next, define the decision a record is allowed to express. Does it recommend blocking one hostname, a hostname and its descendants, a request path, or a visible element? Those choices affect both coverage and breakage. Avoid a general pattern field unless another field unambiguously declares its language. Our comparison of domain lists and browser rules explains why the enforcement layer belongs in this early discussion.
Choose one initial use case and build its complete lifecycle. A single well documented export with a working correction process is a stronger foundation than several loosely specified formats.
Separate evidence records from enforcement exports
Use a canonical record to preserve why a recommendation exists. Include a stable identifier, the target, an explicit match scope, a category, the evidence date, and a review state. Keep the original observation distinguishable from the latest reviewer decision. An observation can remain historically useful after the resulting rule has been withdrawn.
Generate consumer exports from these records. A compact domain export might include only approved hostname rules. A browser export can include syntax specific to its documented target engine. A review export can retain explanations and provenance. Produce all exports from the same approved release so a support engineer can trace a downloaded line back to the decision that created it.
| Field | Proposed purpose | Question it should answer |
|---|---|---|
rule_id | Stable identity | Which decision is being corrected? |
match_scope | Explicit interpretation | Does the target include subdomains? |
observed_at | Evidence age | When was the behavior observed? |
review_state | Publication eligibility | Has the recommendation been approved? |
Document normalization separately. Specify treatment of case, trailing dots, internationalized names, duplicate entries, and invalid input. Keep rejected records in a review report, with reasons, so silent cleanup does not conceal recurring upstream problems.
Version the contract, the content, and the policy
Keep three identifiers distinct. A schema version describes the response structure. A release identifier selects a particular set of records. A policy version records the criteria used to include or exclude entries. Updating a hostname should not require a schema migration; changing what a category means deserves a visible policy change.
Make published releases immutable. When a mistake is found, publish a corrected release and identify the one it supersedes. Retain enough history to reproduce a reported incident. If a client says a checkout failed yesterday, support needs the exact active release, including local exceptions, rather than a guess based on the current list.
For paginated responses, bind the cursor to a release. Otherwise, entries added during a download can move page boundaries and leave the client with a mixture. A complete snapshot file is often easier to reason about for the first implementation.
Add incremental updates after recovery works
If full downloads become too costly, design an incremental update with an explicit base release and target release. Represent removals as carefully as additions. Have the client verify that its active base matches the update's expected base before applying any changes. If it does not match, offer a complete snapshot as the documented recovery path.
Specify what happens if an update is delivered twice, arrives out of order, or stops halfway through. Apply it to a candidate copy and validate the resulting release before activation. Retain fixtures for those cases alongside examples of ordinary updates. These exercises make the contract reviewable and give client authors something concrete to implement against. Avoid removing the full snapshot route merely because most clients normally use smaller updates; it remains useful for onboarding, repairs, and independent verification of reconstructed content.
Use ordinary HTTP mechanisms for efficient downloads
For a stable download URL, return an entity tag and let clients send it in If-None-Match on later GET requests. When the stored representation matches, the server can respond with 304 Not Modified. The authoritative details are in RFC 9110's conditional request specification. Keep this cache validation behavior distinct from the application's release approval checks.
Document which representation each validator identifies. A plain domain file and a richer JSON response need their own identity. Test caching through the actual distribution path, including any intermediary, so the client receives the intended content and metadata together.
Suggest an update interval appropriate to the feed's purpose, with randomized scheduling to spread requests. Give clients a bounded retry strategy and a clear response to temporary failure. An unavailable endpoint should not quietly translate into an empty active list.
Treat activation as a separate step
Download into temporary storage. Check response status, expected format, size limits, and any release integrity information before parsing. Validate every record against the declared schema and target syntax. Reject unsupported required features explicitly. Logging a warning while activating an incomplete interpretation makes later failures difficult to diagnose.
Then compare the candidate with the current release. Flag surprising deletions, a large change in target scope, or an unexpected category appearing in a narrowly configured feed. These are review prompts whose limits should come from your own normal release history. A large change can be legitimate, but it deserves an explanation before automated activation.
Compile the candidate into the consumer's representation and run a small set of representative checks. Activate it only after all required checks pass, using a mechanism that keeps clients from observing a half written file. Retain the previous accepted version. Record download time, activation time, and release identity separately so freshness reports describe what is actually running.
Make corrections and stale data visible
Build removal and exception workflows alongside additions. A mistaken block deserves an addressable report, a reproducible example, and a way to trace the correction into a later release. Expose a concise change log that identifies withdrawn rules and meaningful scope changes. Clients should not have to compare unexplained files to discover why a service started working again.
Define how long a client may retain its last accepted release after download failures. The right choice depends on the consumer's purpose. Have the client report the stale state and follow an explicit local policy. Avoid claiming that a successful scheduled request proves freshness; the server may still be offering the same old data.
If local exceptions are allowed, keep them outside the downloaded file and document precedence. Include an owner and review date for each exception. This lets a corrected upstream release arrive without erasing a deliberate local decision.
Observe quality without collecting browsing history
For operational monitoring, begin with release identifiers, download outcomes, parser failures, and activation status. Collect only the information needed to diagnose those functions. A list distribution service does not inherently need a record of every page a user visits.
When a breakage report needs a request sample, ask for a minimal reproduction and provide redaction guidance. Remove account tokens and sensitive query parameters before sharing evidence with maintainers. In test environments, use controlled accounts and fixtures wherever practical.
Track quality beyond uptime: unreviewed corrections, unexplained scope changes, and failed client compilations can reveal problems that successful HTTP responses hide. The API planning guide and AI scoring overview can help teams separate delivery reliability from confidence in individual classification decisions.
Build a contract you can support
A useful first release has explicit semantics, reproducible exports, conditional downloads, and a documented recovery path. Before adding more endpoints, rehearse a malformed update, a withdrawn rule, an unavailable server, and a client that has missed several releases. Each rehearsal should end with a known active state and an explanation an operator can understand. That is the practical standard for an API whose data changes the behavior of other software.
