Galxe quest platform integration: setting up quests and OAT

Why Galxe integration breaks on reward distribution

After integrating Galxe, a typical failure looks like this: a participant completed all steps of the quest campaign, saw the green checkmark — but there is no reward. The campaign owner sees a spike in activity at the start and almost empty reward distribution statistics.

The cause is almost never the contract itself: the pipeline breaks, where quest condition verification, completion recording, and reward distribution live at different stages and with different delays.

Condition verification reads not the action itself, but its confirmed state: an event in the required contract, balance at the snapshot moment, the fact of subscription or completion of an external task.

If a participant took a step a couple of minutes before the window closes, the network has not yet indexed the event — the task is marked as not completed, and such an address no longer enters the reward distribution queue.

The second point of loss is quest restrictions. Edition limit, one task per wallet, filtering out multi-accounts by a set of attributes, mint queue.

Without deduplication and repeatable distribution, the same address passes verification twice, while an honest participant hits an exhausted limit and leaves.

The cost of such a failure is not an error in the logs, but the loss of participants: a person who did not receive the reward on the first attempt will not participate in the next campaign. Below we analyze how this is closed.

What managed quest mechanics provide and how to measure them

Quest mechanics stop being manual work when reward distribution is tied to events on-chain and on the platform itself, rather than to operator actions.

On Galxe, this is assembled as follows: completion of a condition is recorded automatically, the reward is accrued by event, and disputed situations go into a separate queue with an action history. Then the mechanics are measured by four numbers.

The first is the share of automatic accruals. At campaign launch it stays around 60–70%: some tasks require manual verification — subscriptions, reports, off-chain activity.

After configuring rules and linking checks to data sources, the share rises above 95%, and manual operations remain only for exceptions.

The second is response time to a surge of participants. The rush comes in a wave: in an hour, as many requests arrive as would not accumulate during the day.

A layered accrual queue keeps processing without degradation — the reward response remains in minutes, not stretched over a day.

The third is the share of disputed cases and support load. A dispute almost always means a lack of traces: it is not visible whether the participant completed the condition and when.

An event log with time and wallet identifier turns the investigation into checking a single record, and the share of requests reaching manual review drops several times.

The fourth is campaign metrics: conversion from visit to completion, share of task chains completed to the end, drop-off between steps. They show not "how many came," but where the participant stopped — and this is a reason to change the conditions, not the budget.

Galxe integration: which connection modes to choose

The connection mode determines who gets the accounting of completed tasks and where the campaign traffic goes. In practice, the choice comes down to three schemes, and they are not interchangeable: each divides data between you and the Galxe platform in its own way.

A campaign on the platform side is a fast entry: the mechanics and audience are already assembled, but traffic goes to someone else's domain, and the platform changes task rules.

Your own quest module removes this: you determine what counts as completion, store accrual history, and configure anti-fraud protection.

A hybrid scheme with result mirroring covers both tasks: tasks run on the platform, while statuses and rewards are transferred to your dashboard.

What matters here is not the export, but regular reconciliation — a discrepancy of a couple of percent by the end of the campaign produces incorrect recipient lists.

We check the platform's limitations before launch: allowed task types, verification timelines, access to participant export — these most often determine whether your own module is needed.

Describe the task — we will return with an estimate and a plan for the chosen mode.

Work order: from campaign audit to settings handover

We start work by analyzing what is already configured: which campaigns are running in Galxe, how rewards are distributed, and where conditions are set manually. Then we build the route so that every rule is verifiable and acceptance does not turn into rework on live participants.

1. Audit of current scenarios — list of quests, reward types, and steps; we mark duplicates, overlaps by timing, and places where accrual depends on manual correction.
2. Quest data schema — entities and relationships: campaign, step, completion condition, reward, activity window, limit per participant; we mark which fields come from external systems.
3. Condition assembly — we translate requirements into verifiable rules: action threshold, step order, time limit, re-completion.
4. Test run on a small group — closed list of wallets and a run of all branches: completion, non-completion, repeat, cancellation, reward distribution.
5. Acceptance — we reconcile the accrual log with expected logic, check double distributions and correctness of participant statuses.
6. Settings handover and team training — access, campaign descriptions, and regulations: how to add a quest, change a condition, stop distribution.

After handover, your team launches new campaigns on its own — without coming back to us for every change.

What we hand over: configurations, schemas, regulations

A project is delivered not when the campaign has run, but when your team launches the next one without us. Therefore we hand over a set of artifacts — settings, structure descriptions, distribution procedure, and access rules, all next to the code, not in a chat.

• Campaign configurations — templates with default parameters: timelines, completion conditions, reward distribution, limits per participant. New activity is assembled by editing a template, not from scratch.
• Data schemas — how profile, wallet, task event, and reward distribution record are linked; which fields are required, where participant uniqueness is checked.
• Distribution regulations — when accrual happens automatically, how long it waits for confirmation, how disputed cases and repeat attempts are processed.
• Team instructions — step-by-step launch scenario, notification setup, pre-launch checks, and analysis of typical errors with causes.
• Access roles — separation of rights: who only views statistics, who edits conditions, who confirms distribution. Change history is recorded.
• Set of checks — self-check scenarios after launch: duplicate rewards, unclosed tasks, stuck accruals.
• Rollback map — how to pause a campaign, revoke a reward, and restore the previous configuration in one operation.

We close the handover with a walkthrough: we go through each artifact, launch a test campaign with your own hands, and stay in touch during the first independent launches.

Case study: campaign from manual reward distribution to automated verification

The campaign was launched on Galxe for a project community: a series of tasks — channel subscription, holding a token in a wallet, a repeat transaction on-chain.

The reward, OAT, was distributed manually: the operator exported a list of addresses, checked each against the condition completion table, and confirmed distribution in batches.

With a flow of several thousand participants, this turned into a separate role for the entire campaign duration.

Where they got stuck

Manual reconciliation produced three effects at once.

The reward distribution timeframe stretched to 3–4 days, and a participant who completed the conditions in a minute waited almost a week for it; errors when transferring addresses reached 4–6% of distributions, and disputed cases such as "the transaction went through, but the mark was not counted" went to support.

Reward-related requests accounted for up to 40% of all campaign messages, and the flow did not subside as activity grew.

What was moved to automated verification

Task conditions were described formally and moved to automated verification: a background job reads network events, checks the address against the task rule, and initiates reward issuance.

Repeat distribution is cut off by the "address + task" key, while discrepancies are flagged for review instead of blocking the entire distribution.

The reward arrives within 2–4 minutes after completing the conditions, the share of erroneous and repeat issuances dropped to zero, and support load fell by a factor of three — only requests about real discrepancies remained. The reconciliation rule was reused in the next campaign, with only the task conditions changed.

How does a quest on your own domain differ from a campaign in Galxe?

Both paths solve one task — confirm participant actions and distribute a reward — but they distribute control differently.

On your own domain, you own both the verification logic and the wallet database; in a campaign on an external platform, you rent ready-made infrastructure together with its audience.

Data control is the main difference. On your own domain, the wallet, signature, and completion history remain in your database: you segment, export, replay, and set thresholds for next stages.

On the platform, you see an aggregate for the campaign, while the participant's personal history is in their profile.

Speed and flexibility are separated at the poles. A campaign is assembled from ready-made blocks and launches quickly, but a condition outside the builder — balance verification, activity in a third-party protocol, a combination of events — goes into your own circuit. Your own domain gives freedom of conditions but requires your own development.

External platform rules are a separate risk: moderation, changes to mechanics, restrictions on reward types. For a long-term program, it is reasonable to keep critical logic and the database in-house, and use the platform as an acquisition channel.

Technical concerns: limits, duplicates, and reward revocation

Before launching a campaign, the client asks four questions: how repeat participants are filtered out, what happens if platform rules change, how results are recalculated, and whether a reward can be revoked. We answer each — the entire mechanics rest on the distribution log, not on manual moderation.

The foundation is a single log: wallet address, linked account, task, time, and result. The reward is accrued once; reprocessing the same event changes nothing.

What to do if the platform changes the rules?

Campaign conditions are versioned: an edit does not rewrite history but is added as a new version with an effective date. Already distributed rewards remain under the previous version, new participants follow the new one.

If the platform changes the confirmation method, we update only the verification — the log and distribution are not affected.

How do you recalculate results if you find an error?

Recalculation is based not on the current state but on the event log: we take a slice for the required period, apply the current rules again, and obtain a discrepancy. Then — additional accrual or revocation only for affected addresses, while the campaign is not stopped. The report shows whom and to what extent the recalculation affected.

Can a reward be revoked, and what about campaign resilience?

Where distribution has not yet been written on-chain, revocation goes through the participant registry, and unclaimed rewards are canceled before receipt. If the record is irreversible, revocation is impossible — that is why we keep a verification window until the final step.

The checks themselves go through several sources: if one fails, the task goes into a retry queue, and the participant sees the status "under review," not a rejection.

Let's discuss the task: what is needed to estimate a quest campaign

To come back with a timeline estimate and work plan, rather than general considerations, a minimum set of input data is needed. The more specific the input, the more accurate the analysis — down to distributing tasks by stages and assignees.

Send or show during a call:

• the network and standard in which achievements and OAT are issued, and who owns the reward contract;
• campaign task types: on-chain actions, channel subscriptions, invitations, participation in events;
• accrual logic: what the reward is issued for, whether there are levels, limits, and repeat distributions;
• campaign timelines and expected participant volume — this determines the load on reward distribution;
• access: quest platform account with the required roles, test wallet, and environment for the run;
• materials: task texts, visuals, campaign page, draft requirements, if any;
• reporting: which campaign metrics need to be visible and in what form to export them.

In response, we will come back with a stage-by-stage work plan, a timeline estimate for each, and a reward flow scheme. As a separate item — the risks we close before launch and what will be required from your side for this.

The next step is a short call: we go over the inputs, clarify the scope and reporting format. Describe the task — we will discuss it and come back with an estimate and a plan.