A current job count becomes a trend only when there is a comparable previous observation. The first successful check cannot establish growth by itself. A monitoring integration should make that first snapshot visible and keep incomplete collections from quietly replacing the comparison point.
Hiring Trend Index watches explicit company or board slices. Company slices can name a provider and token; board slices describe a bounded market sample. These are different observation scopes, even when both eventually produce counts of engineering roles.
Name the experiment before collecting it
The following input is the installed public example with an explicit watch name. The listed organizations and keywords identify collection targets, not freshly verified vacancy totals. Using the same watch_key preserves the intended comparison history; a new watch starts a separate one.
{
"slices": [
"company:greenhouse:gitlab",
"board:xing-jobs:engineering"
],
"watch_key": "software-hiring-example",
"new_window_days": 30
}
Keep your watch definition in version control or a configuration table. Record the slices and the company lookback setting with each exported observation. If the definition changes materially, start a separately named series or annotate the break rather than treating the next count as directly comparable with the old one.
Preserve the first-check distinction
A baseline-created row is a current snapshot. The next complete observation can report before and after counts and a function-level direction. Store baselineCreated alongside totalOpenRoles, totalOpenRolesBaseline and totalOpenRolesDelta. Showing a first-check zero delta as flat hiring would imply a comparison that did not happen.
Function grouping is part of the installed method. Counts from an ATS and counts from a board sample should retain their source and slice labels. A change can reflect postings entering or leaving the observed source, collection timing, or changes in the underlying sample. It does not by itself prove changes in headcount, revenue or completed hiring.
Keep incomplete slices out of the baseline
An unavailable slice must remain a coverage gap. The installed contract exposes partial state, missingSlices and source counters, while other slices can still deliver. An incomplete slice does not advance its baseline. That behavior protects the next valid comparison from using a timeout or a truncated collection as its previous truth.
The same distinction belongs in your dashboard. A missing observation is not a zero. Leave a gap or attach an unavailable state rather than drawing an apparently measured collapse in open roles. If some slices succeeded, publish their bounded results with a visible partial-run label and route the failed slices for investigation.
Inspect storage and delivery before repeating
This Actor uses a named baseline in the buyer's account. The watch identifier is therefore operational state, not just a presentation label. Avoid simultaneous runs for the same logical watch, and inspect an uncertain run's Dataset and charge counters before repeating it. A local process timeout alone does not establish that platform work stopped.
For an integration acceptance check, inspect a first snapshot, a later comparable snapshot and an incomplete-slice outcome. Verify that the chart distinguishes baseline creation, a measured flat count and missing coverage. Keep source collection time beside import time. The resulting series can support a defensible observation about this hiring sample without claiming a complete labor-market census.
Price and verification scope
FREE-tier event prices read on 24 October 2026 are $0.005 for apify-actor-start and $0.01 for result-found. Start-event count can depend on allocated memory; other account tiers have their own rates. Check the listing's current billable unit and the platform's run spending limit before executing an example. Input row or result caps are separate from Max total charge. A free diagnostic does not necessarily remove the platform start charge.
This article is pinned to public latest build 0.2.2 (420XlHjUglrFYhsCI) at the recorded read time. Source, input and pricing were read from Apify; no new cloud build or run was started. The supplied example and any synthetic local checks do not establish current source facts, cloud delivery or customer outcomes.
Inspect the Actor's current contract and pricing.
AI-assisted writing. Source contracts and verification limits are documented above.
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