About Oink and how its job-search content is checked

Oink is an independent AI job search product that turns a job seeker’s current brief into explained matches delivered through Telegram or a private web feed. It is built and operated alongside the nomad-agent collection tools published on Apify. This site documents the consumer product, the reasoning behind its matching approach, and practical ways to inspect public job listings more carefully.

The content exists to help job seekers and developers make a concrete decision. It is not written to manufacture pages for every keyword variation, and Oink does not publish copied job descriptions as search landing pages.

How Oink creates and checks content

Product claims are checked against the current public interface, configuration, and executable implementation before a page is approved for publication. Third-party technical claims should link to the organization’s own documentation or another primary source where one exists. Experience-led or aggregate findings must state the sample window, method, and limitations instead of presenting an anecdote as a universal rule.

AI-assisted drafting or organization may be used. That assistance does not make a claim true, and it is not treated as a source. The operator remains responsible for checking product behavior, resolving contradictions, and deciding whether a page is ready to publish. This disclosure follows the useful “who, how, and why” questions in Google’s people-first content guidance.

Each evergreen page displays a Last reviewed date. Articles display a publication date and, after a material change, a separate updated date. Dates are not advanced merely because the site was rebuilt. The sitemap uses the same material-update date so a deployment does not pretend unchanged content is new.

Evidence labels matter

Oink separates several kinds of proof that are often conflated:

• a local test shows that a defined behavior passed in the tested tree;
• a deployment receipt identifies what was uploaded and where;
• a live fetch shows what a public URL returned at a particular time;
• a sitemap or IndexNow response is a discovery request, not an indexing receipt;
• an indexed URL is not proof of impressions, clicks, or a useful conversion;
• a Telegram card sent is not proof that someone opened or applied to the job.

The same discipline applies to the product. A 0–5 match score is a relevance ranking against the current brief, not an interview probability. A liveness check reduces the risk of a stale posting but cannot guarantee that a third-party employer still accepts applications. The AI matching guide and job-source guide explain those boundaries in detail.

Commercial relationships and links

Some developer articles link to Apify Actors published by nomad-agent, the same operator behind Oink’s collection work. Those links promote related first-party tools; they are not presented as independent third-party reviews. Actor availability, inputs, pricing, and source support can change, so readers should verify the current Store listing and run contract before integrating.

Oink’s job-seeker calls to action open the Oink product itself. A guide should remain useful without clicking that call to action. Promotional links do not justify an unsupported statistic, a hidden limitation, or a recommendation that the evidence would not otherwise support.

Privacy and responsible reporting

The public privacy policy describes the account, resume, preference, interaction, diagnostic, and analytics data the product can process. Open-web discovery can send derived job-title or keyword queries to a search provider; it does not need the raw resume for that request. Readers should use the current Privacy page for the operative disclosure rather than assuming “AI job search” means no third-party processing.

Original SEO research may use aggregate operational evidence, but it must not expose resumes, profile text, contact details, chat identifiers, or identifiable job-seeker behavior. Small cohorts should be suppressed or combined when reporting them would create re-identification risk.

Corrections and material changes

When a factual issue is found, the page should be checked against the authoritative source, corrected narrowly, and given a new updated date only when the reader-facing content materially changed. If evidence is unavailable or contradictory, the claim should be qualified or removed rather than polished into certainty.

Current product facts can also drift. Source availability, pricing, onboarding requirements, and delivery behavior deserve action-time checks before publication. Historical articles are reviewed in the 90-day SEO program specifically to remove stale counts, outdated score wording, and claims that are stronger than the implementation can prove.

To understand the product rather than the publishing method, begin with how Oink works. For practical reading, browse the job-seeker and developer guides or see how a match becomes a Telegram job alert.