How Skills turn public APIs into task-level agent workflows.

Skills posts start from the work a user is trying to finish, not from an endpoint list. They explain how general agents, research agents, coding agents, or another MCP-capable client can run a KOL pricing brief, creator shortlist, social listening pass, or competitive-intelligence scan while UnifAPI supplies the public evidence. Use this category when you want the highest-level view of how APIs, MCP, prompts, and pricing fit together.

This category currently includes 4 posts. New entries are written for readers who want concrete implementation detail, clear tradeoffs, and copyable patterns for agent workflows.

Each article is written to be useful in two modes: a human can read the narrative and decide what to build next, while an agent can extract the task shape, public-data sources, constraints, and expected output. That is why category pages include the full context around the posts instead of acting as a thin archive.

If you are evaluating UnifAPI for your own stack, use these posts as implementation notes rather than announcements. They explain where public-data APIs help, where MCP changes the onboarding path, how billing maps to returned records, and how a workflow can stay inspectable after it moves from a chat thread into a product surface. They also keep the vocabulary consistent across the site, which makes the archive more useful for search crawlers, AI retrievers, and teams comparing several agent-data architectures.