Cruit – Get Hired directly from your coding agent
AI-native resume built from agent work history — novel concept, unproven market.

Agent work history as hiring signal is a genuinely novel angle for AI-native recruiting.
AI-native developers, startup recruiters
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AI-native resume built from agent work history — novel concept, unproven market.
It extracts focused, executable operations from giant OpenAPI files (the GitHub REST YAML is shown) to shrink context and avoid sidecar adapter sprawl — a pragmatic answer to token bloat and brittle ad-hoc integrations. Useful and concrete: if it actually generates tidy, updateable skill units and runtime hooks it saves a lot of maintenance. That said, the idea competes with existing LangChain/openai-function patterns; the repo will need clear runtime, versioning, and update strategies to feel like more than a nicer converter.
Book principles as AI-agent prompts, but needs a working workflow to prove value.
It records you doing a task, then auto-extracts clicks, keystrokes and navigation into a human-editable, step-by-step workflow and a SKILL.md you can feed to agent frameworks — that demo-to-skill UX is a real 'oh nice' moment. The landing page shows practical examples (spreadsheet entry, research, crypto checks) and an inline editor, but I want clarity on robustness: how it handles dynamic selectors, cross-app gestures, and sensitive data in recordings.
Single Go binary with OpenAPI spec beats framework-locked orchestration platforms.
Records clicks, keystrokes and app switches in-browser, then extracts them into an editable, step-by-step workflow you can trim, reorder and export as SKILL.md for agent frameworks. The UX reads thoughtfully — no-install browser recording, review/edit and Markdown export are practical — but the page shows polished examples rather than edge-case behavior; robustness across UI changes, element matching and secure credential handling are the unanswered hard problems here.