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19matches
The CrewAI job-posting example uses configurable research and writing agents to combine company context, role requirements, and industry information into a draft advertisement.
The setup workflow defines role-specific signals, maps Ashby application questions, and calibrates the rubric with past applications before scheduling daily candidate reviews.
The workflow identifies a recruiter's roles in Ashby, checks candidate-stage bottlenecks and stale records, and adds unresolved Slack actions to a prioritized review.
The skill investigates a target company's GitHub contributions, engineering writing, and conference activity, then cross-checks professional identities before proposing outreach targets.
The template retrieves Ashby context, asks eligibility questions, calculates a proposed bonus, checks the supplied policy range, and drafts a Slack approval request.
The agent identifies role requests, extracts hiring details, asks for missing information, and confirms the newly created Ashby opening in the original thread.
An Ashby-triggered agent resolves the candidate and role and posts a contextual Slack reminder for the interview team's feedback.
The assistant combines an Ashby scorecard, hiring rubric, and Slack context to examine a stated concern and prepare a reasoned recruiter response.
The skill combines Ashby application history with screen notes to draft a consistent evidence-based evaluation, logistics, and questions for the next interview stage.
The skill reads a pre-filtered Ashby sourcing dashboard, summarizes the current week's activity, and creates a Slack draft scoped to the recruiter's own numbers.
This workflow reads a candidate's application and interview notes and drafts role-specific feedback bullets in the ATS for a recruiter to review.
The template turns a job description and hiring criteria into stage-specific competencies, questions, strong-answer indicators, and warning signs in a shared Google Doc.
The template combines Ashby feedback and BrightHire transcripts to identify already-covered topics, unresolved risks, and useful final-round questions in a Google Doc.
The workflow verifies role ownership in the ATS, groups new referrals by recruiter, and posts deduplicated Slack threads for follow-up.
The template gathers role objectives through a chatbot and combines them with company examples to draft a job description, application questions, and interview guide.
GPT-4o-mini summarizes resume PDFs linked from a candidate sheet, emails the interviewer a structured brief, and marks the row processed to avoid repeats.
The agent uses Reducto to extract resume information and can connect the parsed profiles with the recruiting team's Ashby and Slack workflow.
The template reads PDF or DOCX resumes from a Notion candidate database, compares them with the linked job requirements using OpenAI, and writes scores and feedback back to Notion.
A VLM Run workflow parses emailed resumes, analyzes linked GitHub activity, and records a technical candidate profile with notifications for the recruiting team.