recruiting-pipeline
Scannednpx machina-cli add skill anthropics/knowledge-work-plugins/recruiting-pipeline --openclawRecruiting Pipeline
Help manage the recruiting pipeline from sourcing through offer acceptance.
Pipeline Stages
| Stage | Description | Key Actions |
|---|---|---|
| Sourced | Identified and reached out | Personalized outreach |
| Screen | Phone/video screen | Evaluate basic fit |
| Interview | On-site or panel interviews | Structured evaluation |
| Debrief | Team decision | Calibrate feedback |
| Offer | Extending offer | Comp package, negotiation |
| Accepted | Offer accepted | Transition to onboarding |
Metrics to Track
- Pipeline velocity: Days per stage
- Conversion rates: Stage-to-stage drop-off
- Source effectiveness: Which channels produce hires
- Offer acceptance rate: Offers extended vs. accepted
- Time to fill: Days from req open to offer accepted
If ATS Connected
Pull candidate data automatically, update statuses, and track pipeline metrics in real time.
Source
git clone https://github.com/anthropics/knowledge-work-plugins/blob/main/human-resources/skills/recruiting-pipeline/SKILL.mdView on GitHub Overview
This skill helps you manage the entire recruiting pipeline from Sourced to Accepted. It tracks stages, actions, and key metrics to surface bottlenecks and improve hiring outcomes. When connected to an ATS, it pulls candidate data in real time for up-to-date visibility.
How This Skill Works
Candidates progress through defined stages—Sourced, Screen, Interview, Debrief, Offer, and Accepted—with stage-specific actions (personalized outreach, basic fit screening, structured interviews, calibrated feedback, offers/negotiation, onboarding). The system updates statuses, calculates pipeline metrics (velocity, conversion rates, time-to-fill, source effectiveness), and can auto-sync with an ATS for real-time data. Triggers like 'recruiting update', 'candidate pipeline', 'how many candidates', or discussions of sourcing, screening, interviewing, or offers activate the workflow and data updates.
When to Use It
- During weekly recruiting standups to show pipeline health and progress across stages (Sourced → Accepted).
- After sourcing campaigns to evaluate source effectiveness and optimize channels.
- Post-interview debriefs to calibrate feedback and improve decision consistency.
- When extending offers to monitor acceptance rates and time-to-fill from offer to acceptance.
- When you want a real-time view of how many candidates are in each stage and overall pipeline velocity.
Quick Start
- Step 1: Define stages (Sourced, Screen, Interview, Debrief, Offer, Accepted) and assign clear criteria for each.
- Step 2: Connect your ATS or begin manual candidate tracking and start updating statuses as candidates move.
- Step 3: Monitor the pipeline regularly, use triggers like 'recruiting update' to refresh data, and review key metrics (velocity, conversions, time-to-fill).
Best Practices
- Define clear criteria for each stage (Sourced, Screen, Interview, Debrief, Offer, Accepted) and ensure all team members follow them.
- Keep statuses updated in real time, preferably via ATS integration for automatic syncing.
- Track key metrics: pipeline velocity, stage-to-stage conversion, source effectiveness, offer acceptance rate, and time to fill.
- Use structured evaluations during interviews and debriefs to reduce bias and improve decision quality.
- Periodically review source performance and adapt sourcing strategy based on data.
Example Use Cases
- A recruiter monitors velocity from Sourced to Offer and identifies a bottleneck in the Interview stage, then tweaks interview scheduling to speed up progress.
- An ATS-connected pipeline updates statuses automatically, delivering a real-time dashboard for hiring managers.
- The team compares LinkedIn, referrals, and campus channels to see which yields higher offers accepted, reallocating budget accordingly.
- Debriefs are standardized to calibrate feedback across interviewers, improving consistency of candidate evaluations.
- Time-to-fill improves by 15% after optimizing stage handoffs and reducing idle time between stages.