--- name: recruiter slug: recruiter version: 1.0.0 description: Source candidates, screen resumes, and manage hiring pipelines with effective recruiting practices. homepage: https://clawic.com/skills/recruiter metadata: clawdbot: emoji: 🎯 os: - linux - darwin - win32 displayName: Recruiter --- # Recruiting Assistance Rules ## Role Understanding - Internal recruiter vs agency recruiter have different incentives — agencies paid on placement, internal on fit - Recruiting is sales with humans — both selling the role to candidates and candidates to hiring managers - Time-to-hire matters but quality matters more — bad hires cost 2-3x salary to fix ## Job Descriptions - Requirements vs nice-to-haves must be clearly separated — overloaded requirements scare good candidates - "Years of experience" is a poor proxy — focus on demonstrated skills and outcomes - Salary range transparency attracts better candidates — hiding it wastes everyone's time - Avoid gendered language and unnecessary requirements — "rockstar" and "must lift 50lbs" narrow pools - Include what the role actually does daily — not just responsibilities, but reality ## Sourcing Candidates - LinkedIn is obvious but saturated — good candidates get 50+ messages weekly - Personalized outreach beats templates — reference specific work, projects, or posts - Referrals have higher success rates — incentivize and track them - Passive candidates need compelling reasons — they're not looking, give them a reason to listen - Diverse sourcing requires intentional effort — same channels produce same candidate profiles ## Resume Screening - Look for impact, not just responsibilities — "managed team" vs "grew team from 3 to 12" - Job hopping context matters — industry, company health, growth trajectory - Gaps aren't automatic disqualifiers — ask, don't assume - Side projects and open source show initiative — especially for technical roles - Education requirements exclude capable candidates — evaluate when truly necessary ## Interview Process - Define evaluation criteria before interviews — consistency enables comparison - Structured interviews reduce bias — same questions, same order, scoring rubric - Take-home tests respect candidate time limits — 2-4 hours max, paid if longer - Interview loops shouldn't exceed 4-5 rounds — respect for candidates' time signals culture - Interviewers need training — untrained interviewers make poor decisions and create legal risk ## Candidate Experience - Respond to all applicants — ghosting damages employer brand - Communicate timeline upfront — "you'll hear back in X days" then actually do it - Feedback after rejection helps when possible — legal concerns are often overstated - Keep candidates warm during slow processes — silence feels like rejection - Rejected candidates may return or refer — treat everyone as future relationship ## Compensation - Know market rates for the role — underpaying attracts desperate, not best - Total compensation includes equity, benefits, flexibility — don't just compare base - Negotiation isn't adversarial — find mutually acceptable terms - Internal equity matters — new hires shouldn't out-earn existing employees unfairly - Be prepared to walk away — desperation leads to bad deals ## Pipeline Management - Track candidates through stages — lost candidates are wasted sourcing effort - Speed matters — good candidates have options, slow processes lose them - Bottlenecks are usually hiring manager availability — surface and solve - Rejection reasons inform future sourcing — pattern recognition improves targeting - Keep pipelines warm for future roles — relationship building pays off ## Legal Considerations - Consistent process protects against discrimination claims — document everything - Questions about age, family, religion, disability are off-limits — focus on job requirements - Background checks require consent and compliance — laws vary by jurisdiction - Offer letters should be reviewed by legal — verbal offers can create issues - Non-competes and NDAs in offers need explanation — candidates should understand ## Red Flags in Candidates - Badmouthing previous employers — pattern will continue - Vague answers about accomplishments — may not have been responsible - Inability to explain gaps or moves — evasion suggests problems - Different story in different interviews — consistency matters - Unwillingness to provide references — hiding something ## Common Mistakes - Hiring for culture fit that's actually bias — "fit" can exclude diversity - Rushing to fill headcount — empty seat better than wrong person - Ignoring hiring manager feedback patterns — some reject everyone, some accept everyone - Not selling the role actively — interviewing is two-way evaluation - Over-relying on credentials — pedigree doesn't guarantee performance --- Source attribution: clawic Original project: https://github.com/clawic/skills/blob/f825206afbf1c697202533a9187be68c7b697e0e/skills/recruiter/SKILL.md License: MIT License information: https://opensource.org/license/mit Original upstream instructions; downloaded from Mega AI Hub. ## Upstream license notice MIT License Copyright (c) 2026 Ivan G. Davila Permission is hereby granted, free of charge, to any person obtaining a copy of this software and associated documentation files (the "Software"), to deal in the Software without restriction, including without limitation the rights to use, copy, modify, merge, publish, distribute, sublicense, and/or sell copies of the Software, and to permit persons to whom the Software is furnished to do so, subject to the following conditions: The above copyright notice and this permission notice shall be included in all copies or substantial portions of the Software. THE SOFTWARE IS PROVIDED "AS IS", WITHOUT WARRANTY OF ANY KIND, EXPRESS OR IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF MERCHANTABILITY, FITNESS FOR A PARTICULAR PURPOSE AND NONINFRINGEMENT. IN NO EVENT SHALL THE AUTHORS OR COPYRIGHT HOLDERS BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHER LIABILITY, WHETHER IN AN ACTION OF CONTRACT, TORT OR OTHERWISE, ARISING FROM, OUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR OTHER DEALINGS IN THE SOFTWARE. # Mega AI Hub resource metadata Creator / publisher: clawic Original project: https://github.com/clawic/skills/blob/f825206afbf1c697202533a9187be68c7b697e0e/skills/recruiter/SKILL.md Attribution basis: Source repository record Fields of work: Human Resources Roles: HR Generalist, People Operations, Recruiter Specialties: Specialty not specified Tools: Tool not specified Country applicability: Country not specified Classification basis: Source catalog labels Instruction SHA-256: cbd17a1d67f81abc29fd7ba04d9b71de62be7bc02e0e433317ddc39c22b9dfa4