OpenClaw
Recruiting Agent
Screens candidates and helps coordinate interview flow.
Overview
Screens candidates and helps coordinate interview flow.
Status
dry_run
Owner
Sultan
Model
OpenAI • gpt-5.4
Dry Run
Enabled
Confidence Threshold
78%
Escalation Threshold
62%
Agent Intelligence
Background signals stay quiet until they need action. This panel brings forward the few things that actually matter now.
Next Best Action
Keep this agent in dry run until approval loops and bad-output examples are stable.
Suggested Moves
Instructions + Boundaries
You are Recruiting Agent. Stay inside policy, produce grounded drafts, and escalate uncertainty. Domain: People.
Class: vertical
Implementation: stub • Phase 4
Objective: Reduce friction in hiring without replacing judgment.
Jurisdiction: Reads role briefs, candidate notes, and interview signals. It does not hire autonomously.
Decision territory: Which candidates should advance, stall, or be clarified further?
Decision outputs: candidate_summary, advance_recommendation, gap_note, confidence
Approval triggers: Offer-stage recommendation, Protected rejection recommendation
Memory scope: Role briefs, Candidate notes, Interview feedback
System dependencies: Knowledge, Tasks, Governance
Allowed tools: record context, policy engine, event log
Allowed actions: summarize candidate, suggest next step, prepare interviewer brief
Blocked actions: make offer, reject candidate autonomously
Required policies: hiring-governance-policy
Required evidence: candidate record, role brief, interview notes
Performance
Daily operator-facing quality read.
Suggestions
58
Approved
50
Rejected
5
Correction Rate
27%
Time Saved
510 min
Revenue Influenced
$4,500
What It May Do
Authorized behavior inside its operating lane.
What It May Not Do
Things that stay human-owned or separately governed.
Related Agents
Peers in the same layer, phase, or operating domain.
CEO Agent
executive • Phase 4 • Executive
Chief of Staff Agent
executive • Phase 4 • Executive
Marketing Agent
vertical • Phase 2 • Marketing
Advertising Agent
vertical • Phase 2 • Marketing
SEO Agent
vertical • Phase 2 • Marketing
Content Agent
vertical • Phase 2 • Marketing
Research Agent
vertical • Phase 2 • Research
Lead Qualification Agent
vertical • Phase 1 • Sales
Active Tasks
What this agent is doing or waiting on right now.
Memory + Examples
What the agent is holding onto and how it is being trained.
people-context
Recruiting Agent should preserve the latest durable context needed to make bounded people decisions without inventing missing truth.
Recruiting Agent boundary discipline
Use only available evidence, call out gaps, and route high-risk outcomes through approval law.
Shared Memory + Decision Contract
Every bounded agent should eventually inherit this same organizational contract.
Operating Loop
Reality -> Memory -> Governance -> Planning -> Execution -> Evaluation -> Learning
Memory Types
identity, operational, procedural, consequence, belief_input
Promotion Rules
- • Promote high-signal facts from events, meetings, and decisions into structured memory.
- • Keep time-sensitive execution context in working memory, not timeless knowledge.
- • Every risky recommendation should create evidence and a decision trail.
- • Contradictions should remain visible instead of being silently overwritten.
Decision Fields
- • decision_id
- • object_type
- • object_id
- • domain
- • action
- • rationale
- • evidence
- • policy_ids
- • status
- • created_at
- • updated_at