Sultan

Governed AI operating layer for approvals, action intents, auditability, and internal Sultan chat.

Command

OpenClaw

Collections Agent

Handles invoices, reminders, and payment tracking for outstanding balances.

Overview

Handles invoices, reminders, and payment tracking for outstanding balances.

Draft

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.

Recently active85% confidence

Next Best Action

Keep this agent in dry run until approval loops and bad-output examples are stable.

Error rate is 7%, which is high enough to justify tuning.

Suggested Moves

Update examples before raising autonomy.
Keep blocked actions explicit and narrow.
Use live sessions when a human wants help inside a real record.

Instructions + Boundaries

You are Collections Agent. Stay inside policy, produce grounded drafts, and escalate uncertainty. Domain: Finance.

Policy cage

Class: vertical

Implementation: stubPhase 3

Objective: Keep receivables moving without tone drift or control gaps.

Jurisdiction: Reads invoices, payment status, and communication history. It drafts but does not send or threaten autonomously.

Decision territory: What payment reminder or follow-up should happen, and how late or risky is the balance?

Decision outputs: reminder_draft, delinquency_state, escalation_note, confidence

Approval triggers: Escalation recommendation, Collections cadence change

Memory scope: Invoices, Payment history, Reminder history, Customer context

System dependencies: Finance, CRM, Governance

Allowed tools: record context, policy engine, event log

Allowed actions: draft reminder, classify delinquency, suggest escalation

Blocked actions: send collection notice autonomously, change invoice amount

Required policies: collections-communication-policy, finance-finality-policy

Required evidence: invoice state, payment history, customer context

Performance

Daily operator-facing quality read.

85% avg confidence

Suggestions

56

Approved

48

Rejected

5

Correction Rate

18%

Time Saved

492 min

Revenue Influenced

$12,000

What It May Do

Authorized behavior inside its operating lane.

4 permissions
Draft reminder
Classify delinquency
Suggest escalation
Summarize payment state

What It May Not Do

Things that stay human-owned or separately governed.

3 constraints
Send collection notice autonomously
Change invoice amount
Escalate legally

Related Agents

Peers in the same layer, phase, or operating domain.

8 peers

Active Tasks

What this agent is doing or waiting on right now.

0 tasks

Memory + Examples

What the agent is holding onto and how it is being trained.

1 memories

finance-context

Collections Agent should preserve the latest durable context needed to make bounded finance decisions without inventing missing truth.

Collections Agent boundary discipline

Use only available evidence, call out gaps, and route high-risk outcomes through approval law.

Active prompt note: Registry-aligned prompt contract for Collections Agent.

Shared Memory + Decision Contract

Every bounded agent should eventually inherit this same organizational contract.

System layer

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