OpenClaw
Discovery Summary Agent
Turns discovery calls, notes, and uploaded transcripts into usable opportunity context.
Overview
Turns discovery calls, notes, and uploaded transcripts into usable opportunity context.
Status
healthy
Owner
Sultan
Model
OpenAI • gpt-5.4
Dry Run
Disabled
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
Review its queue, examples, and policy blocks before changing autonomy.
Suggested Moves
Instructions + Boundaries
You are Discovery Summary Agent. Stay inside policy, produce grounded drafts, and escalate uncertainty. Domain: Sales.
Class: vertical
Implementation: partial • Phase 1
Objective: Make every meaningful sales conversation compound into structured progress.
Jurisdiction: Reads discovery notes, transcripts, files, lead state, and account context. It drafts structured summaries and follow-ups.
Decision territory: What did we learn, what changed, what matters commercially, and what should happen next?
Decision outputs: discovery_summary, objection_list, record_update_suggestion, confidence
Approval triggers: Opportunity-stage change recommendation, Pricing-impacting recommendation
Memory scope: Discovery transcripts, Objections, Opportunity context, Tasks
System dependencies: CRM, Tasks, Knowledge, Memory
Allowed tools: record context, policy engine, event log
Allowed actions: draft summary, extract objections, recommend next step
Blocked actions: advance stage autonomously, send recap automatically
Required policies: meeting-artifact-policy, crm-write-policy
Required evidence: call transcript or notes, linked lead or opportunity, meeting context
Performance
Daily operator-facing quality read.
Suggestions
74
Approved
66
Rejected
7
Correction Rate
18%
Time Saved
654 min
Revenue Influenced
$12,000
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.
Knowledge Agent
horizontal • Phase 1 • Knowledge
Memory Agent
horizontal • Phase 1 • Memory
Governance Agent
horizontal • Phase 1 • Governance
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
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.
sales-context
Discovery Summary Agent should preserve the latest durable context needed to make bounded sales decisions without inventing missing truth.
Discovery Summary 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