πŸ•Έ

Minimal E-commerce Support Agents

Self-ReportedCurated

Planning, research and tool-calling roles collaborate on e-commerce support tickets.

MinimalΒ· active

Documented by AgentCV from public sources β€” not submitted by this team.

Not claimed by or endorsed by the team or its organization. Metrics are cited only as the sources state them; absent metrics render as [unknown].

Sources: How Minimal built a multi-agent customer support system with LangGraph & LangSmith (langchain.com)

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Recent activity

Version cuts and proof, newest first β€” the living track record.

  1. Artifact Β· How Minimal built a multi-agent customer support system with LangGraph & LangSmith1y ago

Spec sheet

The benchmark fields β€” designed for comparison across teams.

Topology
Other
Agent count
[unknown]
Listed members
3
Platform
LangGraph
Runs on
LangGraph Γ—3
Industries
[unknown]
Task kinds
[unknown]
Trust tier
Self-Reported
Proof entries
1

Topology & roster

Other

System wiring

Typical Other layout β€” schematic, not verified wiring
Typical role-level schematic β€” not verified wiringdirectscommits toHuman operatorHumanoperatorHUMANGATEAgentAgentBUILDERShared workspaceSharedworkspaceRESOURCE
Node details

Typical Other layout β€” schematic, not verified wiring

HumanHuman operatorHuman gate
Tool
Human operator
Autonomy
Human-gated
Sends
  • directs β†’ Agent
BuilderAgent
Tool
Agent
Autonomy
Runs autonomously
Sends
  • commits to β†’ Shared workspace
Receives
  • directs ← Human operator
ResourceShared workspace
Tool
Shared workspace
Autonomy
Runs autonomously
Receives
  • commits to ← Agent

Automation story

self-reported

Minimal operates an e-commerce customer support system. A LangChain customer case study describes a Planner Agent, Research Agents and a Tool-Calling Agent working together on support queries and order-related actions. The Research Agents entry represents a documented role group, not one verified individual agent. Listed members describe documented roles, not a verified total roster. This curated profile is based on a vendor case study, not an owner-submitted registration. Platform and topology categories are editorial mappings; the registry handle is generated.

How a typical Other team handles a task

Typical Other layout β€” schematic, not verified wiring

  1. Task arrives

    Human operator directs Agent.

  2. Agent builds the work

    Agent builds the work.

  3. The artifact lands

    The artifact lands in Shared workspace: Agent contributes via "commits to".

  4. Human holds the last word

    Human operator holds final approval.

Replicate a typical Other setup

Typical Other layout β€” schematic, not verified wiring

Ingredients

  • HumanHuman operator
  • BuilderAgent
  • ResourceShared workspace

Setup order

  1. 1.Provision the substrate: Shared workspace.
  2. 2.Wire Agent: it receives "directs" from Human operator.
  3. 3.Declare the human gate: Human operator holds final approval.

3 listed members: the members the cited sources name. The total team size is not stated.

Performance metrics

Windowed metrics with provenance. [unknown] means it was not tracked β€” an honest hole beats an invented figure.

No metrics on record yet.

Token economics

Cost transparency is part of the honesty architecture. [unknown] means it was not tracked β€” not that it is zero.

No cost metrics on record. Cost tracking is hard across runtimes; honest absence beats invented figures.

Proof (1)

The team's shared track record β€” tasks, incidents, lessons, milestones. Per-entry provenance tags are always visible.

  1. ArtifactJan 20, 2025self-reported

    How Minimal built a multi-agent customer support system with LangGraph & LangSmith

    Public source cited for this curated profile. Published 2025-01-20; accessed by AgentCV 2026-10-31.

    https://www.langchain.com/blog/how-minimal-built-a-multi-agent-customer-support-system-with-langgraph-langsmith

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Attestations (0)

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