AgentForge Runtime | Tool-Using Agent Runtime and Task Execution Framework v3.5

Description

AgentForge Runtime is a framework for building tool-using AI agents that can plan tasks, call approved tools, maintain execution state, and produce structured outputs under developer control. It is intended for teams that need more than a single prompt response but do not want an uncontrolled autonomous agent. The module provides an execution runtime where tools, permissions, task steps, memory scope, failure handling, and output schemas can be explicitly defined. It can support internal automation assistants, research agents, data workflow agents, coding support agents, document processing agents, and controlled operations agents. A typical use case is to give the agent a defined task, allow it to call a limited set of tools, track intermediate steps, handle failures, and return a structured result that can be reviewed or passed to another system. The module is useful when paired with AgentTool Router, AgentMemory Vault, ToolCalling SDK, GuardrailPolicy Engine, and WorkflowOrchestrator AI. It should not be treated as a fully autonomous decision maker. Production systems should restrict tool access, log every action, set execution budgets, validate outputs, and require approval for risky actions.

Product attributes

Canonical product name: AgentForge Runtime

Module type: Tool-using AI agent runtime framework

Primary category: AI agents

Secondary categories: Agent orchestration, task execution, tool use, controlled automation

Suggested list price: £899.00

Intended users: AI engineers, automation engineers, backend developers, agent system builders, platform teams

Applicable lifecycle stage: Agent prototype, controlled automation, internal assistant development, tool-using workflow construction

Typical inputs: Agent instructions, task definitions, approved tool registry, context payloads, execution policies, output schemas

Typical outputs: Structured agent runs, tool call traces, step logs, final task outputs, execution metadata

Delivery format: ZIP package automatically delivered by email after purchase

Expected package contents: Source files, agent runtime examples, tool registration templates, configuration files, documentation, tests

Runtime environment: Python based agent development environment

Integration mode: Agent backend runtime, internal automation service, tool orchestration layer, workflow execution component

Recommended skill level: Advanced

Commercial rights: Full commercial use is permitted

Modification rights: Modification, custom agent design, internal adaptation, and proprietary integration are permitted

Open source policy: Public open sourcing is prohibited

Redistribution policy: Resale, redistribution, sublicensing, or repackaging as a standalone module is prohibited

Production readiness note: Requires tool permission control, action logging, prompt injection review, output validation, and approval policies

Validation standard: The module is considered valid when a sample agent can execute a defined task, call approved tools, log steps, and return structured output as documented