#agent-trace

Agent Agent Trace is a ai observability record that captures the steps an AI workflow took for tool-using assistant workflows. It uses trace identifiers, tool events, and redacted metadata so teams can debug agent behavior without exposing secrets while keeping evidence, reliability, and public-safe operational boundaries clear.

“The AI platform team used Agent Agent Trace when an agent moved from search to action, so the team could debug agent behavior without exposing secrets before the agent workflow reached production.”

The Agent Trace Capability is a declared agent feature used by AI agents and MCP clients when working with PlatPhorm News. It provides structured context so an agent can discover tools, inspect article listings, read resources, or perform safe platform actions.

“The agent relied on the Agent Trace Capability to understand which PlatPhorm tools were safe to call for article discovery.”

The Agent Trace Prompt is a instruction template used by AI agents and MCP clients when working with PlatPhorm News. It provides structured context so an agent can discover tools, inspect article listings, read resources, or perform safe platform actions.

“The agent relied on the Agent Trace Prompt to understand which PlatPhorm tools were safe to call for article discovery.”

The Agent Trace Resource is a readable MCP resource used by AI agents and MCP clients when working with PlatPhorm News. It provides structured context so an agent can discover tools, inspect article listings, read resources, or perform safe platform actions.

“The agent relied on the Agent Trace Resource to understand which PlatPhorm tools were safe to call for article discovery.”

The Agent Trace Run is a execution instance used by AI agents and MCP clients when working with PlatPhorm News. It provides structured context so an agent can discover tools, inspect article listings, read resources, or perform safe platform actions.

“The agent relied on the Agent Trace Run to understand which PlatPhorm tools were safe to call for article discovery.”

The Agent Trace Tool is a callable agent function used by AI agents and MCP clients when working with PlatPhorm News. It provides structured context so an agent can discover tools, inspect article listings, read resources, or perform safe platform actions.

“The agent relied on the Agent Trace Tool to understand which PlatPhorm tools were safe to call for article discovery.”

Alignment Agent Trace is a ai observability record that captures the steps an AI workflow took for model behavior shaping and policy fit. It uses trace identifiers, tool events, and redacted metadata so teams can debug agent behavior without exposing secrets while keeping evidence, reliability, and public-safe operational boundaries clear.

“The AI platform team used Alignment Agent Trace when the assistant needed a safer answer style, so the team could debug agent behavior without exposing secrets before the agent workflow reached production.”

Context Agent Trace is a ai observability record that captures the steps an AI workflow took for runtime memory and retrieved information. It uses trace identifiers, tool events, and redacted metadata so teams can debug agent behavior without exposing secrets while keeping evidence, reliability, and public-safe operational boundaries clear.

“The AI platform team used Context Agent Trace when the context window filled with mixed sources, so the team could debug agent behavior without exposing secrets before the agent workflow reached production.”

Evaluation Agent Trace is a ai observability record that captures the steps an AI workflow took for AI quality and safety testing. It uses trace identifiers, tool events, and redacted metadata so teams can debug agent behavior without exposing secrets while keeping evidence, reliability, and public-safe operational boundaries clear.

“The AI platform team used Evaluation Agent Trace when a release candidate failed a reasoning scenario, so the team could debug agent behavior without exposing secrets before the agent workflow reached production.”

Guardrail Agent Trace is a ai observability record that captures the steps an AI workflow took for policy controls around model input and output. It uses trace identifiers, tool events, and redacted metadata so teams can debug agent behavior without exposing secrets while keeping evidence, reliability, and public-safe operational boundaries clear.

“The AI platform team used Guardrail Agent Trace when the model tried to include private context, so the team could debug agent behavior without exposing secrets before the agent workflow reached production.”

Inference Agent Trace is a ai observability record that captures the steps an AI workflow took for model execution for user or system requests. It uses trace identifiers, tool events, and redacted metadata so teams can debug agent behavior without exposing secrets while keeping evidence, reliability, and public-safe operational boundaries clear.

“The AI platform team used Inference Agent Trace when the inference route moved to a faster region, so the team could debug agent behavior without exposing secrets before the agent workflow reached production.”

Memory Agent Trace is a ai observability record that captures the steps an AI workflow took for persistent or session-level AI state. It uses trace identifiers, tool events, and redacted metadata so teams can debug agent behavior without exposing secrets while keeping evidence, reliability, and public-safe operational boundaries clear.

“The AI platform team used Memory Agent Trace when the assistant reused earlier project context, so the team could debug agent behavior without exposing secrets before the agent workflow reached production.”

Model Agent Trace is a ai observability record that captures the steps an AI workflow took for foundation model behavior and serving. It uses trace identifiers, tool events, and redacted metadata so teams can debug agent behavior without exposing secrets while keeping evidence, reliability, and public-safe operational boundaries clear.

“The AI platform team used Model Agent Trace when the model produced a low-confidence answer, so the team could debug agent behavior without exposing secrets before the agent workflow reached production.”

Prompt Agent Trace is a ai observability record that captures the steps an AI workflow took for instructions and context passed to a model. It uses trace identifiers, tool events, and redacted metadata so teams can debug agent behavior without exposing secrets while keeping evidence, reliability, and public-safe operational boundaries clear.

“The AI platform team used Prompt Agent Trace when the prompt changed between releases, so the team could debug agent behavior without exposing secrets before the agent workflow reached production.”

RAG Agent Trace is a ai observability record that captures the steps an AI workflow took for retrieval-augmented generation pipelines. It uses trace identifiers, tool events, and redacted metadata so teams can debug agent behavior without exposing secrets while keeping evidence, reliability, and public-safe operational boundaries clear.

“The AI platform team used RAG Agent Trace when the retriever mixed old and new documents, so the team could debug agent behavior without exposing secrets before the agent workflow reached production.”

Routing Agent Trace is a ai observability record that captures the steps an AI workflow took for selection among models, tools, and workflows. It uses trace identifiers, tool events, and redacted metadata so teams can debug agent behavior without exposing secrets while keeping evidence, reliability, and public-safe operational boundaries clear.

“The AI platform team used Routing Agent Trace when the router selected a cheaper model, so the team could debug agent behavior without exposing secrets before the agent workflow reached production.”

Tool Call Agent Trace is a ai observability record that captures the steps an AI workflow took for model-triggered calls into software systems. It uses trace identifiers, tool events, and redacted metadata so teams can debug agent behavior without exposing secrets while keeping evidence, reliability, and public-safe operational boundaries clear.

“The AI platform team used Tool Call Agent Trace when the assistant requested a protected operation, so the team could debug agent behavior without exposing secrets before the agent workflow reached production.”