Skip to main content
Glama

agentlens_log_event

Record events to an active AgentLens session for observability of AI agent behaviors. Use to log tool calls, responses, or custom actions with severity levels and metadata.

Instructions

Log an event to an active AgentLens session.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
sessionIdYesSession ID from agentlens_session_start
eventTypeYesEvent type (e.g., tool_call, tool_response, custom)
payloadYesEvent payload — structure depends on eventType
severityNoSeverity level (default: info)
metadataNoArbitrary metadata (tags, labels, correlation IDs)
Behavior2/5

Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?

No annotations are provided, and the description is too brief to disclose behavioral traits such as whether logging is synchronous, what happens if the session is inactive, or if there are rate limits. The description adds no value beyond the input schema.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Conciseness4/5

Is the description appropriately sized, front-loaded, and free of redundancy?

The description is a single sentence with no wasted words. However, it could include more useful information without becoming verbose, so it is good but not perfect.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Completeness2/5

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

Given 5 parameters and no output schema, the description lacks necessary context about return values, side effects, and how logged events relate to the AgentLens system. It does not mention that events can be queried later or the consequences of incorrect usage.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Parameters3/5

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

Schema description coverage is 100%, so the schema already documents all parameters. The description does not add any extra meaning beyond the schema definitions, warranting the baseline score of 3.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Purpose5/5

Does the description clearly state what the tool does and how it differs from similar tools?

The description clearly states the verb 'Log' and the resource 'event' targeted at 'active AgentLens session'. It distinguishes this tool from related siblings like agentlens_log_llm_call and agentlens_query_events, which have more specific purposes.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Usage Guidelines2/5

Does the description explain when to use this tool, when not to, or what alternatives exist?

The description provides no guidance on when to use this tool versus alternatives (e.g., log_llm_call for LLM-specific events). It does not mention prerequisites like having an active session or that events can be queried later with agentlens_query_events.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.

Install Server

Other Tools

Latest Blog Posts

MCP directory API

We provide all the information about MCP servers via our MCP API.

curl -X GET 'https://glama.ai/api/mcp/v1/servers/agentkitai/agentlens'

If you have feedback or need assistance with the MCP directory API, please join our Discord server