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list_agents

Read-onlyIdempotent

Retrieves all agents registered in a LastPing project, returning id, slug, name, status, monitor count, and last seen. Use it to review agent health and identify down, blocked, or late agents.

Instructions

List all agents registered in the project. Returns id, slug, name, status, monitor_count and last_seen for each. status is rolled up live from the monitors the agent owns, worst first: down (a monitor is down), blocked (a monitor's run needs a human right now), late (a monitor is late), running (a monitor's run is in flight), up (healthy), pending (a monitor exists but has never reported) or idle (no monitors, or all of them paused/in maintenance). Use register_agent to create one.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault

No arguments

Schema Changelog

Changes observed during successful MCP inspections. Dates show when Glama detected each change.

  1. First observed

TDQS

A4.7/5.0
Behavior5/5

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

Annotations already establish readOnly, idempotent, and non-destructive behavior, so the description does not need to restate safety. It adds valuable behavioral detail beyond annotations: status is a live roll-up from the agent's monitors, ordered worst-first, with each possible value explained. This is essential context for interpreting results, especially given the absence of an output schema.

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

Conciseness5/5

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

The purpose is front-loaded in the first sentence, return fields are listed, and the status semantics are explained compactly but thoroughly. The final sentence routes to register_agent without adding noise. Every sentence earns its place, and the status enumeration is necessary because the status field has custom domain meaning.

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

Completeness5/5

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

This is a zero-parameter read-only list operation with annotations covering safety. The description supplies the return fields and the complete semantics of the status field, which compensates for the missing output schema. An agent has everything needed to invoke the tool and interpret its response correctly.

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

Parameters4/5

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

The tool has zero parameters and 100% schema description coverage, so there is no parameter burden for the description to carry. The phrase 'registered in the project' adds scope context but no parameter-specific documentation is needed.

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 states a specific verb ('List'), the resource ('agents registered in the project'), and the exact fields returned, including the nuanced status field. This makes it clearly distinguishable from siblings like get_agent (single lookup) and register_agent (creation).

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

Usage Guidelines4/5

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

The description explicitly names register_agent as the alternative when the goal is to create an agent. It does not explicitly contrast with get_agent for single-agent retrieval, but the phrase 'List all agents' makes the usage context clear without requiring an exclusion statement.

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

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