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by plori-ai
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JavaScript
Remote

List agents

list_agents
Read-only

List your cloud AI agents newest first, showing each one's model, live session status, web page URL, and last run time. Also reveals the effective model for runs, including plori-auto router selection.

Instructions

List the agents owned by the authenticated account, newest first, with each one's model, live session status, web page url and when it last ran. An agent whose model is empty is not unconfigured: effective_model says what a run will use, and plori-auto means the hosted router chooses per turn.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault

No arguments

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault
itemsYesThe returned items, in the endpoint's documented order.

Schema Changelog

Changes observed during successful MCP inspections.

  1. Changed2 schema fields changedv0.16.2
    • addedOutput schema / properties / items / items / properties / advisor_max_spend_micro_usd
      Added value: +{
+  "description": "Optional maximum advisor-completion spend per turn in micro-US-dollars. Zero disables advisor completions; null leaves no spend cap.",
+  "type": [
+    "null",
+    "integer"
+  ]
+}
    • changedOutput schema / properties / items / items / required
      Previous value: -[
-  "id",
-  "user_id",
-  "name",
-  "backend",
-  "model",
-  "effective_model",
-  "config",
-  "created_at"
-]New value: +[
+  "id",
+  "user_id",
+  "name",
+  "backend",
+  "model",
+  "advisor_max_spend_micro_usd",
+  "effective_model",
+  "config",
+  "created_at"
+]
  2. Changed1 schema field changedv0.16.0
    • changedOutput schema / (root)
      Previous value: -nullNew value: +{
+  "properties": {
+    "items": {
+      "description": "The returned items, in the endpoint's documented order.",
+      "items": {
+        "additionalProperties": false,
+        "properties": {
+          "backend": {
+            "description": "The compute backend this Agent runs on.",
+            "type": "string"
+          },
+          "config": {
+            "description": "Arbitrary JSON owned by the producing engine."
+          },
+          "created_at": {
+            "description": "When the Agent was created.",
+            "type": "string"
+          },
+          "deleting": {
+            "description": "True while this Agent's disk is still being erased; offer no action on it besides retrying the deletion itself.",
+            "type": "boolean"
+          },
+          "deleting_since": {
+            "description": "When the deletion was first requested; present only while deleting is true.",
+            "type": [
+              "null",
+              "string"
+            ]
+          },
+          "effective_model": {
+            "description": "The model a run on this Agent will actually use. plori-auto means the hosted router chooses per turn.",
+            "type": "string"
+          },
+          "id": {
+            "description": "The Agent's unique identifier; pass it to other tools as agent_id.",
+            "type": "string"
+          },
+          "last_run_at": {
+            "description": "When this Agent last started a run; absent when it has never run.",
+            "type": [
+              "null",
+              "string"
+            ]
+          },
+          "model": {
+            "description": "The model slug this Agent is configured to use. Empty means no explicit choice, which is not the same as no model — read effective_model for what a run will actually use.",
+            "type": "string"
+          },
+          "moving": {
+            "description": "True while this Agent's files are being copied to a new disk; check storage_notice rather than a separate route for the outcome.",
+            "type": "boolean"
+          },
+          "name": {
+            "description": "The Agent's name, chosen by its owner and unique within the account.",
+            "type": "string"
+          },
+          "queued_at": {
+            "description": "When a still-warming attach was accepted; present only while it is queued for node capacity.",
+            "type": [
+              "null",
+              "string"
+            ]
+          },
+          "status": {
+            "description": "The live warm-session state: warming, ready, or sleeping; empty when no session is active.",
+            "type": "string"
+          },
+          "storage_notice": {
+            "description": "The one sentence, if any, telling the owner about a storage move that stopped; show it verbatim, not paraphrased.",
+            "type": "string"
+          },
+          "url": {
+            "description": "This Agent's page in the plori web app.",
+            "type": "string"
+          },
+          "user_id": {
+            "description": "The identifier of the account that owns this Agent.",
+            "type": "string"
+          }
+        },
+        "required": [
+          "id",
+          "user_id",
+          "name",
+          "backend",
+          "model",
+          "effective_model",
+          "config",
+          "created_at"
+        ],
+        "type": "object"
+      },
+      "type": [
+        "null",
+        "array"
+      ]
+    }
+  },
+  "required": [
+    "items"
+  ],
+  "type": "object"
+}
  3. Changed1 schema field changedv0.3.0
    • addedInput schema / properties
      Added value: +{}
  4. First observedv0.1.0

TDQS

A4.5/5.0
Behavior5/5

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

Beyond the readOnlyHint annotation, the description adds meaningful behavioral detail: results are returned newest first, include a live session status and web page URL, and there is a non-obvious semantic distinction between an empty model and effective_model, including what plori-auto means. This is genuinely useful interpretive context.

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?

Two sentences, each earning its place. The first sentence front-loads the action, scope, ordering, and output fields; the second adds an important caveat about interpreting the model field. No fluff or redundancy.

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?

For a parameterless read-only listing operation with an output schema available, the description is complete: it covers the scope, ordering, returned fields, and a key edge-case nuance. Nothing needed for correct invocation is missing.

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?

There are zero parameters and schema coverage is 100%, so there is no parameter documentation burden. The description appropriately focuses on output semantics rather than parameters, earning the baseline 4 for a parameterless tool.

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 uses a specific verb ('List'), names the resource ('agents'), and scopes it to the authenticated account. It also reveals the ordering ('newest first') and the returned fields, which clearly distinguishes it from sibling tools like get_agent, list_runs, and list_workflows.

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

Usage Guidelines3/5

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

The usage context is implied: call this when you need to list the account's agents. It does not explicitly contrast itself with get_agent or mention when not to use it, but the simple resource-oriented phrasing makes the primary use case reasonably clear.

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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