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Plori

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by plori-ai
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JavaScript
Remote

List agents

list_agents
Read-only

Retrieve agents owned by the authenticated account in reverse chronological order, including model, live session status, page URL, and last run time; empty models show effective_model.

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

A4.3/5.0
Behavior4/5

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

Annotations already declare readOnlyHint=true and openWorldHint=false, so the safety profile is covered. The description adds genuine non-obvious context: results are ordered newest first, what fields come back, and the important caveat that an empty model is not an error because effective_model / plori-auto resolve routing at run time.

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, both front-loaded and non-redundant: the first delivers purpose/scope/ordering, the second resolves a real ambiguity about a sentinel output value. No filler.

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 zero-parameter, read-only listing tool with an output schema, this is more than adequate – the return shape is documented elsewhere and the description supplies the interpretation nuance an agent would otherwise get wrong.

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 takes zero parameters, so the schema imposes no semantic burden and the baseline is 4. Nothing in the description is needed to disambiguate inputs.

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 names a specific verb and resource ('List the agents'), scopes it precisely ('owned by the authenticated account'), and states ordering ('newest first') plus the fields returned. That scope cleanly separates it from the singular get_agent sibling, so an agent can pick it without opening either schema.

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?

Usage is implied by 'list the agents owned by the authenticated account' – a reasonable agent infers it should be used to enumerate agents. However, there is no explicit when-to-use/when-not guidance and no mention of the get_agent alternative for fetching a single agent's detail.

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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