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Universal Agents

by ai.universalagents
OverviewDiscussionsAdmin

Answer a frequently asked question

answer_faq
Read-only

Answers common questions about Universal Agents: agent readiness, working with teams, industries, timeline, what makes us different, data safety, adoption. Omit the question to get all of them.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
questionNoThe question or a keyword, e.g. "data" or "how long".

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault
matchYesall: no question given; best: the closest answers; none: no match, so all of them.
answersYes
agent_mayYesWhat an agent may do with this answer unsupervised: a level on the Universal Agents Delegation Map, 1 Tell to 7 Hands Off.
provenanceYes

Schema Changelog

Changes observed during successful MCP inspections.

  1. Changed1 schema field changed
    • changedOutput schema / (root)
      Previous value: -nullNew value: +{
+  "additionalProperties": false,
+  "properties": {
+    "agent_may": {
+      "additionalProperties": false,
+      "description": "What an agent may do with this answer unsupervised: a level on the Universal Agents Delegation Map, 1 Tell to 7 Hands Off.",
+      "properties": {
+        "label": {
+          "type": "string"
+        },
+        "level": {
+          "type": "integer"
+        },
+        "note": {
+          "type": "string"
+        }
+      },
+      "required": [
+        "level",
+        "label",
+        "note"
+      ],
+      "type": "object"
+    },
+    "answers": {
+      "items": {
+        "additionalProperties": false,
+        "properties": {
+          "agent_may": {
+            "additionalProperties": false,
+            "description": "What an agent may do with this answer unsupervised: a level on the Universal Agents Delegation Map, 1 Tell to 7 Hands Off.",
+            "properties": {
+              "label": {
+                "type": "string"
+              },
+              "level": {
+                "type": "integer"
+              },
+              "note": {
+                "type": "string"
+              }
+            },
+            "required": [
+              "level",
+              "label",
+              "note"
+            ],
+            "type": "object"
+          },
+          "answer": {
+            "type": "string"
+          },
+          "provenance": {
+            "additionalProperties": false,
+            "properties": {
+              "accountable": {
+                "additionalProperties": false,
+                "properties": {
+                  "contact": {
+                    "type": "string"
+                  },
+                  "name": {
+                    "type": "string"
+                  },
+                  "title": {
+                    "type": "string"
+                  }
+                },
+                "required": [
+                  "name",
+                  "title",
+                  "contact"
+                ],
+                "type": "object"
+              },
+              "answer_type": {
+                "enum": [
+                  "pricing",
+                  "product"
+                ],
+                "type": "string"
+              },
+              "authors": {
+                "items": {
+                  "additionalProperties": false,
+                  "properties": {
+                    "name": {
+                      "type": "string"
+                    },
+                    "title": {
+                      "type": "string"
+                    }
+                  },
+                  "required": [
+                    "name",
+                    "title"
+                  ],
+                  "type": "object"
+                },
+                "type": "array"
+              },
+              "effective": {
+                "type": "string"
+              },
+              "source": {
+                "additionalProperties": false,
+                "properties": {
+                  "path": {
+                    "type": "string"
+                  },
+                  "repo": {
+                    "type": "string"
+                  }
+                },
+                "required": [
+                  "repo",
+                  "path"
+                ],
+                "type": "object"
+              }
+            },
+            "required": [
+              "answer_type",
+              "authors",
+              "accountable",
+              "source",
+              "effective"
+            ],
+            "type": "object"
+          },
+          "question": {
+            "type": "string"
+          }
+        },
+        "required": [
+          "question",
+          "answer",
+          "provenance",
+          "agent_may"
+        ],
+        "type": "object"
+      },
+      "type": "array"
+    },
+    "match": {
+      "description": "all: no question given; best: the closest answers; none: no match, so all of them.",
+      "enum": [
+        "all",
+        "best",
+        "none"
+      ],
+      "type": "string"
+    },
+    "provenance": {
+      "additionalProperties": false,
+      "properties": {
+        "accountable": {
+          "additionalProperties": false,
+          "properties": {
+            "contact": {
+              "type": "string"
+            },
+            "name": {
+              "type": "string"
+            },
+            "title": {
+              "type": "string"
+            }
+          },
+          "required": [
+            "name",
+            "title",
+            "contact"
+          ],
+          "type": "object"
+        },
+        "answer_type": {
+          "enum": [
+            "pricing",
+            "product"
+          ],
+          "type": "string"
+        },
+        "authors": {
+          "items": {
+            "additionalProperties": false,
+            "properties": {
+              "name": {
+                "type": "string"
+              },
+              "title": {
+                "type": "string"
+              }
+            },
+            "required": [
+              "name",
+              "title"
+            ],
+            "type": "object"
+          },
+          "type": "array"
+        },
+        "effective": {
+          "type": "string"
+        },
+        "source": {
+          "additionalProperties": false,
+          "properties": {
+            "path": {
+              "type": "string"
+            },
+            "repo": {
+              "type": "string"
+            }
+          },
+          "required": [
+            "repo",
+            "path"
+          ],
+          "type": "object"
+        }
+      },
+      "required": [
+        "answer_type",
+        "authors",
+        "accountable",
+        "source",
+        "effective"
+      ],
+      "type": "object"
+    }
+  },
+  "required": [
+    "match",
+    "answers",
+    "provenance",
+    "agent_may"
+  ],
+  "type": "object"
+}
  2. First observed

TDQS

A3.7/5.0
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 a genuine behavioral trait not in the annotations: omitting the question returns the full set of FAQs, which tells the agent how the default invocation behaves.

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?

Two compact sentences, front-loaded with the topic scope and closing with the omission default. No wasted phrasing, though the topic list is long and could be summarized.

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

Completeness4/5

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

With an output schema present, return values need not be described, and the topic enumeration plus default behavior give the agent enough to invoke it correctly. Missing only guidance on how it relates to the sibling tools.

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 coverage is 100% for the single parameter, and the schema already states that a keyword like 'data' or 'how long' is valid. The description reinforces this by enumerating topics, which is useful for matching, but adds little beyond the schema baseline.

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

Purpose4/5

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

States a clear verb (Answers) and the resource/topic scope (common questions about Universal Agents), enumerating the covered domains. It is distinguishable from siblings like about_universal_agents, though it doesn't explicitly say how it differs.

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 only usage guidance is the default behavior: 'Omit the question to get all of them.' There is no explicit when-to-use-this-vs-siblings guidance, such as when to prefer about_universal_agents or get_pricing over the FAQ.

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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