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Mixer4AI

by com.mixer4ai
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self_register_agent_card

Starts self-registration: submits this agent's own card metadata (name, endpoint URL, capabilities, declared protocols) with NO credential required. Returns a one-time access code and a domain-challenge token/well-known path - keep the access code, it is the only way to correct this draft, trigger its challenges, check its status, or have it approved. Registration only completes once both challenges pass AND your human owner approves it once (approve_agent_self_registration).

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
requestYes

Schema Changelog

Changes observed during successful MCP inspections.

  1. Changed1 schema field changed
    • addedInput schema / properties / request / properties / x-mixer4ai / properties / reputationScoreBreakdown / properties / incorporationContinuityLine
      Added value: +{
+  "default": null,
+  "type": [
+    "string",
+    "null"
+  ]
+}
  2. Changed1 schema field changed
    • addedInput schema / properties / request / properties / x-mixer4ai / properties / reputationScoreBreakdown
      Added value: +{
+  "default": null,
+  "properties": {
+    "asOf": {
+      "format": "date-time",
+      "type": "string"
+    },
+    "baseline": {
+      "type": "number"
+    },
+    "components": {
+      "items": {
+        "properties": {
+          "contribution": {
+            "type": "number"
+          },
+          "eventCount": {
+            "type": "integer"
+          },
+          "eventType": {
+            "type": "string"
+          }
+        },
+        "required": [
+          "eventType",
+          "eventCount",
+          "contribution"
+        ],
+        "type": "object"
+      },
+      "type": "array"
+    },
+    "formulaVersion": {
+      "type": "integer"
+    },
+    "score": {
+      "type": "number"
+    }
+  },
+  "required": [
+    "score",
+    "baseline",
+    "formulaVersion",
+    "asOf",
+    "components"
+  ],
+  "type": [
+    "object",
+    "null"
+  ]
+}
  3. First observed

TDQS

A4.2/5.0
Behavior4/5

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

Annotations provide no safety profile (readOnlyHint/idempotentHint/destructiveHint all false), so the description carries the burden. It covers important behavior: no credential required, returns a one-time access code and challenge token/path, registration completion requires both challenges and human approval. The emphasis on keeping the access code because it is the only way to affect the registration is a meaningful disclosure. It does not mention idempotency, duplicate-call side effects, or token expiration, so it stops short of perfect transparency.

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?

Three sentences, each carrying distinct and necessary information: the action and auth requirement, the returned artifacts and the critical access code warning, and the composite completion criteria. The description is front-loaded with the core purpose and uses dash-parenthetical syntax to keep related details together; no filler or redundant restatement.

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?

The tool is complex (multi-step, heavy nested schema, no output schema, and low annotation clarity). The description adequately covers the flow—why and how to start registration, what you get back, what to keep, and what must happen to finish. It leaves some gaps around the full return type shape and detailed construction of the request object, but it affords enough context for an agent to invoke and continue through the registration lifecycle.

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?

With 0% schema description coverage, the description must compensate for parameter meaning. It surfaces some high-level semantics ('name, endpoint URL, capabilities, declared protocols' and maps them to request fields), but the schema is a nested object with many required fields such as skills, defaultInputModes, defaultOutputModes, and x-mixer4ai.verificationTier that are left entirely unexplained. The description adds some value over the schema's bare type names but does not fully compensate for the massive schema.

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 action: 'Starts self-registration' and 'submits this agent's own card metadata', listing the resource (name, endpoint URL, capabilities, declared protocols). It clearly distinguishes from siblings by highlighting 'NO credential required' and referencing the self-registration workflow with approval via approve_agent_self_registration. This is not tautological and leaves no ambiguity about what the tool does.

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 gives clear context for when this tool is used: self-registration without credentials, followed by domain/endpoint challenges and human approval. It names the follow-up approval tool and explains that the access code is needed for subsequent steps. It does not explicitly exclude any sibling alternatives like register_agent_card, but the context strongly implies the intended use case.

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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