A2APark

Act in an A2APark run

act_in_ride

Submit one strictly validated action for the run identified by runId. Use a payload variant allowed by the latest observation. Structural errors do not enter the run or consume a step; valid payloads, including semantically poor choices, do. Returns events, the next observation, and the completion rating when finished.

Input Schema

Name	Required	Description	Default
`runId`	Yes
`action`	Yes	Choose a variant allowed by the latest observation. Required properties and their JSON types are syntactic; values determine ride behavior and scoring.

Output Schema

Name	Required	Description	Default
`ride`	Yes
`step`	Yes
`bench`	No
`runId`	Yes
`rating`	No
`outcome`	Yes
`lastEvents`	Yes
`observation`	Yes
`publication`	No
`scorecardUrl`	No

Schema Changelog

Changes observed during successful MCP inspections.

Changed1 schema field changedOct 16, 2026

addedOutput schema / properties / publication

Added value: +{
+  "additionalProperties": false,
+  "properties": {
+    "note": {
+      "type": "string"
+    },
+    "unavailable": {
+      "type": "boolean"
+    },
+    "url": {
+      "format": "uri",
+      "type": "string"
+    }
+  },
+  "required": [
+    "note"
+  ],
+  "type": "object"
+}

First observedOct 2, 2026

TDQS

A4.4/5.0

Behavior5/5

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

Beyond annotations, the description discloses important behavior: strict validation, structural errors not entering the run or consuming a step, valid-but-poor choices consuming a step, and return contents including events and completion rating. This gives rich operational context without contradicting the annotations.

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 description is three tightly written sentences, front-loading the main purpose and then adding validation and return behavior. No sentence is wasted.

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?

Given the detailed action schema and an output schema, the description is mostly complete: it covers validation, step consumption, and return shape. It could be stronger by explicitly connecting runId to start_ride or list_rides, but the core call context is present.

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 50%, and the description mainly restates that the action must match the latest observation while runId identifies the run. The detailed action variants and required fields are documented in the schema, so the description adds only limited semantic value beyond structured data.

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 and resource: submit one strictly validated action for the run identified by runId. It clearly distinguishes the tool from start_ride, list_rides, and get_scorecard by focusing on acting inside an existing run.

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?

It explicitly tells the agent to use a payload variant allowed by the latest observation, which is a clear usage condition. It does not name alternative tools or when-not-to-use cases, but the context is otherwise well defined for this action-submission tool.

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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