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AxonityAI

Axonity Flow MCP Server

Official
by AxonityAI

read_agent_published

Retrieve the live published version of an agent that the runtime uses, enabling comparison with the draft to identify pending publish changes.

Instructions

Read the LIVE published version of a agent — what the runtime actually uses, as opposed to the draft that read_agent returns. Diff the two to see what a pending publish would change.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
idYesThe agent's id.
Behavior3/5

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

No annotations are provided, so the description must fully convey behavioral traits. It clarifies the tool reads the live published version (a read-only operation) but does not disclose permissions, error handling, or rate limits. While it adds value beyond the name, it could be more transparent about potential side effects or limitations.

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 two sentences, front-loading the main purpose and key distinction. Every sentence provides value with no redundancy or filler. Highly efficient.

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?

For a simple read operation with a single parameter, the description adequately explains the purpose and contrasts with the draft version. There is no output schema, but the description implies the return of the agent object. It could mention the response structure aligns with read_agent, but it is sufficiently complete for the task.

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%, so the description does not need to add much. The only parameter 'id' has a basic description in the schema ('The agent's id.'), and the description does not provide additional context or format details. Baseline score of 3 is appropriate.

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 clearly states the tool reads the LIVE published version of an agent, contrasting with the draft returned by read_agent. It explicitly distinguishes from a sibling tool and specifies the resource (agent) and action (read published version).

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 mentions diffing the published version against the draft to see pending changes, providing a clear use case. It implicitly contrasts with read_agent for draft retrieval, offering guidance on when to use this tool. However, it does not explicitly state when not to use it or list alternatives beyond read_agent.

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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