qlikcloud_assistant_chat

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

The description explains that the tool runs with the signed-in user's permissions and accesses knowledge bases accordingly, which is important for authorization awareness. It also outlines thread management behavior. Since no annotations are provided, this description carries the full burden and covers key behavioral aspects.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Is the description appropriately sized, front-loaded, and free of redundancy?

The description is efficient and informational, with no redundant content. Each sentence adds value, from the core action to the permission context and thread handling instructions.

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

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

The description covers the essential usage context, including authorization and thread management. While the output format is not described, the presence of an output schema reduces the need to spell out return values. Overall, it is sufficiently complete for practical use.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

All three parameters are explained in the description: assistant_id (how to find it), message (the question), and thread_id (optional, for continuing conversations). This fully compensates for the absence of schema-level descriptions.

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

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

The description clearly states the tool's primary function: sending a message to a Qlik Answers assistant and receiving a response. It distinguishes itself from sibling tools like qlikcloud_get and qlikcloud_delete by focusing on chat interaction.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Does the description explain when to use this tool, when not to, or what alternatives exist?

It provides clear guidance on how to use the tool, including the behavior of thread_id for conversation continuity. While it doesn't explicitly say 'use this instead of other tools', the context is unambiguous given the chat-specific purpose.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.