Train KB from PPTX

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

Annotations already indicate a mutating, non-destructive operation; the description adds little beyond restating 'train.' It does not disclose whether content is appended/replaced, whether the operation is synchronous, or any authentication or side-effect details.

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 one-sentence description is front-loaded and economical, with no wasted words, but it is slightly too terse given the tool's 8 parameters and lack of output schema; a single additional sentence on usage or outcomes would not compromise conciseness.

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?

With no output schema and a moderately complex 8-parameter input, the description leaves significant gaps: no return value, no async indication, no prerequisite knowledge (e.g., existing rag_id), and no differentiation from closely related training tools.

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?

Schema description coverage is 100% and all eight parameters have individual descriptions, so a baseline score of 3 is appropriate. The tool description itself contributes no additional parameter-level meaning (e.g., base64 encoding or chunking behavior).

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 uses the specific verb 'train' with a concrete resource ('PPTX presentation') and target ('knowledge base'), directly distinguishing it from sibling parse-only tools like lyzr_parse_pptx and other lyzr_kb_train_* formats.

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?

The use case is implied by the name and description (training a KB from PPTX), but there are no explicit when-to-use instructions, exclusions, or references to alternatives such as lyzr_kb_train_documents or lyzr_parse_pptx.

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