Train Knowledge Graph from Text

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

Annotations already declare readOnlyHint=false and destructiveHint=false, and the description adds minimal behavioral context. It mentions 'v4' but does not explain whether the operation is synchronous or asynchronous, how it handles duplicate text, or any side effects beyond what annotations already signal.

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 a single sentence with no filler, demonstrating strong efficiency. However, the brevity leaves out contextual information that would help the agent, so it is concise but not optimally structured for full understanding.

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 six parameters, nested objects, and no output schema, the tool has moderate complexity. The description is too sparse to cover important aspects like synchronous vs. asynchronous execution, required fields, or expected return behavior, leaving clear gaps.

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%, so all six parameters are already well-documented in the input schema. The description adds no additional parameter-level meaning, placing it at the baseline of 3 without further compensation.

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 'Ingest text into the v4 knowledge graph' uses a specific verb and resource, and the 'v4' qualifier adds useful specificity. It distinguishes from kb_train_text (KB vs KG) and kg_train_website (text vs website), but does not explicitly contrast with the async lyzr_kg_train_text_task sibling, leaving slight ambiguity.

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?

No guidance is provided on when this tool should be chosen over alternatives like lyzr_kg_train_text_task or lyzr_kg_train_website. The description lacks any mention of preferred use cases, exclusions, or context-based recommendations.

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