narrative-engine__translate_narrative

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

With no annotations provided, the description carries the full burden for behavioral disclosure. It only states the transformation and lists options, omitting details on output format, side effects, authentication needs, or error conditions. This is insufficient for a tool with no annotation support.

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 followed by well-formatted lists. Every part contributes value, with no wasted words, making it highly concise and front-loaded.

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?

Given the tool's complexity (4 parameters, nested object, no output schema, no annotations), the description is incomplete. It fails to explain the output, handle optional parameters, or specify input format for 'agent_output', leaving significant gaps for an agent.

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?

The description adds meaning for 'audience_type' and 'format_type' by listing allowable values, compensating slightly for the 0% schema description coverage. However, it does not explain 'agent_output' or 'key_message', leaving gaps for half the parameters.

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 purpose: 'Translate raw ecological/agent data into a decision-maker-ready narrative.' It also lists specific audience and format options, making the verb and resource distinct from the sibling tool 'narrative-engine__describe_agent'.

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 description provides a list of possible audience types and format types, giving clear context on when to use the tool. However, it lacks explicit when-not-to-use or alternative tool references, though no direct siblings compete for narrative generation.

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