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

The description adds meaningful behavioral context beyond the annotations: narratives are machine-generated summaries, not edited articles, and a high post_count with low author_count may indicate one person repeating themselves. This is exactly the kind of interpretive warning an agent needs and is not derivable from readOnlyHint, openWorldHint, or idempotentHint.

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 compact and front-loaded, defining the resource first and then adding a crucial interpretive caveat. Every sentence earns its place, and there is no filler or repetition of schema details.

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?

For a simple one-parameter read-only tool, the description provides enough context to call it safely and interpret results sensibly. It implicitly signals that returned stories expose post_count and author_count, though it does not describe the full return shape.

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 only parameter, limit, is a conventional optional integer with a default in the schema, so the description's silence on it creates little ambiguity. However, schema description coverage is 0%, and the description does not compensate by explaining how limit affects the result set.

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 identifies the resource as current narratives and explains the unit of data: an LLM summary of a cluster of posts, not a single document. It lacks an explicit verb like 'retrieve' but the intent is unmistakable. It partially distinguishes itself from post-level tools like get_story_posts, though it does not name siblings.

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 intended use is implied by 'Current narratives' and the caveat about reading author_count before quoting one provides real interpretive guidance. However, it does not explicitly say when to choose this tool over alternatives such as get_narrative_clusters or get_story_posts, nor does it state when not to use it.

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