get_narratives

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

With no annotations, the description carries full weight. It discloses the output structure (each narrative has sentiment, mass, agreement, headlines) and the semantic difference from get_sentiment. It does not mention error conditions or side effects, but for a read-only data retrieval tool that is acceptable. The description provides context beyond the schema by explaining the 'mass' and 'agreement' concepts.

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 longer than necessary but well-structured: it opens with a value statement, lists the key fields, and then provides usage guidance. It is front-loaded with the most important info (full set vs top three) and ends with a clear alternative. A bit verbose but not wasteful.

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 no output schema, the description explains the return format (narratives with sentiment, mass, agreement, headlines). It also explains the use cases and how to differentiate from get_sentiment. It does not mention what happens if asset is omitted, but that is a minor gap given the schema marks both fields optional. The description is sufficient for an agent to understand what it will get and when to call it.

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 coverage is 100% (both asset and limit have descriptions in the schema). The description adds no new meaning about the parameters themselves—it only references the returned data. The schema already covers the default for limit ('default 8') and asset values. Baseline of 3 is appropriate since the schema does the heavy lifting.

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 resource ('narratives') and the action (retrieve the full set), and distinguishes it from get_sentiment which only returns the top three. It names the returned fields (sentiment, mass, agreement, headlines) which makes the tool's purpose concrete and differentiated from siblings like get_history and get_sources.

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?

Explicitly explains when to use this over get_sentiment: 'get_sentiment already returns the top three — call this when you want the whole picture or the headlines.' Also provides use cases (answer WHY sentiment is where it is, distinguish quiet vs contested markets). This is clear routing guidance with an explicit alternative.

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