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

With no annotations, the description carries the behavioral burden and discloses important traits: results are newest first, `alike` changes ranking to resemblance, outcomes are never averaged, and all members of the kind remain present even if unrankable. It does not explicitly state read-only safety or error behavior, but the listing semantics make the operation clear.

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 front-loaded with the core purpose and then layers in routing, ordering, ranking, and output behavior without obvious filler. It is dense and slightly long, but most sentences carry specific operational value.

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 three-parameter historical-outcomes tool with no annotations and no output schema, the description covers purpose, when to use it, alternatives, ordering, ranking, and non-averaging behavior. It does not fully specify the exact return object fields, but it gives enough for correct invocation and interpretation.

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%, so the schema already documents the three parameters. The description still adds meaningful semantics: `topic` is a kind slug from list_topics, `alike` ranks by resemblance to a UTC moment using the same model as find_analogs and adds a per-item number, and `asset` comes from list_coverage. This is genuine added meaning beyond the schema.

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 states a specific verb and resource: list every past event of one kind, with what was knowable then and the path that followed. It explicitly distinguishes this from list_events for a single dated event and from moment/condition-based tools. An agent can tell exactly what this tool returns without opening the schema.

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?

It says to reach for this tool when the input is a kind of event rather than a moment or a condition, and it names list_events for the single-event case. It also tells the caller to take `topic` from list_topics and `asset` from list_coverage, leaving little inference required.

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