splithub_experiment_events

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

With no annotations, the description carries the full burden and does well: it discloses retention ('raw events stay 7 days, 30 on Pro'), required scope ('key needs events:read'), ordering (newest first), and pagination mechanics (nextBefore pages older, pass as before). It does not mention rate limits or error behavior, keeping it below a 5.

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?

One dense but front-loaded paragraph: what it returns first, then filters/paging, then retention/auth, then the use case. Every clause is informative, though the telegraphic phrasing ('Same from / to / filters as splithub_results') is slightly compressed.

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 7-parameter tool with a nested filters object, no annotations and no output schema, the description covers purpose, filter/paging semantics, retention window, required scope and event shape. An agent has enough to call it correctly and interpret what comes back.

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 only 43%, so the description must compensate, and it does: it explains that type keeps one kind, that before is fed by nextBefore from the previous page, and that from/to/filters behave identically to splithub_results. Only limit is left undocumented in both places, a minor gap.

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?

States a specific resource (raw events of one experiment), names the two event kinds returned (exposure, goal) and the fields carried (time, visitor, url, country). The 'raw events' framing plus the pointer to splithub_results implicitly separates it from the aggregated sibling, so an agent can pick it 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?

Explicitly says 'Use to check that exposures and goals arrive after wiring code,' giving a concrete invocation context, and references splithub_results as the place to get the same from/to/filters for aggregated queries. It stops short of stating when NOT to use it (e.g., for conversion numbers), so it is clear context without full exclusions.

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