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

Annotations include readOnlyHint: true and idempotentHint: true, but the description states that mark_read:true flags returned events as read and makes the next call only show newer ones. This is a mutating, non-idempotent side effect, directly contradicting the annotations.

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 and each sentence adds value, covering behavior, filters, side effects, and an external endpoint. It is slightly longer than necessary but remains efficient and well-structured.

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?

With no output schema, the description compensates by detailing the return payload (source, citation_uri, raw event payload) and explains filtering, mark_read behavior, and polling. Some details like limit and unread_only are left to the schema, which is acceptable.

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 description coverage is 100%, so baseline is 3. The description adds concrete examples like type 'sec_8k' and ISO timestamps, and explains the mark_read side effect beyond the schema's basic definition.

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?

Clearly states it pulls fired events from the user's subscription feed and returns the most recent alerts with metadata like source and citation_uri. This distinguishes it from siblings such as list_subscriptions and recent_changes.

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 says polling works fine and points to an alternate HTTP endpoint for scripts and dashboards, giving clear context for usage. However, it does not explicitly compare against sibling tools or 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.