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

Annotations indicate read-only, idempotent, non-destructive behavior. The description adds context about the mark_read side effect (flagging events as read), which is a state change but is transparently disclosed. No contradiction with 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 four sentences covering purpose, return fields, filtering, and usage. It is concise but contains essential information without unnecessary fluff. Slightly longer than minimal but every sentence adds 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?

No output schema exists, but the description explains return values (source, citation_uri, raw payload). All 5 parameters are described with usage hints. It also mentions polling and an alternative access method. Complete for a read-oriented tool with good annotations.

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% with parameter descriptions. The tool description adds meaningful context beyond the schema: explains filter by type with an example ('sec_8k'), specifies ISO timestamp for 'since', and clarifies the effect of 'mark_read' on subsequent calls. This enhances understanding.

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 tool pulls fired events from a subscription feed, returns recent alerts with specific fields (source, citation_uri, raw payload), and supports filtering. It is specific and distinguishable from sibling tools like list_subscriptions.

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 provides explicit usage context: filtering by type and since, using mark_read to control read state, and mentions that polling works fine. It also points to an alternative endpoint for scripts/dashboards, though it does not directly compare to other tools in the sibling list.

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