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

Describes side effects of mark_read parameter (flagging events as read), which contradicts the readOnlyHint annotation. Adds critical behavioral context about state modification and that it is idempotent for read operations but not fully read-only.

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?

Three sentences effectively cover main action, return fields, filtering, and an alternative access method. Could be slightly more structured (e.g., bullet points) but remains clear and efficient.

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?

Despite no output schema, description explains return fields (source, citation_uri, raw payload) and covers all parameters including state management (mark_read/unread_only). Includes practical polling advice and alternative endpoint for scripts.

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?

Adds meaning beyond schema descriptions: explains type filters by subscription type, since as ISO timestamp, mark_read to avoid duplicates, unread_only for fresh events, and limit as max. Enhances understanding of each parameter's purpose.

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 subscription feed, specifies return fields (source, citation_uri, raw payload), and mentions filtering by type and ISO timestamp. Distinguishes 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?

Provides usage context: polls work fine and mentions alternative API endpoint for scripts/dashboards. Implicitly suggests when to use the direct API vs this tool, but does not explicitly list when not to use or compare to other similar tools.

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