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

Annotations already declare readOnlyHint=true, destructiveHint=false, etc., but the description adds significant behavioral context: it explains the returned fields (source, citation_uri, raw event payload), the effect of mark_read (flags events read so next call shows newer ones), and states that polling works fine. It also notes the same feed is accessible via HTTP. No contradictions 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 concise (4 sentences) and front-loaded with the main purpose. Each sentence adds value: first sentence states purpose and return fields, second explains filter options, third explains mark_read, fourth mentions polling and alternative access. No wasted words.

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, the description lists key return fields (source, citation_uri, raw event payload). It explains mark_read behavior and filter options. Missing explicit mention of limit default (schema says 50) and unread_only behavior, but overall it is fairly complete for a tool with optional parameters. Could be slightly more detailed on response format, but adequate.

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 covers all 5 parameters with descriptions (100% coverage), but the description adds value by providing usage examples: 'Filter by type (e.g. "sec_8k") and/or since (ISO timestamp)' and explains the mark_read behavior. For limit and unread_only, the schema already describes them, so the description's addition is moderate. With full schema coverage, baseline is 3, but the description's examples and context elevate it to 4.

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 and returns recent alerts with specific fields (source, citation_uri, raw payload). It uses a specific verb ('Pull') and identifies the resource ('fired events from your subscription feed'). This clearly distinguishes it from sibling tools like those for subscribing or querying AI, as it focuses on reading alerts from a persisted feed.

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 guidance on when to use the tool, such as 'Polls work fine' and mentions an alternative GET endpoint for scripts and dashboards. However, it does not explicitly state when not to use this tool versus other reading tools (e.g., ask_pipeworx). The alternative mention helps some, but more explicit exclusion of other tools would improve clarity.

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