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

Annotations already declare a safe read (readOnlyHint true, destructiveHint false), so the bar is lower, yet the description still adds real behavior: results are newest-first, and backfilled matches from the creation sweep are flagged and never sent an email. It omits pagination behavior, but the substantive disclosure here is well beyond 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?

Four sentences, front-loaded with the verb and the highest-value behavioral fact (the payoff + newest-first). Every sentence carries information; the phrasing "the payoff of an alert" is slightly decorative but not wasteful, keeping it just short of a 5.

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 carries the return-value burden and does so: it explains that each match names the watched entity and the episode/podcast slugs, plus what detailed view adds and how backfilled matches appear. Combined with a fully-covered input schema and read-only annotations, an agent has everything needed to call it correctly.

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 view, after, before, limit, cursor, and output_format are all documented structurally; the description largely restates the view/after/before semantics. The only marginal addition is that episode/podcast slugs feed particle_podcast_get_episode and particle_podcast_resolve, which justifies baseline 3 rather than higher.

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 verb and resource ("List the matches an alert has caught") plus ordering ("newest first") and even characterizes the payoff ("the payoff of an alert"). Combined with the name and the explicit downstream-tool references, an agent can distinguish this from particle_alert_list 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?

Gives concrete usage cues: use view=detailed for transcript excerpts, use after/before to scope a date range, and notes which sibling tools the returned slugs feed. It stops short of explicitly saying when not to use it or contrasting it with particle_alert_list, so it's clear context rather than full when/when-not routing.

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