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

Annotations already declare readOnly, idempotent, non-destructive and closed-world, so the safety profile is covered. Beyond that, the description adds real value: it discloses ordering (best fit first), the exact fields returned per lead (id, name, headline, profile URL, foundBecause, note, dm, fit score), and the human-in-the-loop guarantee that nothing is sent without approval — none of which appears in annotations or schema.

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 actual purpose is back-loaded behind two sentences of product overview about ICP matching and the sending planner's daily/weekly limits and warm-up ramp. Some of that context (nothing sent without approval) genuinely matters for interpreting the queue, but the limit details belong to the sending subsystem rather than this read call and could be trimmed.

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 parameters and no output schema, the description carries the full burden and does so: it enumerates every returned field, explains what foundBecause means, states the sort order, and rules out any side effects. An agent has everything needed to call it and interpret the response.

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?

The tool takes zero parameters, so there is no parameter semantics to add and the baseline of 4 applies. The description correctly implies a no-argument call by describing the tool as simply returning the current queue.

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 third sentence states a specific verb and resource: "Returns the leads waiting for a decision, best fit first." It also implicitly separates the tool from approve_lead and skip_lead by framing this as the read step that must precede "approving or skipping", and from get_replies/get_stats which cover other data.

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?

Explicit sequencing guidance — "Read this before approving or skipping anything" — tells the agent exactly where this tool sits in the workflow relative to its siblings, and the absence of inputs signals it is a plain list call. There is no explicit when-not condition or pagination/filtering caveat, so it stops short of a 5.

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