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

Annotations already declare readOnlyHint=true, idempotentHint=true, destructiveHint=false. The description adds genuinely useful context beyond those hints: 'First-party Valuein content. No data reads. Available on all plans.' It also explains the behavioral benefit of following playbooks (better results than improvising tool order), which helps the agent understand the tool's role. 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 front-loaded with the core purpose, then usage guidance, then differentiating constraints. Every sentence adds value: the first paragraph defines the content, the second explains when and why to call it, and the third adds operational facts. No filler.

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?

For a simple, read-only, paginated list tool with one optional parameter and an output schema, the description covers what the tool returns, why it matters, when to call it, and how it relates to get_sop. There are no meaningful gaps given the annotations and output schema already present.

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%, and the schema already fully describes the filter parameter, including case-insensitive substring matching, target fields, examples, and the omit-to-list-all behavior. The description repeats the schema's parameter explanation without adding new semantic meaning, so the baseline score of 3 is appropriate.

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 states a specific verb and resource ('List Valuein's expert research playbooks') and enumerates the exact contents (step-by-step procedures, tool sequences, parallel-wave grouping, output structure). It also differentiates from the sibling get_sop by framing this tool as the listing step that precedes loading a specific playbook.

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?

It gives explicit direction: 'CALL THIS FIRST for any multi-step financial research request, then load the matching playbook with get_sop.' This clearly communicates when to use the tool and the next step. It stops short of explicitly stating when not to use it or naming competing alternatives, so it misses the top score by a narrow margin.

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