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. The description adds genuinely new behavior: long pages are split at headings, the first call reveals how many parts exist, and datasets additionally return JSON data. That pagination and dual-format behavior is exactly the kind of trait annotations cannot express; only the slightly opaque reference to 'nextPart' (the schema field is named 'part') keeps it from a 5.

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 with no filler, and the core purpose is front-loaded before the pagination mechanics. The mention of 'nextPart' without explaining that it is a response field is a small clarity cost, but nothing is redundant.

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?

There is no output schema, so the description carries the return burden and does: markdown body, part structure with a count, and JSON data for datasets. Combined with a fully documented two-parameter schema and complete annotations, an agent has everything needed to call this correctly and interpret the result.

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%, so the baseline is 3, but the description adds meaning beyond the schema: it explains why 'part' exists (long pages are split at headings) and how the agent learns which part to ask for, which the bare 'Which part of a long page, from 1' does not convey. The url parameter is also contextualized as coming from find_resources rather than being any arbitrary link.

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 (read) and enumerates the resource types it covers (guides, studies, playbooks, datasets, recipes, comparisons, changelogs) plus the output format (markdown). It also distinguishes itself from the sibling it pairs with by telling the agent to use the url find_resources returned, so no schema-opening is needed to tell them apart.

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 clear entry conditions: come here after find_resources, pass the url it handed you. It also explains the long-page workflow (first call reports the part count, then request the needed part), which is real usage guidance. It does not state any case where a different sibling should be preferred instead, which keeps it 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.