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

Annotations already declare readOnlyHint, idempotentHint and a closed-world scope, so safety is covered. The description usefully adds that the response is full Markdown text, but says nothing about single-vs-multi language behavior or what happens when a slug is missing.

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?

A single sentence with the output format front-loaded and no filler. Every clause earns its place.

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?

No output schema exists, but the description compensates by naming the return payload (full text as Markdown). Parameters and safety are covered elsewhere, leaving only edge-case behavior unaddressed.

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%: slug has an example ('miamiflow') and language has an enum plus default. The description adds only the slug's provenance, so the baseline 3 applies.

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+resource ('full text of one case study') and even the output format ('as Markdown'), which cleanly separates it from the sibling list_case_studies. The parenthetical '(from list_case_studies)' implies the relationship, though it doesn't explicitly contrast the two tools.

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?

Usage is only implied: the '(from list_case_studies)' note tells the agent where slugs originate, suggesting this is the follow-up to listing. There is no explicit when-to-use/when-not statement or named alternative for other content types (get_post, get_services).

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