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

Annotations already cover the read-only and open-world profile, but the description adds real value beyond them: it discloses that results come from a live index in real time, describes the return shape (page links with title, section, description), and warns about what NOT to do when nothing matches. Minor gap: no indication of how many results are returned or how relevance is ranked, which matters for the 'pick one or two' instruction.

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?

Front-loaded with the audience warning in caps, then the operation, then the follow-up workflow, then example queries. Every sentence carries routing or behavioral information; nothing is a restatement of the name or title.

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 one-parameter search tool with no output schema, the description covers purpose, return shape, and workflow well enough to call it correctly. The remaining gap is result-set behavior — result count and pagination or narrowing strategy — which an agent would need if the first query returns nothing useful.

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?

With a single parameter at 100% schema coverage, the baseline is 3, but the description earns a bump by showing the kinds of input accepted: natural-language questions ('how does X work'), keyword phrases ('find docs on balances'), and format/spec queries ('Solana signing format'). That illustrates the schema's 'Keywords or natural language question' more concretely than the schema alone.

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 — 'Searches the live Yield.xyz documentation index (llms.txt)' — and immediately scopes it as a builder tool, not for end-user actions or live data. It also names the sibling it feeds into (yield_fetch_doc), so an agent can tell it apart from the action and yields tools without opening any 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?

Explicit when-to-use ('developing an integration', with four concrete query examples), explicit when-not ('NOT for end-user actions or live data'), and explicit fallback routing ('use the other docs tools in this MCP (never the action tools)'). It even specifies the follow-up step: pick one or two results and read them with yield_fetch_doc.

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