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

Annotations only declare readOnlyHint=true, and the description goes well beyond that: it discloses term-by-term matching scope, relevance ranking with partial matches retained rather than discarded, fallback behavior when q is omitted, and the shape of the return ('compact listings with URLs'). This is exactly the behavioral context an agent needs to predict results.

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 tight sentences, front-loaded with the purpose, then matching semantics, ranking behavior, and the q-omitted fallback in descending order of importance. No filler sentences; every clause carries information.

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 output schema, the description must carry the return-value burden, and it does so adequately ('compact listings with URLs') without enumerating fields. Parameters are fully covered by the schema, so nothing critical is missing, though a little more on result fields would close the gap.

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 both q and limit are already documented in the schema. The description largely restates the q matching scope and adds no syntax or format detail beyond it, which is the baseline 3 when the schema does the heavy lifting.

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 ('Search bike4mind.com blog posts') and immediately differentiates itself from the sibling get_blog_post by describing term-by-term matching and ranked discovery rather than single-post retrieval. An agent can tell which tool to reach for without opening the 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?

Gives clear usage context: multi-word queries work as natural phrasing, no exact wording is needed, and omitting q lists recent posts. It stops short of explicitly naming alternatives (e.g. 'use get_blog_post to fetch one post'), so routing is implied rather than stated.

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