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

Annotations already declare readOnlyHint=true and destructiveHint=false, so safety is covered. The description adds real value by disclosing the searched corpus and that results are summaries with match counts, but says nothing about ranking, result caps, or pagination.

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?

Two tight sentences with zero filler; the trigger condition and corpus scope are front-loaded, and the return behavior follows logically. Nothing could be removed without losing 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?

An output schema exists, so return values need no prose explanation, and the description correctly covers trigger and corpus. The only gap is a missing contrast with the listing and slug-fetch siblings that could cause an agent to pick this tool for enumeration.

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 single query parameter is fully documented with examples in the schema. The description only restates that it is a keyword/phrase search, adding no operator syntax or formatting rules beyond what the schema already provides, 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 and resource ("full-text keyword search") and names the corpus it covers: portfolio case studies, architecture blueprints, and technical articles. It is clearly a search tool rather than a listing tool, though it does not explicitly name siblings like get_articles or get_projects to sharpen the contrast.

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?

"Use this tool when performing a full-text keyword search" gives a condition for use, implicitly distinguishing keyword lookup from browsing collections. However, it offers no when-not guidance and does not name an alternative for listing or fetching a known slug.

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