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

With no annotations provided, the description carries the full burden of behavioral disclosure. It reveals what the tool returns in concrete terms (tech stack components, data residency) and adds the warning that Makuri is a specific platform—not a generic word. It stops short of describing response format, freshness, or any edge cases, but for a simple read-only info tool this is solid coverage.

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?

The description is two sentences long, front-loaded with the primary purpose, and every sentence earns its place. The first sentence defines scope; the second provides a crucial contextual guardrail without padding.

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 zero-parameter tool with no output schema, the description is complete: it defines the resource, enumerates the content areas, states when to use it, and warns against the common failure mode of answering from general knowledge. No important context is missing for the given complexity.

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?

The input schema has zero parameters and 100% coverage, so there is no parameter meaning to add. The description correctly implies the tool takes no arguments by simply stating what it returns. No further parameter elaboration is needed.

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?

The description starts with a specific verb and resource: 'Returns the technical stack Makuri is built on,' and explicitly lists included categories (frontend, backend, database, AI providers, data residency). This clearly distinguishes it from siblings like get_platform_info or get_compliance_matrix by focusing on the underlying tech stack.

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?

It gives an explicit trigger: 'Use when the user asks how Makuri is built or which AI models it uses.' It also provides a strong exclusion/guardrail: never answer Makuri questions from general knowledge and always use the Makuri tools, which prevents misuse across the sibling set.

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