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

With no annotations provided, the description carries the burden of behavioral disclosure. It does an above-average job by explicitly noting the export is 'deliberately lossy' and enumerating exactly what is omitted, while also summarizing the output style.

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?

Three sentences, each earning its place: the first states the action and output, the second flags important limitations, and the third gives the intended use case. The description is concise, well-structured, and front-loaded.

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 single-parameter tool with no output schema, the description covers the key concerns: what the output is, what it contains, what it omits, and why an agent would use it. It could add an explicit note about the return being a text/string, but the KN-notation description sufficiently implies it.

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%, so the baseline is 3. The description adds no parameter-specific meaning beyond what the schema already provides, but it does reinforce that the project must be published and that the token comes from metamodel_list_projects.

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 names a specific verb ('Export'), a specific resource ('published MetaModel project'), and a distinct output format ('KN notation'). It also lists what the output contains, which separates it from the sibling tools like list_projects or get_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?

The description clearly states when this tool is useful: 'reading or diffing the engineering knowledge behind a project.' The explicit lossy caveat also implies when not to use it, though it does not name sibling alternatives directly.

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