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

Annotations already declare readOnlyHint=true and destructiveHint=false. The description adds valuable behavioral context: the tool can return either the full schema or a filtered subset depending on the element_type parameter, with size implications ('much smaller'), and emphasizes the schema is 'authoritative' and 'generated from the protocol.' No contradictions with annotations.

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 three sentences, each earning its place: statement of purpose, explanation of the two modes, and actionable usage guidance. No redundant or filler content.

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 tool with one optional parameter and no output schema, the description is complete: it explains the input options, the return value's nature (exact field names, types, enums), and connects to sibling authoring tools. The absence of an output schema is compensated by the explicit statement that it returns a JSON Schema, making the return self-evident.

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 fully describes the element_type parameter (coverage 100%), so the baseline is 3. The description adds concrete examples ('text', 'shape', 'particles') and clarifies the no-argument behavior, reinforcing the schema semantics and providing helpful usage context. This elevates it above baseline.

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 clearly states the tool's function: 'Return the authoritative JSON Schema for a Clipkit Source — exact field names, types, and enums, generated from the protocol.' It uses a specific verb ('Return') and resource ('JSON Schema for a Clipkit Source'), and further distinguishes itself from sibling tools by referencing authoring workflows (set_project / add_element). This is a clear, specific purpose that is not confused with other tools like get_project.

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 gives explicit when-to-use guidance: 'Use this when authoring with set_project / add_element so you never guess a field.' It also explains the two calling modes (with or without element_type). However, it does not name alternatives to avoid or explicitly state when not to use it, so it falls short of a perfect score.

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