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

Annotations already declare readOnlyHint and idempotentHint, so the safe-read nature is known. The description adds valuable behavioral context by enumerating the return fields (id, title, cluster, definition, rationale, implications, risk-if-violated), noting that laws also carry eponym and validator_questions, and specifying that unknown slugs return an error_payload. This goes beyond the annotation baseline and informs edge-case handling.

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 compact and front-loaded with the core purpose, then packs lens semantics, return fields, usage alternatives, and error behavior into three sentences. Every sentence contributes unique value without redundancy, achieving high informational density.

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 simple get-by-slug tool with two parameters, the description covers all necessary context: what the tool returns, how the lens parameter alters selection, when to use it versus alternatives, and how errors are handled. The presence of an output schema further reduces ambiguity, and the description still goes beyond by detailing the content of the response.

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% with descriptive parameter entries, so baseline is 3. The description enriches this by explaining the semantic meaning of each lens value ('architecture' = 10 agentic principles, 'surface' = 8 design laws, 'spec' = 8 spec laws) and by advising users to obtain slugs from principles.list, which is not explicit in the schema. This compensates well for the schema's bare listing.

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 opens with 'Get one doctrine entry by stable slug', clearly stating the verb and resource. It further distinguishes the lens values by naming exactly what each selects (10 agentic principles, 8 experience-design laws, 8 spec-quality laws), and explicitly contrasts with principles.list and principles.search, making it easy to identify the tool's unique role.

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 usage instructions: 'Use this when you already have the exact slug from principles.list', and names alternatives: 'prefer principles.search when the user describes a topic or failure mode in natural language; prefer principles.list when you need every entry or every entry within a cluster.' This is textbook when/when-not guidance with specific alternatives.

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