get_rubric

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

With no annotations, the description fully explains behavior: returns eight scored areas, optionally filtered by slug, and mentions the framework's origin (talks). It is transparent about what the tool does and its scope.

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 sentences, no wasted words. The first sentence delivers the core purpose; the second adds optionality and practical context.

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 retrieval tool with one optional parameter and no complex output schema, the description is complete enough. It explains the return value structure and the tool's relevance, though it could mention that the output is static.

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 description adds meaning by explaining the slug parameter with an example ('cognitive-bias-resistance') and the result of omission (full rubric). This goes beyond the schema's generic description.

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 returns a specific resource (the Ray Group DeFi UX rubric) with a specific verb ('Returns'), and distinguishes it from sibling tools like get_glossary_entry and get_pattern by focusing on the rubric's role in audits.

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 explicitly advises using this tool to 'ground UX assessments in a published, opinionated framework rather than generic advice,' providing a clear when-to-use context. It does not explicitly state when not to use it compared to siblings, but the context is strong enough.

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