ReftrixMCP

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

Annotations already indicate read-only and idempotent behavior. The description adds valuable context by specifying the exact detection types (coverage, anomaly, drift) and target models (DINOv2/e5-base), but does not disclose what data structure or format the tool returns.

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 bilingual description is efficiently structured with zero waste: the first sentence defines the action, the second enumerates specific operations and models. Every clause serves a purpose.

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?

While parameters are fully documented in the schema and annotations cover safety, the description lacks completeness due to the absence of an output schema. It should describe what quality metrics or report structure users can expect as a return value.

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?

With 100% schema description coverage, the baseline is 3. The description does not add semantic meaning beyond the schema (e.g., explaining the trade-offs between 'sections' vs 'parts' scope, or when to enable distribution statistics).

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 monitors embedding quality and performs specific operations (coverage, anomaly detection, drift detection) on specific models (DINOv2/e5-base). However, it does not explicitly differentiate this from sibling tools like `quality.evaluate` or `page.analyze`.

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 provides no guidance on when to use this tool versus alternatives such as `quality.evaluate` or `audit.query`, nor does it mention prerequisites like requiring existing embeddings to analyze.

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