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

Annotations already establish readOnlyHint=true, destructiveHint=false, and openWorldHint=false, so safety is covered; the description adds the actual diagnostic surface (size, fact count, session status, last read). It does not discuss historical range, rate limits, or behavior when no context has ever been saved, which is the main remaining gap.

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 plus a short exclusion clause, with the trigger condition front-loaded before the do-not guidance. Every clause earns its place and nothing is repeated from the schema or annotations.

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?

There is no output schema, so the description must carry the return payload, and it does: context size, number of saved facts, session status, and last read time. Combined with the zero-parameter schema and read-only annotations, an agent has everything needed to call and interpret this tool.

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 tool takes zero parameters, which is the correct baseline of 4; the description implicitly confirms it is a pure diagnostic call requiring no inputs. There is nothing further to document.

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?

States a specific diagnostic verb (verify delivery) plus exactly what is reported: context size, saved fact count, session status, and last-fetch time. It explicitly distinguishes itself from the sibling get_brand_context, which reads the context itself, so an agent can separate the two without opening schemas.

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?

Names concrete trigger conditions (user asks whether Nokbase is working, whether saved context reaches their AI tools, or when it was last read) and adds an explicit when-not clause routing to get_brand_context. Nothing is left to inference.

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