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

Annotations already communicate readOnlyHint=true and destructiveHint=false Mend the description adds useful semantics: zeros represent empty scopes)Skip and counts represent rows, not quality. This extra context helps the agent interpret results correctly and goes beyond what the annotations alone provide.

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 function, then adds usage context and an important interpretation caveat. Every sentence earns its place and there is no redundancy or filler.

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?

With no parameters, clear annotations, and a short description explaining return semantics, the tool is mostly self-sufficient. The only small gap is that 'layer' and 'scope' are domain-specific and are not formally defined, but the surrounding sibling names and the description's examples make their meaning reasonably inferable.

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 has zero parameters and the schema is fully covered, so the baseline is 4. The description mentions 'per layer and per scope' and 'scope' but does not need to define parameters because none exist. No parameter documentation gap exists for the agent.

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 states that the tool returns real counts per layer and per scope, with zeros for no data. That is a clear, specific function. It does not explicitly name sibling tools like read_facts or read_hypotheses to differentiate itself, so it falls just short of a 5.

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 a concrete use case: check counts before writing so you know whether a scope already has facts or hypotheses. It also warns that counts are about quantity, not quality. It does not explicitly point to which sibling tool to use instead for actual content, so some guidance is implied rather than named.

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