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

Annotations already declare read-only and idempotent behavior, so the bar is lower. The description adds valuable context: the operation is an 'estimate' (implying approximation) and it 'warns about truncation risk'. This goes beyond the schema and annotations without contradicting them.

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 two sentences, front-loaded with the most important action, and contains no filler or redundant repetition of annotations. Every word contributes to understanding the tool's 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?

Given the tool's moderate complexity, full schema coverage, and presence of an output schema, the description sufficiently covers inputs, purpose, and key behavior. It does not need to describe return values because the output schema handles that, and it adequately sets expectations about estimation and warnings.

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 description coverage is 100%, so the baseline is 3. The description repeats the message structure already present in the schema and does not add new parameter details. It provides no additional syntax or format guidance beyond what the schema already documents.

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's function with specific verbs ('estimate', 'check', 'warns') and names its resource (message array and target model's context window). It distinguishes itself from siblings like count_tokens by adding the context-window fit check and truncation warning.

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 implicitly communicates when to use the tool (when you need to estimate token usage and verify context fit), but it does not explicitly name alternatives or exclusions. Given the clear context stated, this meets the 'clear context, no exclusions' level.

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