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

Annotations already declare the tool read-only, idempotent, and non-destructive. The description adds meaningful behavioral detail: it uses cl100k_base (~4 chars/token), can optionally keep the end, and reports whether truncation occurred along with an estimated token count. This goes beyond the annotations and provides transparency about the operation's output semantics.

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 three sentences with no filler. It front-loads the main purpose, then covers the optional behavior, and finally states what the tool reports. Every sentence contributes useful information.

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 modest complexity and the presence of an output schema, the description covers all essential aspects: purpose, tokenization basis, optional direction, and output reporting. It is complete enough for an agent to select and invoke the tool correctly without further clarification.

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 input schema already has 100% parameter coverage, providing descriptions for input, from_end, and max_tokens. The description adds extra meaning by explaining cl100k_base tokenization and the practical reason for using from_end (keeping recent history), which helps the agent understand how to use the parameters effectively.

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 opens with a specific verb and resource: 'Truncate text to at most N tokens' and clearly states the goal of avoiding exceeding an LLM context window. It also distinguishes itself from sibling tools like count_tokens and token_budget_calculator by focusing on the action of truncation rather than counting or budgeting.

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 clearly states the primary use case ('to avoid exceeding an LLM context window') and adds a practical scenario for the optional from_end flag ('useful for keeping recent conversation history'). It does not explicitly name alternatives or state when not to use the tool, but the context is clear enough for an agent to decide appropriately.

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