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

Annotations already establish this is a read-only, idempotent, closed-world computation with no side effects, so the safety profile is fully covered. The description adds two genuine traits beyond that: it emits a warning when the budget exceeds the model context window, and it supports 25+ models. It does not say how estimates are derived or how the total is reported, but with an output schema present that gap is minor.

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?

Three short sentences, front-loaded with the core allocation-planning purpose, followed by the warning behavior and model coverage. Nothing is redundant with the name and every sentence carries 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?

With annotations covering side-effect safety, full schema coverage, and a declared output schema, the definition covers what an agent needs to decide and call correctly. The only real gap is how the four buckets interact with the raw-text vs. token-count parameter pairs, which is left to the schema.

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 all eight parameters (model, three raw-text inputs, three token-count inputs, expected output) are already documented in the schema. The description's enumeration of buckets roughly mirrors those parameters and adds no format, precedence, or mixing guidance (e.g., raw text vs. pre-computed tokens), so the baseline 3 is appropriate.

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 names a specific verb (plan) and resource (token allocation) and enumerates the four budget buckets it covers, plus an overflow-warning behavior. It is clear what the tool does, though it never explicitly distinguishes itself from close siblings like count_tokens, context_window_check, or estimate_llm_cost.

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?

Usage is only implied: the word 'plan' suggests pre-flight budgeting before constructing a prompt, and the warning behavior hints at validating a proposed allocation. There is no explicit when-to-use, when-not-to-use, or 'use X instead when you only need Y' routing against the many sibling token/cost tools.

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