assess_book

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

With no annotations provided, the description carries full behavioral burden and handles it well. It explicitly warns not to compute own figures, not to extrapolate past the coverage window, and explains how to interpret `sufficient: false`. It also explains why only complete months are averaged, giving concrete reasoning about partial-month distortion.

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 front-loaded with the core purpose and follows with a useful list of output categories and important behavioral constraints. It is slightly repetitive ('Read this and report it' near 'Do NOT compute your own figures'), but every section earns its place and the length is appropriate for the complexity.

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?

The tool takes no parameters, so the main need is clarity about what the agent should expect and how to handle edge cases. The description covers outputs, constraints, and the meaning of sufficient: false. It could be even stronger with a one-line statement about when to choose this over generate_report or balances, but the absence of parameters and presence of an output schema make this sufficient.

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 is empty (0 parameters), so there are no parameter semantics to clarify. The description adds meaningful information about what the tool produces, which compensates for the lack of any input surface. No parameter documentation is needed here.

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: 'Review the book and return COMPUTED facts about it as JSON' and enumerates the specific fact categories (coverage, income/expense, runway, category shares, etc.). It does not explicitly differentiate from siblings like get_ledger or balances, but the emphasis on 'computed facts' and the listed outputs make the tool's role distinct enough.

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 implies this tool is for retrieving pre-computed assessment facts rather than raw ledger data or user-computed figures. However, it never explicitly says when to choose this over siblings such as get_ledger, balances, or generate_report, nor does it state exclusions like 'use balances for raw account balances instead'.

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