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

With no annotations, the description carries the full burden. It valuably discloses that the analysis is rules-based, deterministic, and uses no LLM, and it names the output components. However, it does not state side effects, permission requirements, or return format details beyond the score range and counts.

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: it states the score output, the supporting outputs, the deterministic method, and the input in three short fragments with no waste.

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?

For a simple one-parameter analysis tool with no output schema and no annotations, the description covers the core purpose, method, and output shape well enough to call it correctly. The main missing piece is clarifying its relationship to the sibling aitells_report.

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?

There is only one parameter, and schema description coverage is 100%, so the schema already documents that 'text' is the text to analyze. The description adds no semantic detail beyond restating the input, which is the baseline 3 case.

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 that the tool produces an AI-writing-tells score from 0-99 plus a verdict and counts, which is a specific analysis operation. It does not explicitly differentiate itself from the sibling aitells_report, so it stops 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 only says 'Input: text to check', which is invocation detail rather than usage guidance. It gives no indication of when to use this tool instead of aitells_report or other siblings, and no exclusions.

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