Analyze Tone

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

No annotations exist, so the description carries the burden; it does usefully signal that the tool is advisory ('sugere reformulações') rather than rewriting the text, and lists what it flags. However it does not state whether it works only on Portuguese text, whether there are length limits, or how findings are reported, which matters for a zero-annotation tool.

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?

A single front-loaded sentence followed by four tight bullets, each of which adds distinct, non-redundant information. Nothing repeats the name or title.

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?

An output schema exists, so return-value explanation is not needed, and the detection list covers the core behavior well. The main remaining gap is language/scope constraints and the absence of any routing guidance among the many sibling tools.

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 one parameter ('text') at 0% schema description coverage; the description implies it should be academic prose but never says so explicitly or mentions language, format, or size expectations. The bullet list explains what is analyzed more than what to pass in.

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?

States a specific verb and object ('analisa o rigor científico e a impessoalidade da escrita acadêmica') and enumerates the exact phenomena detected (first person, unsupported value judgments, colloquialisms, uncited paragraphs). This clearly separates it from siblings like validate_citations or check_structure, which address different concerns.

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 implied by the domain (academic writing review) but there is no explicit statement of when to call this versus check_structure, validate_citations, or audit_research_spec, nor any exclusion criteria. An agent must infer the placement in the workflow.

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