optimize_headings

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

No annotations provided, so description carries full burden. It states the tool analyzes and suggests improvements, which implies non-destructive behavior. However, it does not disclose any additional behavioral traits such as authentication needs, rate limits, or whether it modifies content. Returns are mentioned but not deeper behavior.

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?

Two sentences with no wasted words. Efficiently communicates purpose and outputs. Front-loaded with key 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 100% schema coverage for two simple parameters and no output schema, the description adequately explains return values (headings, issues, recommended outline). No missing context for this straightforward tool.

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 coverage is 100% with descriptions for both parameters (content and keyword). The description adds no new meaning beyond the schema; it just mentions analyzing heading structure. Baseline score of 3 is appropriate as schema already documents parameters.

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 analyzes heading structures, suggests improvements, and returns specific outputs including current headings, issues, and a recommended outline. It distinguishes from sibling tools like 'analyze_keyword' which focuses on keywords, and 'check_readability' which checks readability.

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 usage when heading structure improvement is needed, but does not explicitly state when to use versus alternatives. Sibling tools are listed but not compared. Provides clear context but lacks exclusion criteria.

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