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

Beyond annotations (readOnlyHint, idempotentHint), the description adds detailed behavioral traits: the tool never raises protocol errors on invalid input, returns a structured error object, and is always safe to retry. This provides valuable context not present in annotations alone.

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 concise, front-loaded with the core purpose, and every sentence adds meaningful information (usage, example, error behavior, safety). No unnecessary words or repetition.

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 tool with one parameter, read-only semantics, and a predictable output (example given), the description covers purpose, usage, error handling, and retry safety. It is fully sufficient for an agent to select and invoke this tool correctly.

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 a clear description of the 'text' parameter. The description adds example input format but no additional meaning beyond what the schema already provides. The baseline of 3 is appropriate since the schema carries the load.

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 checks a post against every major platform's length limit at once, listing specific platforms (X, LinkedIn, Instagram, etc.). It distinguishes itself from sibling tools like analyze_writing and reading_time by explicitly noting what it does not cover.

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 provides explicit guidance: 'Use before posting, to catch truncation. Not for readability (analyze_writing) and not for reading duration (reading_time).' It also explains error handling and that retries are safe, giving the agent clear context for when and when not to invoke this tool.

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