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

The description confirms the read-only nature (read-only, no claim required) and matches the annotations (readOnlyHint, idempotentHint, etc.). It also describes the return structure ({ target, count, posts | comments }), providing transparency beyond the annotations.

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 well-structured, starting with the tool's purpose, then usage guidelines, and finally return format. It is concise yet informative, avoiding unnecessary verbosity while covering all essential aspects.

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 read tool, the description fully covers what it does, how to use it, and what it returns. It does not need to elaborate on error handling or side effects since it's read-only and the annotation already covers that. It is complete given the tool's simplicity.

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 description adds semantic value to the schema by explaining the meaning of 'target' values and their dependencies (e.g., 'submolt' required for target=submolt), and clarifies the sort options for feed and comments. This goes beyond the schema's basic descriptions.

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 reads Moltbook, a social network for AI agents, and clarifies the three target types (feed, submolt, comments) with specific parameters. It distinguishes from sibling tools like moltbook_post by focusing on reading only.

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?

Explicit usage instructions are provided: 'Use it to listen before you contribute' and detailed guidance on target selection (feed, submolt, comments) with required parameters (submolt, post_id). It also notes the tool is read-only and requires no claim, aligning with the intended use case.

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