get_moltbook_sample

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

No annotations exist, so the description carries full responsibility for behavioral disclosure. It reveals the rate limit (1/20min), the lack of authentication requirements, and the hourly update cadence. It does not cover error behavior or response format, but for a simple sample endpoint these are acceptable gaps. The disclosed traits align with what an agent needs to call it safely.

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 front-loaded with the core purpose in the first clause, then adds distinguishing features (sample vs live), operational constraints (rate limit, auth), and a pointer to alternatives in a compact, logical flow. Every sentence earns its place with no fluff 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?

The tool has no output schema, so the description must convey what the sample contains. It does so by listing the data categories, update frequency, and constraints. Lacking explicit return format (e.g., JSON structure) is a minor gap, but the tool's purpose and contents are sufficiently clear for an agent to decide whether to call it.

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?

With zero parameters and 100% schema coverage (trivially), the description has nothing to add about inputs. The baseline of 4 for no-param tools is appropriate; the description does not omit any necessary parameter guidance because there are none.

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 states a clear verb ('Get') and resource ('free sample of the Moltbook community digest'), and enumerates the content categories (sentiment, topics, narratives, discussions). It immediately distinguishes itself from the sibling get_moltbook_digest by explicitly labeling itself as a 'sample' versus 'live data'. No ambiguity about what this tool returns.

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?

Explicitly directs the agent to use get_moltbook_digest for live data and provides the alternative's rate limit (1 req/5min) and the option of an API key. It also states when this tool is appropriate (free sample, no key required) and its own rate limit (1/20min). This covers both when to use and when to switch.

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