get_all_user_posts

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

With no annotations, the description must cover behavioral traits. It describes retrieving posts but does not disclose side effects, authentication needs, rate limits, pagination behavior, or what 'contextualized' means. It implies a read operation but lacks necessary detail.

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 with a clear first sentence and uses bullet example queries. It is front-loaded and efficient, though the examples could be integrated more tightly.

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 the tool has 5 parameters, no output schema, and no annotations, the description is incomplete. It lacks details on return format, pagination, rate limits, and what 'contextualized' entails, which are needed for effective usage.

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 description coverage is 100%, so baseline is 3. The description does not add meaning beyond the schema for parameters like username, platform, simple, limit, offset. No extra value or deficiency.

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 verb 'retrieve' and the resource 'all contextualized post renderings of a specific Twitter/X user'. It distinguishes from sibling tools like 'search_relevant_posts' by focusing on a single user's all posts.

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 usage context with example queries ('What topics does @elonmusk tweet most about?') and states it's for analyzing posts for insights. However, it does not specify when not to use or explicitly contrast with sibling tools.

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