Get Tweet

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

Annotations already declare readOnlyHint=true, destructiveHint=false, idempotentHint=true, and openWorldHint=true. The description adds behavioral context by mentioning the use of the FxTwitter API, the output format options (markdown/json), and the return data structure including author info, media URLs, and engagement stats. While it does not discuss rate limits or authentication, the combination of annotations and description provides sufficient transparency.

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 structured and front-loaded: first sentence states purpose, followed by paragraphs for arguments, returns, examples, and notes. Every sentence adds value without redundancy. It is appropriately sized for the tool's complexity.

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 absence of an output schema, the description provides a good overview of return data (author, text, media, engagement, polls, quote tweets). It also notes limitations. However, it could be more precise about the exact fields and nesting structure, leaving some ambiguity for agents that need strict parsing guidance.

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 100% schema description coverage, the description adds significant meaning beyond the schema: it explains that `url` can be a tweet URL or ID and provides examples; for `response_format`, it clarifies the two options and their purposes. The 'Returns' section elaborates on the output, compensating for the lack of an output schema.

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 that the tool fetches a single tweet with all its content, including text, media, polls, and engagement metrics. It distinguishes from sibling tools by noting that it does not fetch replies and directs users to `tweetsave_to_blog` for complete blog post formatting.

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 on when to use: to retrieve a single tweet. It also specifies what not to use it for (fetching replies) and offers an alternative tool (`tweetsave_to_blog`) for related tasks. Examples of input formats (URL or ID) further clarify usage.

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