draft_reply

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

With no annotations provided, the description carries the burden of explaining behavior. It discloses that the tool analyzes a tweet, matches the user's writing style, returns a draft only, never posts automatically, and requires a ShipPost API key. This is solid transparency, though rate limits and error behavior are not mentioned.

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, and avoids unnecessary length. There is minor redundancy between 'in your voice using AI' and 'matches your writing style,' but the API key requirement and draft-not-post warning are useful and earned.

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's low complexity, full schema coverage, and presence of an output schema, the description is largely complete. It covers purpose, key behavior (draft-only), and authentication. Slightly more context about how it relates to draft_tweet/draft_thread would make it fully complete.

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 the schema already explains tweet_id, tweet_text, and tweet_author. The description adds no additional parameter-level detail, which is acceptable because the schema does the heavy lifting; baseline 3 is appropriate.

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 uses a specific verb+resource pair ('Draft a reply to a tweet') and clarifies the AI voice/style behavior. It distinguishes itself from reply_to_tweet by explicitly noting this returns a draft and does not post, and from tweet/thread drafting tools by focusing on replies.

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 gives clear usage context: use this to generate a draft reply, not to post it. It explicitly says 'Use reply_to_tweet() to post,' which is a named alternative. However, it does not fully explain when to choose this over other drafting tools like draft_tweet or draft_thread.

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