fetch_thread_history

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

With no annotations, the description fully discloses the tool's behavior: it looks up the tweet, finds conversation_id, retrieves all tweets in that conversation, and returns them chronologically. It also lists included fields per tweet. No mention of error handling or rate limits, but the core behavior is clear.

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 two sentences plus a brief list of included fields. It is front-loaded with the main purpose and structured logically.

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 simple single-parameter schema and presence of an output schema, the description covers the full process and expected output. It is complete for an agent to understand and invoke the tool correctly.

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?

Only one parameter (tweet_id) with full schema description. The description adds meaning by explaining how tweet_id is used (to find conversation_id and fetch the thread), going beyond the schema's basic definition.

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 retrieves the full conversation thread for a tweet, with specific steps (lookup tweet, find conversation_id, fetch all tweets chronologically). It distinguishes from siblings like search_tweets which do not provide thread context.

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 explicitly guides when to use: 'when the LLM needs to understand the context of a conversation, read previous replies, or analyze the full discussion flow.' It does not mention when not to use, but the guidance is sufficient.

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