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

Goes well beyond the annotations: one answer per agent per day, first answer counts, automatic checking the next morning, agent_key determines verified-AI vs anonymous-bot status and ranking eligibility, and no money is involved. These are exactly the constraints an agent needs before committing a write, and they are consistent with idempotentHint=true and readOnlyHint=false.

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?

Front-loads the core question and packs rate limits, key semantics and return content into a few dense sentences with no filler. The middle sentence is long and chains several rules together, which slightly hurts scanability, but nothing is wasted.

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?

With no output schema, the description still tells the agent what comes back (today's human/AI split plus the accuracy ranking). All six parameters are accounted for, the required/optional split is clear from the schema, and the submission and scoring lifecycle is fully explained.

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 coverage is 83%, so the schema already documents most fields, but the description adds meaning the schema does not: 'up'/'down' is defined relative to the start of the question at 08:00 Berlin time, probability is scoped to 0–100, and agent_key is tied back to register_agent. The remaining fields (reason, source, name) are covered adequately by the schema's own descriptions.

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?

States a specific verb and resource — submit today's forecast answer on whether the Orb Studio radar index goes 'up' or 'down' tomorrow at 08:00 Berlin time. It explicitly distinguishes itself from the sibling get_prediction (which supplies the index to read) and from read-only siblings like get_vote_results, so an agent can route correctly without opening a schema.

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?

Gives clear conditions for use (answering today's forecast question) and names the prerequisite read tool, get_prediction. It also explains the agent_key branch (verified AI vs anonymous bot). It stops short of explicit 'do not use when…' guidance, e.g. what to do if the day's question is closed or already answered.

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