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

Annotations already indicate read-only, idempotent, and non-destructive behavior. The description adds context by explaining that the tool returns time series data with annual and monthly options, and mentions the baseline. It does not contradict annotations and provides useful behavioral detail beyond what annotations convey.

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, consisting of three sentences that front-load essential information (data source, units, baseline), followed by options, use cases, and frequency explanation. Every sentence adds value without redundancy.

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 partially explains return values (annual and monthly formats) but does not detail the exact output structure (e.g., columns, units per row). The mention of 'seasonal' values is introduced but not clarified. Additionally, the historical date range (starting 1880) is implied by the start_year default but not stated.

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 100%, but the description adds value by elaborating on the frequency parameter (annual returns one row per year, monthly returns Jan-Dec per year) and mentions regions explicitly. This provides additional meaning beyond the schema 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?

The description clearly states the tool retrieves NASA GISTEMP surface temperature anomaly time series for a specified region and frequency. It mentions specific use cases like climate bets and cross-source checks, effectively distinguishing its purpose from siblings such as get_latest_anomaly.

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 suggests use cases for climate bets, trend comparisons, and cross-source checks. It explains the difference between annual and monthly frequencies, providing context for when each is appropriate. However, it does not explicitly state when to avoid this tool or mention alternative sibling tools.

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