get_lightning

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

The description discloses that GLM detects total lightning from GOES-East with 20-40 s latency, and it explains the output composition. Without annotations, this provides reasonable transparency, though it could detail data freshness limitations or edge cases.

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 mostly concise, with two sentences that front-load the purpose. The first sentence is somewhat long but packs necessary information. Minor redundancy could be trimmed.

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 presence of an output schema (not shown), the description adequately covers the tool's functionality: output fields, source, latency. It provides enough context for an AI agent to use the tool correctly, though parameter details are sparse.

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 0% schema description coverage, the description must add meaning. It mentions 'radius_km' and 'minutes' as time window parameters but does not clarify lat/lon or provide format details. The default values are in schema but not explained in description.

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 GOES GLM total-lightning activity near a CONUS point, listing specific output fields such as flash count, rate, nearest strike, and a tiered safety interpretation. It is distinct from sibling tools, which focus on other weather phenomena.

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 implies real-time use with 'recent window' but does not explicitly state when to use this tool versus alternatives like get_threat_brief. No exclusion criteria or context for selection are provided.

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