novada_traffic_daily

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

Annotations show readOnlyHint=true, describing a safe read operation. Description adds significant context: parallel fan-out, partial failure handling, return structure (total_mb, per-product, error flags), and the typo parameter behavior. No contradiction.

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?

Well-structured with sections (main action, best for, returns, params, auth). Each sentence is informative; a minor reduction in length would be possible but current length is justified.

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?

Despite no output schema, description fully explains return values (total_mb, per-product, error flags) and handling of partial failures. Covers all essential aspects for a traffic aggregation tool.

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 description adds defaults (7 days ago, today), typo behavior ('emits both start_time AND strat_time'), and optional products subset. This meaningfully extends the schema.

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?

Clear verb ('aggregate') and resource ('daily traffic consumption') with specific scope ('across all 5 Novada proxy products in PARALLEL'). Distinguishes from siblings by mentioning fan-out to multiple endpoints.

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?

Explicit best-for use cases: 'How much have we spent on proxies in the last N days?' and dashboarding. Also explains partial failure behavior, but does not explicitly state when not to use.

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