dsp_thresholds

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

No annotations are provided, so the description carries the full disclosure burden. The zero-parameter shape makes mutation risk effectively nil, so the practical gap is small, but the description never confirms this is a static reference lookup with no side effects, nor whether the target values are current or illustrative ('Indicative' suggests the latter but is ambiguous).

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?

A single efficient sentence with the resource and its payload front-loaded. The trailing ellipsis and unexplained 'Fantastic' label slightly weaken precision, but there is no padding.

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?

For a simple zero-param reference tool with no output schema, the description should convey the shape of the return (a metric-to-target mapping, presumably) and what the acronyms stand for. It gestures at this but leaves the return structure and the tier concept ('Fantastic') unexplained.

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?

The tool takes zero parameters, so there is nothing for the description to disambiguate; the baseline of 4 applies. The listed acronyms add framing but no parameter-level meaning is needed or missing.

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?

It says the tool surfaces Amazon DSP scorecard metrics and their target values, and lists representative acronyms (DCR, POD, DSC, DNR, LoR). But the verb is implicit and the qualifier 'Fantastic targets' is undefined jargon that an agent can't interpret without prior context. Nothing distinguishes it from siblings like explain_metric or pnov_benchmark.

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?

No statement of when to call this versus explain_metric (definitions) or pnov_benchmark (benchmarks), even though those siblings overlap conceptually with 'metrics and targets'. There are no exclusions or preconditions at all; usage must be inferred from the one-line purpose.

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