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

With no annotations, the description clarifies that this is a pure computation producing a score, label, and saturation value from supplied numbers. It does not disclose the scoring thresholds, handling of missing optional parameters, or return structure, which leaves some behavior implicit.

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 a single dense sentence that front-loads the primary output and includes all relevant inputs. The 'Wave 5 N.4 —' prefix is process metadata that adds little, but the body is concise and free of filler.

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 no annotations, no output schema, and 0% schema coverage, the description should explain label thresholds, the nature of market_saturation, and the return shape; it does not. It is enough to locate the tool but not enough to fully predict its behavior or validate results.

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 description coverage is 0%, so the description must carry parameter semantics, but it mostly restates the names: avgCpcUsd, totalMonthlySpendUsd, and optional competitorBidders + competition. It adds the dataforseo_ad_traffic source and optionality, yet does not explain how competition or competitorBidders influence the score or what valid units/meanings are beyond 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?

The description identifies a specific computation — ppc_spend_score (0–10) plus label (STRONG/CONFIRMED/WEAK/ABSENT) and market_saturation — and names the input source. This distinguishes it from the sibling compute_* tools by PPC context and concrete outputs.

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?

It gives clear invocation context: feed numbers from dataforseo_ad_traffic and use the PPC traffic projection parameters. It does not explicitly exclude alternative compute_* siblings, but the PPC-specific language is enough to route an agent.

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