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

Goes well beyond the annotations (readOnly=false, idempotent=false) by disclosing the metered cost model, per-plan allowances, the unit-per-page+keyword accounting, the partial-result behavior when the cap is hit (finished gaps kept, cap_reached true), and the internal page-selection heuristic. This is unusually rich operational context for a mutation-style tool.

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?

Long but dense and front-loaded: purpose first, then cost model, then on-demand constraint, then selection heuristic, then dry_run/result guidance. Every sentence carries distinct information, though it could be trimmed slightly.

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?

No output schema exists, yet the description covers where results land (get_competitive_landscape -> content_gaps), the partial-cap caveat, and the cost, which is everything an agent needs to invoke and report correctly.

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%, so the baseline is 3; the description adds meaning by tying each analysis to a unit cost and clarifying that dry_run spends nothing while limit caps the pairs analysed. It reinforces rather than merely repeats 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?

States a specific verb and resource ('work out which topics rivals cover that this site's own ranking pages do not') and names where the output goes, distinguishing it from read/analysis siblings. An agent can tell what it does without opening the schema.

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 when-to-use: 'Deliberately on-demand — nothing computes gaps on a schedule, so call this when the user actually wants the answer.' It also directs the agent to run dry_run first and to fetch results later for free via get_competitive_landscape, naming the alternative consumer.

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