content_recommendations

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

With no annotations, the description carries the full burden of behavioral disclosure. It explicitly instructs the agent to base analysis only on returned data, report exact numbers, avoid speculation, and acknowledge insufficient data. This is strong behavioral guidance beyond simple function, covering data fidelity and uncertainty handling.

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 longer than two sentences, but each section earns its place: purpose, output types, behavioral constraints, and presentation format. It is well-structured with clear sections, though the presentation details add length. No waste, but slightly verbose.

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?

The description covers what the tool returns (prioritised actions), behavioral guardrails, and presentation requirements. It lacks detailed return structure, but no output schema exists, and the description provides sufficient context for a tool of this complexity. The explicit presentation instructions add completeness.

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 100%, so both parameters (days, max_recommendations) are already documented. The description does not add additional semantic detail about parameter usage or effects beyond the schema, so the baseline score of 3 is appropriate.

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 what the tool does: 'Get actionable content recommendations by cross-referencing quick wins, content gaps, and cannibalisation data.' It names the specific data sources, distinguishes it from sibling tools like quick_wins or content_gaps, and describes the output categories (pages to update, content to create, pages to consolidate).

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 usage by cross-referencing multiple data sources, positioning it as a combined-recommendations tool versus individual sibling tools. Though it doesn't explicitly state when not to use it or name alternatives, the context is clear enough for an agent to infer appropriate scenarios.

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