gsc_content_recommendations

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

With no annotations provided, the description carries the full burden of behavioral disclosure. It goes beyond a simple description by specifying important usage rules: 'Base your analysis ONLY on the data returned', 'Report exact numbers', and 'Do not speculate about causes... unless the data explicitly supports it.' It also mandates a specific presentation format, which is a behavioral trait that greatly aids an agent in delivering consistent results.

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 typical but is well-structured into purpose, output, analysis rules, and presentation rules. The first sentence immediately conveys the core function, and each subsequent section adds necessary guidance. The presentation section is detailed but earns its place for a tool that expects rich visual output. Slight verbosity prevents a perfect 5.

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?

There is no output schema, so the description must convey what the tool returns. It does so by listing 'pages to update, content to create, and pages to consolidate.' It also addresses how to handle insufficient data. However, it lacks specific details on result ordering, default behavior when parameters are omitted (although schema provides defaults), or any potential limitations, which keeps it from a 5.

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 input schema already documents all three parameters (days, dataset, max_recommendations) with 100% coverage. The description adds no parameter-specific meaning, such as examples or expected values, beyond what the schema provides. Therefore, 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 the tool's purpose: 'Get actionable content recommendations by cross-referencing quick wins, content gaps, and cannibalisation data.' It uses a specific verb and resource, and distinguishes itself from sibling tools like gsc_quick_wins and gsc_cannibalisation by explicitly combining these data sources. The output is also well-defined: 'prioritised actions: pages to update, content to create, and 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 provides clear context for when to use the tool: when integrated content recommendations are needed, not just raw data. It mentions cross-referencing multiple data sources, which implies it should be selected over individual data source tools. However, it does not explicitly state 'use this instead of X' or list exclusions, so it falls short of a perfect 5.

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