get_insights

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 mentions the prerequisite (synced data) which is crucial context, but doesn't describe other important behaviors: whether this is a read-only operation, what the output format looks like (tabular data? JSON structure?), whether there are rate limits, or what happens with large result sets. The description adds some value but leaves significant behavioral aspects unspecified.

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 efficiently structured: it starts with the core purpose, immediately lists all insight types (essential information), provides helpful parenthetical explanations for key insights like 'opportunities', and ends with the critical prerequisite. Every sentence earns its place, and the information is front-loaded with the most important details first.

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 the tool's complexity (11 parameters, no output schema, no annotations), the description is incomplete. While it covers the purpose, insight types, and prerequisite well, it doesn't address the output format, result limitations, or behavioral characteristics needed for a tool with this many parameters and analytical complexity. The agent would need to guess about the return structure and operational constraints.

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 schema description coverage is 100%, so the schema already documents all 11 parameters thoroughly. The description adds minimal parameter semantics beyond the schema - it lists the 16 insight types (which the enum already contains) and briefly explains the 'opportunities' insight. However, it doesn't provide additional context about parameter interactions or usage patterns that would help the agent beyond what's in the schema descriptions.

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: 'Run pre-built analytical queries against synced GSC data.' It specifies the verb ('run'), resource ('pre-built analytical queries'), and target data ('synced GSC data'). It also lists all 16 insight types, providing specific differentiation from sibling tools like 'query_gsc_data' (which likely runs custom queries) and 'get_overview' (which might provide general metrics).

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 explicit usage guidance: 'Requires synced data — run setup first if needed.' This tells the agent when NOT to use this tool (if data isn't synced) and what alternative to use first ('setup'). It also implies this tool is for analytical insights rather than raw data queries, distinguishing it from siblings like 'query_gsc_data'.

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