Connection and graphs

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

Annotations already declare readOnlyHint=true, destructiveHint=false, openWorldHint=true, so the safety profile is covered. The description adds useful context that this is a connection-confirmation step and that graph_id defaults to the primary graph, but says nothing about latency, permissions required, or failure behavior if the connection is broken.

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?

Front-loaded with the purpose, then the field list, then the actionable 'Good first call' guidance in priority order. Every clause carries information; no 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?

With zero parameters and an output schema already covering the return shape, the description only needs to say what the call is for and why an agent should make it. Both are answered, plus the graph_id handoff detail that makes downstream calls correct.

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 tool takes zero parameters, so the baseline of 4 applies; the schema cannot be missing anything. The graph_id note refers to sibling tools' arguments rather than this tool's own input, so it adds cross-tool clarity but no local parameter detail.

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?

Names a specific verb and resource ('Report the connected Tableau site and its knowledge graphs') and enumerates the returned fields (server URL, site, product version, auth method, availability flag, and per-graph id/name/status/is_primary). An agent can distinguish it from siblings like graph_health or search_nodes without opening any 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?

Explicitly frames itself as a 'Good first call' and explains how its output feeds other tools ('gives the graph ids the other tools accept as graph_id'), including the default when graph_id is omitted. No when-not conditions or named alternative diagnostics (e.g., graph_health) are given, so it falls short of a 5.

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