Analyze AI Tool Stack

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

Annotations already declare readOnly/idempotent/non-destructive/openWorld, so the safety profile is covered. The description adds genuinely new behavioral context: the analysis is derived from 'GateOnAI data only' and is explicitly non-prescriptive, which tells the agent how to interpret and caveat the 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?

Two sentences, no filler. The core capability (what observations are produced) is front-loaded, and the scope/caveat sentence follows. Every clause carries information.

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 an output schema present, return values need not be described. The description covers the data source limitation and the interpretive stance, which is what an agent needs before calling. Only the absence of routing guidance versus siblings keeps it from being fully complete.

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% and the schema already documents the slug list, min of 2 and max of 40, and slug format via example. The description's '2-40 GateOnAI tool slugs' merely restates the schema bounds, adding no syntax or sourcing detail beyond it. Baseline 3 applies.

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 names a specific analysis resource – a set of AI tools – and enumerates the three outputs it produces (tools not listed, category overlaps, data connections), which distinguishes it from compare_ai_tools and get_compatible_tools. It stops short of explicitly naming a sibling it is not, so it lands at 4 rather than 5.

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?

It frames the output as 'observations... not recommendations and not judgments', which implicitly tells the agent when this tool is appropriate (neutral gap-analysis) versus a recommendation tool. However, there is no explicit 'use this when X, use Y instead' routing guidance relative to the many siblings like search_ai_tools or find_ai_pipeline.

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