get_supplemental_context

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

Annotations already declare readOnlyHint=true, openWorldHint=true, and idempotentHint=false. The description adds useful latency/cost context by disclosing the cache check, 8 parallel outbound HTTP calls, and a categorization pass, which implies external fan-out and variable results. It stops short of stating return shape, rate limits, or failure behavior, so it earns moderate credit on top of the annotations.

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, front-loaded with sources, but the parenthetical about '1 memory cache check + 8 parallel outbound HTTP API calls + 1 5-bucket categorization pass' is implementation detail an agent cannot act on. It spends words on internal mechanics rather than on decision-relevant 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 no output schema and 6 parameters, the description should describe what comes back and in what form, but it says nothing about the return payload. Combined with missing usage guidance, it is not complete enough for an agent to invoke confidently despite annotations covering the safety profile.

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 the schema alone fully documents all six parameters including the tricky 'domain' exclusion rule. The description adds no parameter-level detail, making the baseline 3 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 verb ('fan-out pulling') and resource ('real-time economic data from 80+ institutional sources') are stated concretely, so the mechanical operation is graspable. However, the purpose is framed around internal architecture rather than an agent-facing task, and it never clarifies what 'supplemental' context means or how it differs from siblings like get_domain_intelligence or search_statistics. That ambiguity keeps it at a vague-purpose 3.

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 contains no when-to-use, when-not-to-use, or alternative-selection guidance. Nothing tells the agent which query types should route here versus the many intelligence/search siblings. Only the parameter docs hint at usage, and those are not part of the description.

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