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

Annotations already declare readOnlyHint, idempotentHint, non-destructive, and closed-world, so the safety profile is covered. The description adds useful context beyond that: the OAuth-dependent behavior of modelId and a hint that this is the discovery step before refining axis ids. No limits or auth caveats beyond OAuth, hence not a 5.

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 the core action and payload contents, then the OAuth conditional. No wasted words; "Start here" is a terse but effective fragment.

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?

For a read-only, fully-annotated tool with 100% schema coverage and an output schema, the description covers everything an agent needs: what it returns, that it's the starting point, and the OAuth-dependent parameter behavior. Return-value details are correctly left to the output schema.

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% for the single optional modelId, and the schema already documents the OAuth-omission semantics. The description restates that behavior rather than adding new syntax or format detail, so the baseline of 3 for full schema coverage 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?

States a specific verb+resource ("Read a Hunchful collaboration model") and enumerates the payload contents: hunches with axis, pole, confidence, refinable axis ids, and connection info. It's clearly distinguishable from mutating siblings like add_hunch or apply_refinement, though it doesn't explicitly name an alternative.

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?

"Start here" positions the tool as an entry point, and the OAuth clause gives a concrete conditional (omit modelId to read the connected person's own model). It stops short of naming when NOT to use it or pointing to a specific alternative, so it's strong but not exhaustive.

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