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

Annotations already cover the read-only/idempotent safety profile, so the description is free to add the behavior that actually matters: the exact content of each mode, the important caveat that station-wide purity does not prove a specific model or group is genuine, and the explicit list of content that is omitted. That purity caveat is real decision-relevant behavior not derivable from any structured field.

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 long but front-loaded and earns most of its length, leading with the two-mode split before detail. The single dense paragraph is heavier than ideal — the model-mode clause and the purity warning could be broken out — but there is 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 no output schema, the description carries the full burden of describing return values and does so for both modes, including named fields (selectedModelDirectlyVerified, actualModelSeen, detectedAt) and the markdown report's sections. For a four-parameter read tool this is complete enough to call correctly.

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%, so all four parameters including the locale enum are already documented in the schema itself. The description reinforces the model/group coupling and the consequence of passing model, but adds little syntactic or semantic detail the schema lacks — 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 verb and resource — an OkkMax report for one relay station — and immediately splits it into two distinct output modes (full markdown vs. compact per-model JSON). An agent can tell exactly what this returns and how it differs from search_stations or get_model_board without opening the 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?

It gives explicit conditional guidance: pass model when the user cares about a specific model, group only in combination with model, and take the slug from search_stations. It also states exclusions (promotions, invitation codes, invite links). It stops short of routing the agent away from this tool toward siblings like get_model_board or find_cheapest_relay.

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