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

Annotations only cover read-only and open-world, but the description adds consequential behavior: real-time data requires Pro while free access is delayed 24h and withholds the thesis, the feed is identical and impersonal for every subscriber, and filters only select rows rather than personalize them. It also discloses the informational/not-advice framing. This is exactly the kind of context annotations cannot carry.

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 use case, then the payload, then the access/latency caveats — a sensible order with no filler sentences. The quoted marketing-style trigger phrases and the final disclaimer slightly dilute density, so not a 5.

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 return-shape burden and does so by listing feed, tier, side, price, model probability, edge and link, plus the free-vs-Pro delay. Combined with full schema coverage on inputs, an agent has enough to call and interpret it; only pagination/cursor behavior around limit and since goes unstated.

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 four parameters (feed, limit, since, min_tier) are already fully documented with enum values and defaults; baseline is 3. The description's 'filters only select' adds a useful semantic hint (filtering narrows, never alters content) but does not add syntax or format detail beyond the schema.

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 states a specific resource (model-generated Kalshi alerts across weather/crypto/metals/oil/mispricing) and enumerates the payload fields, which clearly separates it from the calculator siblings (calculate_ev, kelly_size, bayes_update). The trigger phrases ('any edge on Kalshi', 'weather trade signals') are quoted rather than described, so the statement of purpose is a bit scattered but still unambiguous.

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 trigger conditions ('Use for "any edge on Kalshi" and "weather trade signals"'), so an agent knows the query shape that should route here rather than to the deterministic calculators. It never names a sibling or states when not to use it, which keeps it 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.