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

No annotations are provided, so the description carries the full burden. It usefully discloses negative constraints — it never chooses assets, amounts, wallets or timing — and explains when the `say` field is null versus populated, which is genuine behavioral context. It still omits return structure, permissions, and any freshness/pagination behavior, so it is helpful but incomplete.

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 core identity is front-loaded ('The shadow analyst scoreboard'), which is good, but the first sentence is a very long run-on and the `say` explanation is dense and jargon-heavy. Every clause is roughly relevant, but readability and structure suffer.

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, no annotations, and zero parameters, the description must convey the return shape. It gestures at the `say` field's structure ({ share, capPoints } and the 23-43% band / capPoints rule) but never lays out the overall response, so an agent knows the concept yet not the full payload. Adequate but with clear gaps.

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?

The tool takes zero parameters, so the baseline is 4. There are no parameters whose semantics the description could add to, and it correctly does not invent any.

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 identifies a specific resource — the shadow analyst scoreboard — and states exactly what it compares (an LLM's daily allocation call vs. the deterministic model alone and an even split). An agent can grasp what the tool yields. It does not, however, differentiate itself from the closely related sibling get_brain_vs_flat, which appears to cover a similar comparison, so the 'vs' framing is not fully disambiguated.

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?

There is no explicit when-to-use or when-not-to-use guidance, and no alternative is named (e.g., 'use get_brain_vs_flat for X instead'). The usage is only implied by the content description. An agent must infer the call context itself.

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