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

Annotations already cover read-only, idempotent and closed-world, so the bar is lower; the description still adds real value by disclosing the scoring method, the meaning of each state label, the sampling limits (5 rows, first 3 ETFs per state list) and the caveat carried in the payload's `reading` field. It does not describe pagination, freshness beyond 'morning read', or how to obtain the full dataset, which keeps it from 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?

The opening question front-loads the purpose well, but the second sentence largely repeats the first ('Where the money is moving' vs 'Sector and macro ROTATION map showing where the money is going'). The remaining content is one long semicolon-chained run-on that packs dense and useful facts but is harder to scan than it needs to be.

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 parameters, no output schema and read-only annotations, the description carries most of the burden and does so: it explains the universe, the scoring, the labels, the truncation and the interpretive caveat. The missing piece is a clear statement of how this snapshot relates to the live variant and to the preceding top-down step.

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 of 4 applies. The description correctly implies a no-argument call and spends its space on output semantics instead, which is the right trade-off here.

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 concrete resource and scope: a sector/macro rotation map covering ~50 sector ETFs and macro-book instruments, each scored on its ratio to SPY versus that ratio's 50-day, bucketed into GO/HOLDING/TURNING/OUT. That is far more specific than the name alone. It never names a sibling, though, and the only differentiation from get_rotation_live is an oblique reference to 'the morning read', so it stops short of a 5.

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 places the tool in a workflow ('the second step of a top-down read') and explicitly warns about misuse ('A state map, not a buy list', 'confirmed rotation is late for a pullback buyer'). What it lacks is an explicit statement of when to prefer get_rotation_live or the first-step read instead, so the guidance is clear but not complete.

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