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

Annotations already declare readOnly, idempotent, and non-destructive hints, so the safety profile is covered. The description adds meaningful behavioral context beyond that: the paid-key requirement for the transition thesis and the specific signal criteria (BUILD verdict, excess-power headroom, time-to-power). It does not cover pagination or error behavior, but that is not critical here given the annotations and output schema.

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 longer than average but every sentence carries signal: scope, return contents, paid-key caveat, positioning, examples, and exclusions are all present without fluff. It front-loads the core value proposition and uses a clear structure. A pure 5 would require slightly more compression, but this is well within acceptable density.

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?

Given the output schema exists and the annotations cover safety, the description is complete for selection and invocation. It explains the use case, the output components (markets, ISO rollup, leaderboard, optional thesis), the paid-key condition, and what it is NOT for. The only minor gap is lack of detail about response size or shape, but that is covered by 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?

With 100% schema description coverage, both parameters are self-documenting in the schema. The description adds one practical example (max_months=24) but no additional semantic nuance beyond what the schema already provides. Baseline mid-range is appropriate.

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 verb ('Returns') and a clearly defined resource ('US markets + ISOs with the strongest near-term emergence signal'), and immediately distinguishes it from siblings by naming what it is not ('current ISO queue snapshot', 'present-day market ranking'). This leaves no ambiguity about the tool's forward-looking scope.

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?

The description explicitly spells out when to use it ('where should I be looking next', 'which market is about to become buildable'), provides a concrete invocation example ('Try: grid_transition_radar max_months=24'), and explicitly excludes alternatives with pointers ('use get_interconnection_queue', 'use rank_markets'). This is the gold standard for usage guidance.

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