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

Annotations already declare readOnlyHint=true and destructiveHint=false, so the safety profile is covered. The description adds valuable behavioral context beyond annotations: the data source (GEM Global Integrated Power Tracker), coverage scale (182,000+ geolocated units, 170+ countries), per-unit attributes (fuel, MW, status, start year, operator/owner, lat/lng), and the return shape (summary by fuel/status plus largest units). This goes beyond what annotations alone convey.

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 every section earns its place: scope, fuel coverage, data provenance, filter semantics, return values, example query, and sibling exclusions. It is front-loaded with the primary use condition. Slightly dense, but for a 7-parameter global-coverage tool with several sibling rivals, the length is justified.

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?

For a tool of this complexity — 7 optional parameters, global scope, multiple closely related siblings, and an output schema present — the description covers all decision-relevant context: primary use case, exclusion conditions with named alternatives, parameter semantics, data provenance, and expected outputs. Nothing an agent needs to select or invoke this tool correctly is missing.

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 the baseline is 3. The description adds genuine semantic value above the schema: it explains pipeline=true as 'JUST the forward set: announced + pre-construction + construction', that fuel is a 'comma-union', and demonstrates parameter interaction with 'get_global_power country=India pipeline=true'. This enriches the bare schema field descriptions.

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+resource (retrieve the Global Energy Monitor Global Integrated Power Tracker asset inventory) and precisely scopes it: WORLDWIDE/non-US, operating plus forward pipeline, all fuels. It distinguishes itself from siblings by name (get_grid_intelligence, get_grid_scoreboard, get_power_pipeline) with an explicit do-not-use boundary, so an agent can select it correctly without ambiguity.

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?

Provides explicit when-to-use guidance ('Use when a user asks about power plants/units WORLDWIDE or in a NON-US country') and explicit when-not-to-use with named alternatives ('Do NOT use for US grid telemetry/headroom (use get_grid_intelligence / get_grid_scoreboard) or the US planned-generator feed (use get_power_pipeline)'). Also supplies a worked example query, leaving nothing to inference.

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