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

Adds real context beyond the readOnly/idempotent annotations: credential behavior (Pipeworx platform key by default, optional caller-supplied _apiKey with the x-key header and a registration URL) and the days default shift (1 without dates, 30 with dates). Missing rate-limit or pagination/result-size caveats for a 300-day series.

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 purpose and metric scope, then usage rules, then credential note — each sentence earns its place. The final credential sentence is long but carries non-obvious operational information.

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?

No output schema exists, so the description compensates by naming the returned fields (fill %, TWh, injections, withdrawals, trend, gas day), and it handles the zero-required-parameter case by explaining scope defaults. Not fully complete on response shape or ordering of a multi-day series.

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 baseline is 3, but the description adds cross-parameter semantics the schema alone doesn't emphasize: how date omission changes the default window, and the hierarchical dependency of facility → company → country. The metric meanings (fill % of working gas volume vs TWh) are also clarified.

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?

States a specific verb and resource — European gas storage levels from GIE AGSI+ — then enumerates the exact metrics returned (fill %, TWh in storage, injection/withdrawal, trend, gas day) and the aggregation levels (EU, country, operator, facility). This is clearly distinct from siblings like gie_storage_facilities (lookup) or gie_storage_outages (disruptions).

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?

Explicit conditional rules: "Omit dates for the latest gas day; pass from/to for a daily series," plus dependency rules in the params (company needs country, facility needs country and company). It does not explicitly say when to prefer gie_storage_facilities or gie_storage_outages instead, though the facility/company EIC references in the schema do point at the lookup sibling.

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