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

Annotations already declare readOnly, openWorld, idempotent, and non-destructive. The description builds on this by stating 'no auth required, unlimited' and specifying the data source and license (CC BY 4.0), which are behavioral details not captured in annotations. It doesn't add anything about side effects, but none exist given the read-only nature. This is useful supplemental context.

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 a single paragraph of five sentences, with the core purpose front-loaded in the first sentence. Subsequent sentences concisely add data breakdown, time coverage, alignment with international standards, typical use cases, and source/licensing info. No sentence is wasted.

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 that an output schema exists)Skip because the tool returns a structured dataset, the description doesn't need to detail return format. It covers the essential context: data type, breakdowns, time range, country scope, and source. It does not mention any limitations like data availability gaps for certain years or how multiple series are aggregated, but those are not critical for an agent to invoke the tool successfully, especially with schema richness.

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 description coverage is 100%, with each parameter already well described in the input schema (e.g., country code format, start/end period defaults, max_series range). The tool description does not add any parameter-specific information beyond the schema, so it meets the baseline for high schema coverage but does not exceed it.

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 ('Retrieve'), a precise resource ('annual greenhouse gas (GHG) emissions data'), and the data source ('OECD Environment Policy and Progress indicators database'). It also specifies the data granularity (by gas type and sector) and the coverage (OECD countries from 1990 to latest). This clearly distinguishes it from sibling tools like oecd.economy.gdp or oecd-data.series.data, which serve different data needs.

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 gives clear context on when to use it ('climate policy analysis, carbon footprint comparisons, tracking progress towards net-zero targets') and highlights the no-auth, free nature. However, it does not explicitly mention exclusions or directly name alternative tools for other types of data, so it stops short of full when-to-use vs. not-to-use guidance.

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