madagascar_get_dataset

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

With no annotations, the description carries the burden of disclosing behavioral traits. It mentions it uses the official public API, which implies a network call and possibly rate limits or versioning, but it doesn't specify if the tool is read-only, what happens if the dataset is not found, or whether it requires authentication. The information provided is minimal but not misleading.

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 one sentence with no filler. It is concise and front-loaded with the key information: what it does (inspect), on which resource (data.gouv.fr dataset), and how to identify it (slug or id). This is excellent conciseness.

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?

This is a simple tool with one parameter and no output schema, so the description could be minimal. However, given the lack of annotations and output schema, it could have added a bit more about expected return value or error behavior. Still, for a basic inspection tool, the description covers the core action and the target resource adequately.

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 schema already provides a description for the single parameter 'dataset' as 'Dataset slug or id', and the description repeats the same information ('by slug or id'). Since schema coverage is 100%, the description adds no additional semantic meaning beyond the schema. Baseline of 3 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 clearly states the tool's purpose: inspecting a single data.gouv.fr dataset by slug or id via the official public API. It names the specific resource (data.gouv.fr dataset) and the intended input type, which is sufficient to distinguish it from the sibling tools that handle other resources like HDX, GDACS, or weather data.

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 implies the tool is for inspection (read operation) via the official public API, which gives a hint for when to use it: when you need a single dataset's details from data.gouv.fr. However, it does not explicitly state when not to use it or provide alternatives (e.g., use search_data_gouv to find datasets, or get_sources to list sources).

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