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

Annotations already declare readOnlyHint=true and openWorldHint=false, so safety is covered; the description adds real value beyond that by disclosing the data provenance (OONI anomaly rates, risk tiers, measurement counts) and warning that scores are estimates, not confirmed block counts, and that coverage/dataAsOf must be read from the response.

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?

Two tight sentences with no filler: the first defines the resource and scope, the second covers return content and the interpretive caveat. Everything is front-loaded and each clause earns its place.

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?

With no output schema, the description must carry the return-value burden, and it does: country scores, risk tiers, measurement counts, plus the source window caveat. Complete enough to call correctly, though it never says how the index is ordered or how many countries are included.

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 tool takes zero parameters, so there is no parameter semantics to explain and the baseline of 4 applies. Nothing in the description misleads about inputs, and the note about reading coverage/dataAsOf from the response implicitly confirms there are no input filters.

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 ('Get the global censorship index with rankings for monitored countries') and scopes it to the global view. It does not name or contrast any sibling, so an agent cannot tell from the text alone why to pick this over get_censorship_summary or get_global_heatmap.

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?

Usage is only implied by the global, parameterless nature of the tool; there is no explicit when-to-use statement, no exclusion criteria, and no named alternative among the crowded get_censorship_* family. Adequate but leaves routing to inference.

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