get_ai_act_score

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

The description explains the scoring methodology in detail: weighted average with control values (compliant=1.0, partial=0.5, non_compliant=0.0) and exclusion of not_applicable controls, which is behavioral context beyond annotations (none provided).

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?

Three sentences: first states the action and output, second explains calculation, third provides companion tool. No wasted words, front-loaded.

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 no parameters and no output schema, the description fully covers what the tool does, how it computes the score, and how to get detailed breakdown, making it complete for an AI agent.

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?

Input schema has 0 parameters (100% coverage), so the baseline is 4. The description does not add parameter info but explains the return value semantics, which is sufficient.

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 returns the overall AI Act compliance score (0–100) and distinguishes it from the sibling tool list_ai_act_controls by mentioning it provides per-article breakdown.

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?

It explicitly recommends using list_ai_act_controls to see per-article breakdown and identify gaps, providing clear context on when to use this tool versus the alternative.

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