Look up a specific AI Act article (e.g. "Art. 53(1)(d)" or "Annex III") and return all related events from our pipeline plus the official EUR-Lex URL.
| Name | Required | Description | Default |
|---|---|---|---|
| article | Yes | Article identifier — e.g. "Art. 53", "Art. 53(1)(d)", "Annex III", "Recital 60". |
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are present, so the description carries the full burden of behavioral disclosure. It reveals the return content ('all related events' and 'official EUR-Lex URL'), but does not explicitly state that the operation is read-only or mention any limitations, edge cases, or safety characteristics. The verb 'look up' implies non-destructive behavior, but that is implicit rather than explicit.
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, well-structured sentence that starts with the verb and resource, includes concrete examples, and contains no redundant or filler content. It earns its place efficiently.
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?
For a simple one-parameter lookup tool with no output schema, the description adequately covers purpose, input format, and return values. It tells the user exactly what will be returned ('all related events' plus the EUR-Lex URL), making it complete enough for this simplicity.
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 input schema covers the single parameter 'article' with 100% description coverage, including examples. The description adds no extra semantic meaning beyond what the schema already provides, so a baseline score 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 uses the specific verb 'look up' and identifies the exact resource (a specific AI Act article) with concrete examples like 'Art. 53(1)(d)' and 'Annex III'. It clearly distinguishes itself from sibling tools by focusing on article-level lookup and returning pipeline events plus the EUR-Lex URL.
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 usage for specific article lookups, but does not explicitly state when to use this tool over alternatives or list exclusions. It gives context by emphasizing 'specific' and examples, but no direct reference to sibling tools or when-not-to-use conditions.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Add one secure layer between your agents and this server.
Each tool has a distinct primary purpose: role-based obligations, article lookup, raw updates, and summary digest. Slight overlap exists between query_ai_act_updates and summarize_changes_since, but descriptions clearly differentiate raw events from aggregated summaries, making confusion unlikely.
All tool names follow a consistent verb-first snake_case pattern (get, lookup, query, summarize). The naming is predictable and clear, with no mixed conventions or vague verbs.
Four tools is a well-scoped size for a focused AI Act radar server. Each tool covers a distinct core need without unnecessary redundancy, making the set feel complete and manageable.
The toolset covers key workflows: finding obligations by role, looking up specific articles, querying regulatory updates, and generating change summaries. A minor gap is the lack of direct article text retrieval (only a EUR-Lex URL is provided), but this does not critically hinder common use cases.
