Assess an AI System Under the EU AI Act

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

Adds substantial behavioral context beyond the readOnly/idempotent/openWorld annotations: 'Sparse inputs fail closed', 'Impact never changes legal classification', and 'classification never implies implementation readiness'. It also discloses how missing facts are returned ('missing_facts with the question to ask') and that output includes provenance, warnings, and recommended follow-up calls. No contradiction with annotations.

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 long but well-structured: purpose and outputs first, then behavioral traits, then a clearly marked profile-building section. Every sentence carries useful information, and the length is justified by the 0% schema coverage, though the minimum-profile list is dense and could be slightly tightened.

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 complex tool with 15 parameters, nested objects, and no schema descriptions, the description covers the essential workflow: what the tool returns, fail-closed behavior, minimum required facts, and how missing facts surface. An output schema exists, so return-value details need not be spelled out. Some advanced optional sections are unaddressed, but the 'supply only facts you were given' guidance mitigates that gap.

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 0%, so the description carries the full burden. It compensates well by defining the fact-object shape (fact_id, value, origin, verification, evidence_reference_ids), prescribing origin/verification values, listing a useful minimum profile, and giving guidance on annex_iii usage. However, several top-level sections (e.g., article_5_prohibitions, controls_and_evidence) receive no parameter-level explanation, so coverage is not exhaustive.

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 ('Assess one normalized EU AI Act system profile against the pinned sealed corpus') and enumerates the three output blocks (legal-classification, impact, implementation-readiness). The scope is clear, but it never explicitly names or contrasts sibling tools like euaiact_classify_system, so differentiation is only implicit.

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 'HOW TO BUILD THE PROFILE' section gives detailed input-construction guidance, which is useful for invoking this tool, but there is no explicit statement of when to choose this tool over siblings, nor any 'use classify_system instead when...' exclusion. Usage context is implied rather than stated.

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