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acttrace_classify

Classify any AI feature's EU AI Act risk category by specifying feature details. Receive a risk tier, confidence, rationale, and obligations.

Instructions

Classify an AI feature's EU AI Act risk category.

Runs ActTrace's deterministic classification engine and returns a risk category (prohibited, possible_high_risk, limited_risk_transparency, minimal_risk, unknown, or out_of_scope_financial_services) with confidence, rationale, triggering facts, missing information, obligations, and source references.

Use this when asked "Is this AI feature EU AI Act compliant?", "What risk tier does my AI feature fall into?", or for a general AI Act risk classification.

ActTrace is for non-financial SaaS / technology products. Financial use cases are reported as out_of_scope_financial_services unless financial_override is set. The result is informational and is NOT legal advice.

Args: feature_name: Short name of the AI feature (e.g. "support chatbot"). description: What the feature does. Strongly recommended — an empty description yields an unknown verdict. use_case: Short use-case label (e.g. "support_assist"). user_facing: True if end users interact with the feature. eu_available: True if the feature is available to EU users. internal_only: True if the feature is for internal staff only. model_provider: Underlying model provider (e.g. "OpenAI"). Required for a confident verdict when the feature is user-facing. human_review_level: One of "none", "optional", "required_before_action", "required_after_action". automated_decision: True if the feature makes automated decisions. high_risk_domain: True if the feature operates in a high-risk domain (hiring, education, biometrics, etc.). sensitive_data: True if the feature processes sensitive data. financial_override: Set True to bypass the financial-services out-of-scope guard for a borderline non-financial feature.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
feature_nameYes
descriptionNo
use_caseNo
user_facingNo
eu_availableNo
internal_onlyNo
model_providerNo
human_review_levelNo
automated_decisionNo
high_risk_domainNo
sensitive_dataNo
financial_overrideNo

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault
resultYes
Behavior5/5

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

With no annotations, the description fully discloses behavior: runs deterministic classification engine, returns detailed fields, states limitations (empty description yields unknown), and clarifies the tool is informational, not legal advice. No hidden side effects.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Conciseness4/5

Is the description appropriately sized, front-loaded, and free of redundancy?

The description is front-loaded with the essential purpose and then provides structured details. It is somewhat lengthy but well-organized, with each sentence serving a purpose. Could be slightly trimmed, but overall efficient given the complexity.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Completeness5/5

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

Given the tool's complexity (12 parameters, regulatory sensitivity) and the presence of an output schema, the description is exceptionally complete. It covers purpose, usage, parameter details, output fields, scope restrictions, and a legal disclaimer. No gaps remain.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Parameters5/5

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. The 'Args:' section provides thorough explanations for all 12 parameters, including allowed values for human_review_level and guidance on when fields are required (e.g., model_provider for user-facing features). This adds critical meaning beyond the bare schema.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Purpose5/5

Does the description clearly state what the tool does and how it differs from similar tools?

The description clearly states the tool's purpose: 'Classify an AI feature's EU AI Act risk category.' It lists possible risk categories and specifies the scope (non-financial SaaS/technology products), distinguishing it from the sibling tool for generating transparency notices.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Usage Guidelines5/5

Does the description explain when to use this tool, when not to, or what alternatives exist?

Explicitly tells when to use: 'Use this when asked "Is this AI feature EU AI Act compliant?", "What risk tier does my AI feature fall into?", or for a general AI Act risk classification.' Also explains when not to use (financial services without override) and notes the result is not legal advice.

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

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