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CSOAI-ORG

AI Incident Reporting MCP

classify_incident

Classify an incident across multiple regulatory regimes, determining notification obligations, forms, and deadlines. Returns a decision tree for compliance actions.

Instructions

Classify an incident against every regime in scope. Returns the multi-regime decision tree: which clocks start, who to notify, on what form, by when.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
entity_typeYes
incident_descriptionYes
affected_people_countNo
duration_hoursNo
economic_impact_eurNo
personal_data_breachedNo
cross_borderNo
is_high_risk_aiNo
is_financial_entityNo
is_nis2_entityNo
is_iso42001_certifiedNo
is_frontier_model_developerNo
api_keyNo

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault
resultYes
Behavior2/5

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

No annotations are provided, so the description must carry the full burden of behavioral disclosure. It states what the tool returns but does not disclose side effects (e.g., whether it modifies state), authentication needs, rate limits, or error behavior. The mention of 'which clocks start' hints at possible side effects, but it is ambiguous.

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 concise: two sentences that convey purpose and output without extraneous text. However, it could benefit from a more structured format to highlight key points.

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

Completeness2/5

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

Given 13 parameters and no param descriptions, the description is insufficient for proper use. It fails to explain which regimes are in scope, how inputs affect classification, or provide examples. An output schema exists but is not described, so the agent cannot infer return structure.

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

Parameters2/5

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

Schema description coverage is 0%, so the description must compensate. However, it does not explain any parameters or their expected values. Parameter titles are somewhat clear, but without description, an agent may misinterpret fields like entity_type or incident_description.

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 verb 'classify', the resource 'incident', and the scope 'against every regime in scope'. It also specifies the output as a multi-regime decision tree with details on clocks, notifications, etc. This distinguishes it from siblings like list_regime_clocks and sign_incident_response_attestation.

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

Usage Guidelines3/5

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

The description does not provide explicit guidance on when to use this tool versus alternatives. While the purpose is clear, there is no mention of prerequisites, when not to use it, or how it relates to sibling tools.

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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