ai-act-projection-interpreter

name	ai-act-projection-interpreter
description	Interpret AI Act projection JSON from GhostCrab MCP (ghostcrab_projection_get or exported rows) into precise human-facing compliance answers. Use when rendering ai-act obligation_cascade, penalty_path, exemption_surface, or sector_risk_profile results, especially for demos where every answer must be cited, scoped, and faithful to the returned rows.
metadata	{"short-description":"Render AI Act projection results"}

AI Act Projection Interpreter

Use this skill when a user asks to explain, summarize, render, or validate JSON returned by GhostCrab for the ai-act workspace (typically via ghostcrab_projection_get or a saved MCP response).

Core Rule

MCP-returned rows are the source of truth. Do not invent obligations, penalties, exemptions, dates, or legal basis not present in the returned rows.

If a row lacks source_ref, source_article, or legal_basis, say the projection result is incomplete and flag it as a quality issue.

Rendering Workflow

1. Identify the template from the request, file name, or row shape:
   • ai_act_obligation_cascade
   • ai_act_penalty_path
   • ai_act_exemption_surface
   • ai_act_sector_risk_profile
2. Load only the needed reference:
   • Output contract: references/projection-output-contract.md
3. Produce a human answer with four parts:
   • short answer
   • grouped/actionable findings
   • cited legal basis
   • quality checks
4. Keep facet_path hidden unless the user asks for debug or trace details.

Required Human Output

For every answer:

• State the row count.
• State whether all rows have usable citations.
• Group rows by the most helpful human dimension.
• Cite each source as Article N - Title or the exact returned source_ref.
• Preserve the returned wording in answer_item for obligations and exemptions.

Template-Specific Guidance

Obligation Cascade

Use for: "Quelles obligations pour un provider high-risk ?"

Render as a compliance checklist grouped by obligation_type, then by article.

Always include:

• total obligations
• legal_effect distribution
• top obligation families
• deadline summary
• sample or full checklist depending on user request

Quality checks:

• all rows should have legal_effect=obligation
• all rows should have operator_compliance_scope in operator, mixed, or general
• all rows should have source_ref

Penalty Path

Use for: "Quelle sanction pour une pratique interdite ?"

Render as a penalty answer with:

• maximum EUR amount
• turnover percentage
• penalty tier
• source article

Do not generalize beyond the returned tier.

Exemption Surface

Use for: "Quelles exemptions a l'Article 6 ?"

Render only explicit exceptions/derogations returned by the projection.

Always show:

• exception text
• legal_effect
• conditionality_type
• article source

If no rows are returned, say no explicit exemption was returned by this projection for the selector.

Sector Risk Profile

Use for: "Mon CRM de recrutement est-il high-risk ?"

Render by category/use case:

• category label
• sector
• risk level
• source

If a sector includes both high_risk and prohibited, call out the prohibited branch separately.

Deterministic Renderer

For repeatable demos, prefer:

python3 skills/ai-act-projection-interpreter/scripts/render_projection.py \
  --template ai_act_obligation_cascade \
  --json out/reports/demo_obligation_cascade_provider_high_risk.json

The script emits Markdown and performs basic quality checks.