waggle-os/docs/AI-ACT-COMPLIANCE-PROOF-2026-04-16.md

Waggle OS -- EU AI Act Compliance Proof

Document version: 2.0 Date: 2026-04-16 Standard: Regulation (EU) 2024/1689 -- Artificial Intelligence Act Scope: Waggle OS platform, all user tiers (FREE / PRO / TEAMS / ENTERPRISE) Previous audit: AI-ACT-AUDIT-2026-04-10.md Author: Waggle OS Compliance Module

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Table of Contents

1. Executive Summary
2. Article-by-Article Mapping
   • Art. 12 -- Automatic Event Logging
   • Art. 14 -- Human Oversight
   • Art. 19 -- Log Retention
   • Art. 26 -- Deployer Monitoring
   • Art. 50 -- Transparency Obligations
3. Compliance Matrix
4. How to Generate Proof
5. Sample Audit Report
6. Gaps and Remediation Plan

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Executive Summary

Waggle OS implements EU AI Act compliance as a built-in, always-on layer that runs on every tier. The compliance infrastructure is not a premium add-on -- it is embedded in the data layer (packages/core/src/compliance/ and packages/core/src/mind/schema.ts) and activates automatically when the system initializes a .mind database.

Core compliance components:

Component	Package	Purpose
InteractionStore	@waggle/core	CRUD for Art. 12 audit log (ai_interactions table)
ComplianceStatusChecker	@waggle/core	Evaluates compliance posture per article
ReportGenerator	@waggle/core	Produces structured JSON audit reports
buildComplianceDocDefinition	@waggle/agent	Generates boardroom-grade PDF reports (pdfmake)
CostTracker	@waggle/agent	Per-model cost tracking with budget caps
confirmation.ts	@waggle/agent	Smart confirmation gates + tiered autonomy
injection-scanner.ts	@waggle/core	Input sanitization (3 pattern sets)
tool-filter.ts	@waggle/agent	Per-context and per-persona tool allow/deny lists
Compliance server routes	@waggle/server	HTTP API surface for all compliance operations

Key architectural decision: The ai_interactions table has DDL-level triggers (ai_interactions_no_delete, ai_interactions_no_update) that make it append-only at the database engine level. No application code can silently mutate or delete audit rows. This answers the auditor's first question -- "can rows be tampered with?" -- with a concrete "no" enforced by SQLite itself.

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Article-by-Article Mapping

Article 12 -- Automatic Event Logging

Requirement: Art. 12(1) mandates that high-risk AI systems enable automatic recording of events (logs) throughout their lifecycle, including at minimum: (a) the period of each use, (b) the reference database against which input data was checked, (c) input data for which the search led to a match, and (d) the identification of natural persons involved in the verification of results.

For general-purpose AI systems (GPAI) deployed in non-high-risk contexts, Art. 12 still applies via Art. 53 as a transparency and traceability measure.

Waggle Implementation:

Sub-requirement	Implementation	File
Event recording	InteractionStore.record() inserts a row per AI interaction	packages/core/src/compliance/interaction-store.ts (line 23)
Model identification	model + provider columns, NOT NULL	packages/core/src/mind/schema.ts (lines 155-156)
Token counting	input_tokens + output_tokens columns	packages/core/src/mind/schema.ts (lines 157-158)
Cost tracking	cost_usd column + CostTracker class	packages/agent/src/cost-tracker.ts
Tool call recording	tools_called column (JSON array)	packages/core/src/mind/schema.ts (line 160)
Human action recording	human_action column (approved/denied/modified/none)	packages/core/src/mind/schema.ts (line 161)
Input/output recording	input_text + output_text columns (Art. 12.1(a))	packages/core/src/mind/schema.ts (lines 169-170)
Workspace + session scoping	workspace_id + session_id columns	packages/core/src/mind/schema.ts (lines 153-154)
Persona tracking	persona column	packages/core/src/mind/schema.ts (line 165)
Append-only enforcement	ai_interactions_no_delete + ai_interactions_no_update triggers	packages/core/src/mind/schema.ts (lines 183-192)
Provenance for imported data	imported_from column	packages/core/src/mind/schema.ts (line 164)
Automatic recording on agent loop	TraceRecorder wired into chat route	packages/server/src/local/routes/chat-helpers.ts

Tier Coverage: All tiers (FREE, PRO, TEAMS, ENTERPRISE). The ai_interactions table is part of the core schema that initializes on every .mind database regardless of tier. There is no tier gate on interaction recording.

Evidence:

• Schema DDL: packages/core/src/mind/schema.ts lines 150-192 define the table, indices, and append-only triggers.
• Store class: packages/core/src/compliance/interaction-store.ts -- record() method (line 23) performs the INSERT with all 14 columns.
• Status checker: packages/core/src/compliance/status-checker.ts -- checkArt12() (line 48) evaluates total interaction count and flags warning for zero rows or non-compliant if the system has been active 24+ hours with no logs.
• Server route: packages/server/src/local/routes/compliance.ts -- POST /api/compliance/interactions (line 86) exposes recording via HTTP.
• E2E test: tests/e2e/full-product-audit.spec.ts line 125 -- GET /api/compliance/status verifies the endpoint returns status data.

Gap: None for the logging mechanism itself. GDPR Art. 17 (right-to-erasure) pseudonymization flow is specified but not yet implemented -- when implemented, it will use tombstone markers via a fresh INSERT rather than bypassing the append-only triggers (documented in schema.ts comment at line 176).

---

Article 14 -- Human Oversight

Requirement: Art. 14 requires that high-risk AI systems be designed to allow effective oversight by natural persons, including the ability to: (a) fully understand the system's capabilities and limitations, (b) correctly interpret output, (c) decide not to use the system or disregard its output, (d) intervene or interrupt the system.

For GPAI deployers, human oversight means maintaining the ability to approve, deny, or modify agent-proposed actions.

Waggle Implementation:

Sub-requirement	Implementation	File
Approve/deny/modify gates	needsConfirmation() + getApprovalClass() functions	packages/agent/src/confirmation.ts (lines 8-50+)
Destructive action blocking	ALWAYS_CONFIRM set (write_file, edit_file, git_commit, etc.)	packages/agent/src/confirmation.ts (line 13)
Tiered autonomy levels	shouldConfirmAtAutonomy() with Normal/Trusted/YOLO levels	packages/agent/src/confirmation.ts (line 147+)
Critical action safety net	isCriticalNeverAutopass() -- stays gated even at YOLO	packages/agent/src/confirmation.ts (line 188)
Bash command classification	SAFE_BASH_PATTERNS (read-only) vs DESTRUCTIVE_BASH_PATTERNS	packages/agent/src/confirmation.ts (lines 25-50)
Connector risk gating	CONNECTOR_WRITE_PATTERNS regex gates write operations	packages/agent/src/confirmation.ts (line 22)
Per-persona tool deny lists	filterToolsForContext() + disallowedTools on AgentPersona	packages/agent/src/tool-filter.ts (line 23)
Oversight action recording	human_action column in ai_interactions + getOversightLog()	packages/core/src/compliance/interaction-store.ts (lines 144-160)
Oversight count aggregation	getOversightCounts() returns approved/denied/modified counts	packages/core/src/compliance/interaction-store.ts (line 163)
Behavioral spec rules	Memory conflict protocol requires explicit user confirmation	packages/agent/src/behavioral-spec.ts (lines 71-79)
Cross-workspace access gates	read_other_workspace, list_workspace_files in ALWAYS_CONFIRM	packages/agent/src/confirmation.ts (lines 17-18)
Input injection defense	scanForInjection() with 3 pattern sets on all external input	packages/core/src (re-exported via packages/agent/src/injection-scanner.ts)

Tier Coverage: All tiers.

• FREE/PRO: Normal autonomy by default. All write operations require confirmation. Tool deny lists active.
• TEAMS/ENTERPRISE: Full audit log (auditLog: 'full' in tiers.ts). Admin panel available for oversight review. Tiered autonomy configurable per workspace.
• The autonomy system guarantees that isCriticalNeverAutopass() tools (destructive bash, git push, force operations) ALWAYS require human confirmation regardless of tier or autonomy level.

Evidence:

• Confirmation logic: packages/agent/src/confirmation.ts -- comprehensive gate system with 3 autonomy levels.
• Status checker: packages/core/src/compliance/status-checker.ts -- checkArt14() (line 75) evaluates oversight action counts and approval rates.
• Tier definition: packages/shared/src/tiers.ts -- auditLog field: 'none' (FREE), 'basic' (PRO), 'full' (TRIAL/TEAMS/ENTERPRISE).

Gap: The auditLog tier capability is defined but the FREE tier sets it to 'none'. This does NOT affect the underlying interaction recording (which always runs) -- it controls the visibility of the audit export UI in the admin panel. The audit data itself exists on all tiers; only the admin dashboard exposure varies. To fully close this gap, the compliance status endpoint (GET /api/compliance/status) should be accessible on all tiers (it currently is -- no tier gate on the route).

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Article 19 -- Log Retention

Requirement: Art. 19 requires that logs generated by high-risk AI systems be kept for a period appropriate to the intended purpose, and for at least six months (unless otherwise provided by Union or national law). Deployers must ensure logs are not deleted or modified during the retention period.

Waggle Implementation:

Sub-requirement	Implementation	File
Default permanent retention	Logs default to indefinite retention (no auto-pruning)	packages/core/src/compliance/status-checker.ts (lines 100-108)
System age tracking	meta.first_run_at entry set on schema init, used for retention math	packages/core/src/mind/db.ts via MindDB.getFirstRunAt()
Pruning detection	checkArt19() compares system age vs oldest log age to detect pruning	packages/core/src/compliance/status-checker.ts (lines 118-142)
Append-only enforcement	SQLite triggers prevent DELETE/UPDATE on ai_interactions	packages/core/src/mind/schema.ts (lines 183-192)
Retention period calculation	retentionDays computed from oldest log timestamp	packages/core/src/compliance/status-checker.ts (lines 113-115)
6-month minimum check	SIX_MONTHS_MS = 180 * 24 * 60 * 60 * 1000 constant	packages/core/src/compliance/status-checker.ts (line 15)

Tier Coverage: All tiers. The retention mechanism is part of the core schema and status checker. There is no tier gate on log retention. The append-only triggers fire on all databases regardless of tier.

Evidence:

• Status checker: packages/core/src/compliance/status-checker.ts -- checkArt19() (line 100) performs the full retention evaluation including the system-age vs log-age pruning detection fix (Review Critical #2 comment at line 117).
• Schema triggers: packages/core/src/mind/schema.ts lines 183-192 -- ai_interactions_no_delete and ai_interactions_no_update triggers enforce append-only at the DDL level.
• The oldest timestamp query (MIN(timestamp)) is in InteractionStore.getOldestTimestamp() at packages/core/src/compliance/interaction-store.ts line 100.

Gap: None. Waggle's default is permanent retention (no auto-pruning), which exceeds the Art. 19 minimum of 180 days. The append-only triggers prevent accidental deletion. The only gap is that GDPR Art. 17 erasure (if a user requests deletion of their data) requires a pseudonymization flow that replaces content with tombstone markers -- this is documented but not yet implemented (schema.ts line 176).

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Article 26 -- Deployer Monitoring

Requirement: Art. 26 requires deployers of high-risk AI systems to: (a) assign human oversight to competent individuals, (b) ensure input data is relevant and sufficiently representative, (c) monitor the operation of the system on the basis of the instructions for use, (d) inform the provider and suspend use if they suspect risks, (e) keep logs, (f) use available technical documentation, (g) classify workspaces by risk level.

Waggle Implementation:

Sub-requirement	Implementation	File
4 active monitors	cost_tracking, tool_logging, model_identification, persona_tracking	packages/core/src/compliance/status-checker.ts (lines 148-153)
Cost monitoring	CostTracker class with per-model pricing + daily budget caps	packages/agent/src/cost-tracker.ts
Budget enforcement	BudgetExceededError + soft/hard cap modes	packages/agent/src/cost-tracker.ts (lines 32-43)
Tool usage monitoring	tools_called JSON array stored per interaction	packages/core/src/mind/schema.ts (line 160)
Model identification	model + provider columns per interaction, aggregated by getModelInventory()	packages/core/src/compliance/interaction-store.ts (line 116)
Persona tracking	persona column per interaction	packages/core/src/mind/schema.ts (line 165)
Risk classification	TEMPLATE_RISK_MAP maps workspace templates to risk levels	packages/core/src/compliance/types.ts (lines 134-154)
Risk level types	`AIActRiskLevel: 'minimal'	'limited'
Workspace-level risk	ReportGenerator accepts getWorkspaceRisk() callback	packages/core/src/compliance/report-generator.ts (line 19)

Tier Coverage: All tiers.

• FREE: 4 monitors always active. CostTracker runs on all tiers. Template risk classification active.
• PRO: Same 4 monitors + auditLog: 'basic' (interaction summary visible).
• TEAMS/ENTERPRISE: Full audit log + admin panel (adminPanel: true). Risk classification visible in admin dashboard.
• The TEMPLATE_RISK_MAP in types.ts automatically classifies workspaces created from templates (e.g., 'legal-review': 'high-risk', 'hr-management': 'high-risk', 'research-project': 'minimal').

Evidence:

• Status checker: packages/core/src/compliance/status-checker.ts -- checkArt26() (line 146) returns the 4 active monitors.
• Cost tracker: packages/agent/src/cost-tracker.ts -- DEFAULT_MODEL_PRICING (line 23) covers 6 Claude models. setBudget() (line 55) configures daily caps.
• Tier capabilities: packages/shared/src/tiers.ts -- auditLog field per tier: 'none' (FREE), 'basic' (PRO), 'full' (TRIAL/TEAMS/ENTERPRISE).
• Risk map: packages/core/src/compliance/types.ts lines 134-154 -- 18 template-to-risk mappings.

Gap: The getWorkspaceRisk() callback in ReportGenerator defaults to returning 'minimal' if no callback is provided (line 32 of report-generator.ts). The workspace config does not yet persist risk classification date (riskClassifiedAt: null at line 53). This means risk classification is template-derived but not user-editable at runtime. For full Art. 26 compliance in high-risk contexts, users should be able to manually set and persist the risk level.

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Article 50 -- Transparency Obligations

Requirement: Art. 50 requires that: (a) deployers ensure AI system output is identifiable as AI-generated, (b) persons interacting with an AI system are informed they are interacting with an AI, (c) providers of GPAI models make available a sufficiently detailed summary of content used for training.

For Waggle as a deployer, the obligation is transparency about which models are being used and ensuring users know they are interacting with an AI.

Waggle Implementation:

Sub-requirement	Implementation	File
Model disclosure in UI	Model name shown in StatusBar per interaction	apps/web/src/ (StatusBar component)
Model inventory	getModelInventory() aggregates all model usage with call counts	packages/core/src/compliance/interaction-store.ts (line 116)
Model recorded per interaction	model + provider columns, NOT NULL constraint	packages/core/src/mind/schema.ts (lines 155-156)
AI-generated content marking	Behavioral spec instructs agents to identify as AI	packages/agent/src/behavioral-spec.ts (quality rules)
Professional disclaimers	Context-sensitive disclaimers for regulated domains	packages/agent/src/behavioral-spec.ts (lines 109-113)
Anti-hallucination discipline	Agents must distinguish KNOWN from INFERRED content	packages/agent/src/behavioral-spec.ts (lines 86-91)
Persona identification	Active persona tracked and disclosed	packages/agent/src/persona-data.ts
LLM routing transparency	LiteLLM config with named model routes	litellm-config.yaml

Tier Coverage: All tiers. Model identification is NOT NULL in the schema -- every interaction must have a model name. The StatusBar shows the active model on all tiers. Professional disclaimers are part of the behavioral spec which loads on all tiers.

Evidence:

• Status checker: packages/core/src/compliance/status-checker.ts -- checkArt50() (line 163) checks whether any models appear in the inventory.
• Schema constraint: packages/core/src/mind/schema.ts line 155 -- model TEXT NOT NULL.
• Behavioral spec: packages/agent/src/behavioral-spec.ts -- qualityRules section (line 83+) includes anti-hallucination discipline and professional disclaimer rules.

Gap: None. Model transparency is enforced at the schema level (NOT NULL constraint) and in the UI (StatusBar). The behavioral spec's disclaimer rules ensure AI-generated content is contextually marked in regulated domains.

---

Compliance Matrix

Rows represent each article sub-requirement. Columns represent tier coverage.

Art. 12 -- Event Logging

Sub-requirement	Free	Pro	Teams	Enterprise
Interaction recording (every AI call)	implemented	implemented	implemented	implemented
Model + provider identification	implemented	implemented	implemented	implemented
Token count tracking	implemented	implemented	implemented	implemented
Cost tracking	implemented	implemented	implemented	implemented
Tool call logging	implemented	implemented	implemented	implemented
Human action recording	implemented	implemented	implemented	implemented
Input/output text capture	implemented	implemented	implemented	implemented
Workspace + session scoping	implemented	implemented	implemented	implemented
Persona tracking	implemented	implemented	implemented	implemented
Append-only enforcement (DDL triggers)	implemented	implemented	implemented	implemented
Import provenance	implemented	implemented	implemented	implemented
Audit export API (POST /api/compliance/export)	implemented	implemented	implemented	implemented
Audit export admin UI	N/A	partial	implemented	implemented
GDPR Art. 17 pseudonymization	missing	missing	missing	missing

Art. 14 -- Human Oversight

Sub-requirement	Free	Pro	Teams	Enterprise
Confirmation gates for write operations	implemented	implemented	implemented	implemented
Destructive action blocking (ALWAYS_CONFIRM)	implemented	implemented	implemented	implemented
Tiered autonomy (Normal/Trusted/YOLO)	implemented	implemented	implemented	implemented
Critical actions gated even at YOLO	implemented	implemented	implemented	implemented
Bash command risk classification	implemented	implemented	implemented	implemented
Connector write-op risk gating	implemented	implemented	implemented	implemented
Per-persona tool deny lists	implemented	implemented	implemented	implemented
Oversight action recording in ai_interactions	implemented	implemented	implemented	implemented
Oversight log aggregation + approval rate	implemented	implemented	implemented	implemented
Cross-workspace access gates	implemented	implemented	implemented	implemented
Input injection scanning	implemented	implemented	implemented	implemented
Admin panel for oversight review	N/A	N/A	implemented	implemented

Art. 19 -- Log Retention

Sub-requirement	Free	Pro	Teams	Enterprise
Default permanent retention (no auto-pruning)	implemented	implemented	implemented	implemented
System age tracking (first_run_at)	implemented	implemented	implemented	implemented
Pruning detection (system age vs log age)	implemented	implemented	implemented	implemented
Append-only DDL triggers	implemented	implemented	implemented	implemented
6-month minimum enforcement	implemented	implemented	implemented	implemented
GDPR Art. 17 erasure flow	missing	missing	missing	missing

Art. 26 -- Deployer Monitoring

Sub-requirement	Free	Pro	Teams	Enterprise
Cost monitoring (CostTracker)	implemented	implemented	implemented	implemented
Daily budget caps (soft/hard)	implemented	implemented	implemented	implemented
Tool usage monitoring	implemented	implemented	implemented	implemented
Model identification monitoring	implemented	implemented	implemented	implemented
Persona tracking	implemented	implemented	implemented	implemented
Template-based risk classification	implemented	implemented	implemented	implemented
Workspace risk level in reports	implemented	implemented	implemented	implemented
Risk classification persistence	partial	partial	partial	partial
Admin panel visibility	N/A	N/A	implemented	implemented

Art. 50 -- Transparency

Sub-requirement	Free	Pro	Teams	Enterprise
Model name in UI (StatusBar)	implemented	implemented	implemented	implemented
Model inventory aggregation	implemented	implemented	implemented	implemented
Model NOT NULL schema constraint	implemented	implemented	implemented	implemented
Professional disclaimers (behavioral spec)	implemented	implemented	implemented	implemented
Anti-hallucination discipline	implemented	implemented	implemented	implemented
Persona identification	implemented	implemented	implemented	implemented
LLM routing transparency	implemented	implemented	implemented	implemented

Summary

Article	Free	Pro	Teams	Enterprise
Art. 12 -- Logging	implemented (13/14)	implemented (13/14)	implemented (13/14)	implemented (13/14)
Art. 14 -- Oversight	implemented (11/12)	implemented (11/12)	implemented (12/12)	implemented (12/12)
Art. 19 -- Retention	implemented (5/6)	implemented (5/6)	implemented (5/6)	implemented (5/6)
Art. 26 -- Monitoring	implemented (7/9)	implemented (7/9)	implemented (8/9)	implemented (8/9)
Art. 50 -- Transparency	implemented (7/7)	implemented (7/7)	implemented (7/7)	implemented (7/7)

Legend:

• implemented -- code exists, tested, and active on this tier
• partial -- mechanism exists but has a known limitation (see Gaps section)
• missing -- not yet implemented (see Gaps section)
• N/A -- not applicable to this tier by design (e.g., admin panel not available on Free)

---

How to Generate Proof

This section provides step-by-step instructions for a user or auditor to independently verify Waggle OS's compliance posture.

Step 1: Generate an Audit Report via the API

The compliance API is available on all tiers via the local sidecar server.

Check current compliance status:

curl http://localhost:3000/api/compliance/status

Returns a ComplianceStatus JSON object with per-article status, detail text, and supporting metrics.

Optionally scope to a specific workspace:

curl "http://localhost:3000/api/compliance/status?workspaceId=ws-my-workspace"

Generate a full audit report for a date range:

curl -X POST http://localhost:3000/api/compliance/export \
  -H "Content-Type: application/json" \
  -d '{
    "from": "2026-01-01T00:00:00Z",
    "to": "2026-04-16T23:59:59Z",
    "format": "json",
    "include": {
      "interactions": true,
      "oversight": true,
      "models": true,
      "provenance": true,
      "riskAssessment": true,
      "fria": false
    }
  }'

The response is an AuditReport object (see Sample Audit Report below).

To scope the report to a single workspace, add "workspaceId": "ws-my-workspace" to the request body.

Server route source: packages/server/src/local/routes/compliance.ts

Step 2: Verify Interaction Logs Exist

List recent interactions:

curl "http://localhost:3000/api/compliance/interactions?limit=20"

Returns { interactions: AIInteraction[] }. Each entry contains:

• id, timestamp -- when the interaction occurred
• model, provider -- which LLM was used
• inputTokens, outputTokens, costUsd -- resource consumption
• toolsCalled -- JSON array of tools invoked
• humanAction -- 'approved', 'denied', 'modified', or 'none'
• persona -- which agent persona handled the request
• inputText, outputText -- the actual request and response content (Art. 12.1(a))

Verify interaction count is non-zero after usage:

curl http://localhost:3000/api/compliance/status | jq '.art12Logging.totalInteractions'

If this returns 0 after the system has been active for 24+ hours, the status will show "non-compliant" with a diagnostic message ("Verify logging pipeline").

Verify append-only enforcement directly in the database:

-- This should FAIL with: "ai_interactions is append-only (EU AI Act Art. 12 audit log)"
DELETE FROM ai_interactions WHERE id = 1;

-- This should also FAIL with the same message
UPDATE ai_interactions SET model = 'tampered' WHERE id = 1;

The triggers ai_interactions_no_delete and ai_interactions_no_update in packages/core/src/mind/schema.ts enforce this at the engine level.

Step 3: Check Model Inventory Completeness

List all models used:

curl "http://localhost:3000/api/compliance/models"

Returns { models: ModelInventoryEntry[] } with aggregated usage per model:

• model -- model identifier (e.g., claude-sonnet-4-6)
• provider -- provider name (e.g., anthropic)
• calls -- total number of invocations
• inputTokens, outputTokens -- total token consumption
• costUsd -- total estimated cost

Filter by date range and workspace:

curl "http://localhost:3000/api/compliance/models?from=2026-04-01&to=2026-04-16&workspaceId=ws-legal"

Verify completeness: Every model that appears in a chat session or agent loop should have a corresponding entry. The model TEXT NOT NULL schema constraint ensures no interaction can be logged without a model identifier.

Step 4: Validate Oversight Log Entries

The oversight log captures every human approve/deny/modify action on agent-proposed tool calls.

Via the audit report:

curl -X POST http://localhost:3000/api/compliance/export \
  -H "Content-Type: application/json" \
  -d '{
    "from": "2026-01-01T00:00:00Z",
    "to": "2026-04-16T23:59:59Z",
    "format": "json",
    "include": {
      "interactions": false,
      "oversight": true,
      "models": false,
      "provenance": false,
      "riskAssessment": false,
      "fria": false
    }
  }'

The response humanOversightLog array contains entries with:

• timestamp -- when the action occurred
• action -- 'approved', 'denied', or 'modified'
• tool -- which tool the action was taken on
• detail -- contextual information (e.g., persona in use)

Check approval rate:

curl http://localhost:3000/api/compliance/status | jq '.art14Oversight'

Returns humanActions (total count) and approvalRate (0-100%).

Step 5: Generate a PDF Compliance Report

For boardroom-grade PDF output, use the buildComplianceDocDefinition() function from @waggle/agent:

import { buildComplianceDocDefinition, renderComplianceReportPdf, writeComplianceReportPdf } from '@waggle/agent';

// Given an AuditReport from Step 1:
const pdfPath = await writeComplianceReportPdf(auditReport, './compliance-audit.pdf');

Or programmatically inspect the document structure:

const docDef = buildComplianceDocDefinition(auditReport);
// docDef is a pdfmake TDocumentDefinitions with:
// - Cover page: org name, risk level, period, overall status
// - Article status grid: per-article status badges
// - Model inventory table with totals
// - Human oversight log (up to 50 most recent events)
// - Harvest provenance table
// - Summary section with aggregate counts

Source: packages/agent/src/compliance-pdf.ts Tests: packages/agent/tests/compliance-pdf.test.ts

Step 6: Verify Risk Classification

Check the risk classification for a workspace:

curl -X POST http://localhost:3000/api/compliance/export \
  -H "Content-Type: application/json" \
  -d '{
    "workspaceId": "ws-legal",
    "from": "2026-01-01T00:00:00Z",
    "to": "2026-04-16T23:59:59Z",
    "format": "json",
    "include": { "interactions": false, "oversight": false, "models": false, "provenance": false, "riskAssessment": true, "fria": false }
  }'

The workspace.riskLevel field in the response shows the classification (minimal, limited, high-risk, or unacceptable).

The TEMPLATE_RISK_MAP in packages/core/src/compliance/types.ts maps workspace templates to risk levels:

Template	Risk Level
legal-review	high-risk
hr-management	high-risk
recruiting	high-risk
finance	high-risk
insurance	high-risk
credit-scoring	high-risk
healthcare	high-risk
sales-pipeline	limited
marketing-campaign	limited
customer-support	limited
product-launch	limited
agency-consulting	limited
education	limited
data-analysis	limited
research-project	minimal
code-review	minimal
content-creation	minimal
project-management	minimal
blank	minimal

---

Sample Audit Report

Below is the structure produced by a ReportGenerator.generate() call (via POST /api/compliance/export). This is the same structure consumed by buildComplianceDocDefinition() to produce the PDF.

{
  "report": {
    "version": "1.0",
    "generatedAt": "2026-04-16T14:30:00.000Z",
    "period": {
      "from": "2026-01-01T00:00:00Z",
      "to": "2026-04-16T23:59:59Z"
    },
    "generatedBy": "Waggle OS"
  },
  "workspace": {
    "id": "ws-legal",
    "name": "Legal Review",
    "riskLevel": "high-risk",
    "riskClassifiedAt": null
  },
  "complianceStatus": {
    "overall": "compliant",
    "art12Logging": {
      "status": "compliant",
      "detail": "1,247 interactions logged with full model, token, cost, and tool tracking.",
      "totalInteractions": 1247
    },
    "art14Oversight": {
      "status": "compliant",
      "detail": "47 human oversight actions: 39 approved, 5 denied, 3 modified.",
      "humanActions": 47,
      "approvalRate": 83
    },
    "art19Retention": {
      "status": "compliant",
      "detail": "Logs retained since 2026-01-15 (91 days). System is still within its first 180 days.",
      "oldestLogDate": "2026-01-15T09:30:00.000Z",
      "retentionDays": 91
    },
    "art26Monitoring": {
      "status": "compliant",
      "detail": "4 active monitors: cost, tools, model ID, persona.",
      "activeMonitors": [
        "cost_tracking",
        "tool_logging",
        "model_identification",
        "persona_tracking"
      ]
    },
    "art50Transparency": {
      "status": "compliant",
      "detail": "2 model(s) in use, all identified in StatusBar and interaction logs.",
      "modelsDisclosed": true
    }
  },
  "modelInventory": [
    {
      "model": "claude-sonnet-4-6",
      "provider": "anthropic",
      "calls": 500,
      "inputTokens": 1000000,
      "outputTokens": 200000,
      "costUsd": 3.50
    },
    {
      "model": "claude-haiku-3-5",
      "provider": "anthropic",
      "calls": 747,
      "inputTokens": 500000,
      "outputTokens": 80000,
      "costUsd": 0.42
    }
  ],
  "humanOversightLog": [
    {
      "timestamp": "2026-04-10T09:15:00.000Z",
      "action": "approved",
      "tool": "save_memory",
      "detail": "Persona: legal-professional"
    },
    {
      "timestamp": "2026-04-11T14:22:00.000Z",
      "action": "denied",
      "tool": "send_email",
      "detail": "Persona: legal-professional"
    }
  ],
  "harvestProvenance": [
    {
      "source": "Claude Code exports",
      "importedAt": "2026-03-01T00:00:00.000Z",
      "itemsImported": 156,
      "framesCreated": 89
    }
  ],
  "interactionCount": 1247
}

PDF Structure (from buildComplianceDocDefinition)

The PDF generated from this report contains the following pages and sections:

Page 1 -- Cover

• Title: "AI ACT COMPLIANCE AUDIT" (honey-colored kicker, #E5A000)
• Workspace name in large bold text (30pt, #08090C)
• Honey-colored horizontal rule separator
• Two-column metadata grid:
  • Left: Risk Level (e.g., "HIGH-RISK"), Period (date range)
  • Right: Overall Status (color-coded: green/honey/red), Generated timestamp
• Page break after cover

Page 2+ -- Compliance Status

• Section header: "Compliance Status" (16pt bold, honey)
• Executive summary sentence based on overall status
• Article status grid table:
  • Column 1: Article label (e.g., "Art. 12 -- Logging")
  • Column 2: Status badge (COMPLIANT in green, WARNING in honey, NON-COMPLIANT in red)
  • Column 3: Detail text

Model Inventory

• Section header: "Model Inventory"
• Table with columns: Model, Provider, Calls, Input tok, Output tok, Cost (USD)
• TOTAL row at bottom with bold sums and #FAFAFA background
• Falls back to italic "No model calls recorded" if empty

Human Oversight Log

• Section header: "Human Oversight Log"
• Table with columns: Timestamp, Action, Tool, Detail
• Capped at 50 most recent events with overflow note
• Falls back to italic "No human oversight events" if empty

Harvest Provenance

• Section header: "Harvest Provenance"
• Table with columns: Source, Imported At, Items, Frames
• Falls back to italic "No harvest provenance data" if empty

Summary

• Bulleted list: total interactions, models in inventory, oversight events, harvest sources
• Horizontal rule separator
• Footer: report version + generator attribution

Every page (2+):

• Header: "Waggle -- AI Act Compliance Audit" (left) + workspace name (right)
• Footer: generation date (left) + page number "X / Y" (right)

PDF metadata:

• Title: "Waggle AI Act Compliance Audit -- {workspace name}"
• Author: "Waggle OS"
• Creator: "Waggle OS Compliance Module"
• Subject: period description

Source: packages/agent/src/compliance-pdf.ts -- buildComplianceDocDefinition() (line 205) Test: packages/agent/tests/compliance-pdf.test.ts -- verifies metadata, page size, margins, content structure

---

Gaps and Remediation Plan

#	Gap	Articles Affected	Severity	Remediation	Status
1	GDPR Art. 17 pseudonymization flow	Art. 12, Art. 19	Medium	Implement tombstone INSERT + status flag flow that replaces inputText/outputText without bypassing append-only triggers	Designed, not implemented
2	Risk classification not user-editable at runtime	Art. 26	Low	Add workspace config field for manual risk level + riskClassifiedAt timestamp persistence	riskClassifiedAt field exists as null; needs persistence logic
3	Admin panel gated to TEAMS/ENTERPRISE	Art. 14, Art. 26	Informational	The underlying data and API endpoints are available on all tiers. Only the admin UI is gated. No action required for compliance -- the API is the proof surface.	By design
4	auditLog capability set to 'none' on FREE tier	Art. 12, Art. 14	Informational	This controls admin UI visibility, not data collection. All interaction data is recorded regardless of this setting. Consider renaming to auditLogUI for clarity.	By design
5	No NER-based PII detection	Art. 10 (data quality)	Low	Current regex-based PII scan catches emails, phones, API keys, JWTs. A model-based NER scanner would improve coverage.	v1 regex shipped; NER deferred

Overall assessment: Waggle OS meets the substantive requirements of Articles 12, 14, 19, 26, and 50 on all tiers. The compliance data layer (schema, interaction store, status checker, report generator) runs unconditionally. The gaps are in ancillary areas (GDPR erasure flow, risk classification UI, PII detection depth) that do not affect the core compliance posture.

---

Generated 2026-04-16. Source files verified against the main branch of waggle-os. For the machine-readable prior audit, see AI-ACT-AUDIT-2026-04-10.json. For the PDF generator, see packages/agent/src/compliance-pdf.ts.