# TraceRTM — Product Requirements Document

**Version:** 1.0
**Date:** 2026-02-12
**Status:** Initial Release

---

## 1. Product Vision

TraceRTM is an enterprise-grade requirements management and traceability platform that bridges the gap between specifications, implementation, and verification. It empowers development teams to:

- **Discover & Capture** requirements from multiple sources (GitHub, Jira, Linear, specifications)
- **Qualify & Analyze** through AI-powered quality scoring, graph analysis, and impact assessment
- **Apply & Track** via comprehensive item management, workflow orchestration, and progress monitoring
- **Verify & Validate** with integrated test management, coverage tracking, and BDD support
- **Report & Visualize** through traceability matrices, dashboards, and analytics
- **Collaborate & Integrate** in real-time with external tools and AI agents
- **Automate & Scale** using agent coordination, MCP protocol, and workflow automation

TraceRTM ensures complete traceability from initial requirements through deployment, providing compliance teams with immutable audit trails and development teams with actionable insights.

---

## 2. Target Users

**Primary Users:**

| User Type | Needs | Key Features |
|-----------|-------|--------------|
| **Developers** | Link code to requirements, understand impact of changes, track implementation progress | Item management, auto-linking, commit linking, code analysis |
| **Product Managers** | Define requirements, track progress, generate reports, ensure coverage | Specification management, progress tracking, traceability matrices |
| **QA Engineers** | Manage test cases, track coverage, verify requirements, execute tests | Test management, coverage tracking, BDD support, verification reports |
| **Compliance Teams** | Audit traceability, verify coverage, export evidence, ensure standards compliance | Blockchain audit trail, export/import, validation reports |
| **AI Agents** | Query traceability data, analyze impact, coordinate workflows, assist teams | MCP server, 50+ tools, agent coordination, workflow automation |

**Secondary Users:**
- Architects (ADR management, system design, dependency analysis)
- Tech Leads (critical path analysis, team coordination, quality metrics)
- DevOps (CI/CD integration, automated validation, deployment tracking)

---

## 3. Success Metrics

| Metric | Target | Measurement |
|--------|--------|-------------|
| **Traceability Coverage** | >95% of requirements linked to code and tests | Graph analysis: % of items with complete link chains |
| **Query Performance** | <100ms p95 for graph queries | Prometheus metrics from Go backend |
| **Test Coverage** | >80% line coverage, 100% requirement coverage | Coverage reports + traceability matrix |
| **User Adoption** | 80% of team members active weekly | User activity tracking |
| **MCP Tool Usage** | >50 tool invocations per day per AI agent | MCP metrics endpoint |
| **Documentation Freshness** | >90% of items updated within 30 days | Timestamp analysis |
| **API Response Time** | <200ms p95 for REST endpoints | FastAPI middleware metrics |
| **Import Success Rate** | >98% successful imports from external systems | Import pipeline success tracking |
| **Agent Coordination** | >95% workflow success rate | Temporal workflow metrics |
| **System Uptime** | 99.5% availability | Health check monitoring |

---

## 4. Epic Hierarchy

```
E1: Discovery & Capture
  E1.1: Import & Ingestion
  E1.2: Specification Management
  E1.3: Auto-Linking & Suggestions
  E1.4: Commit & Code Linking

E2: Qualification & Analysis
  E2.1: Requirement Quality Scoring
  E2.2: Graph Analysis & Validation
  E2.3: Impact Analysis
  E2.4: Critical Path & Dependencies
  E2.5: Coverage Analysis

E3: Application & Tracking
  E3.1: Item Management (CRUD)
  E3.2: Link Management
  E3.3: Status Workflow
  E3.4: Progress Tracking
  E3.5: Feature & ADR Management

E4: Verification & Validation
  E4.1: Test Management
  E4.2: Test Execution
  E4.3: Coverage Tracking
  E4.4: BDD & Scenario Testing
  E4.5: Verification Reports

E5: Reporting & Analytics
  E5.1: Traceability Matrix Generation
  E5.2: Analytics Dashboards
  E5.3: Custom Reports & Export
  E5.4: Metrics & Statistics
  E5.5: Visualization

E6: Collaboration & Integration
  E6.1: Real-Time Collaboration
  E6.2: External Tool Sync
  E6.3: Webhooks & Events
  E6.4: Notifications
  E6.5: AI Chat Assistant

E7: AI & Automation
  E7.1: MCP Server & Tools
  E7.2: Agent Coordination
  E7.3: Workflow Automation
  E7.4: Code Analysis & Indexing
  E7.5: AI-Powered Insights
```

---

## 5. Epic Details — Sub-Epics and Atomic User Stories

### E1: Discovery & Capture

#### E1.1: Import & Ingestion

**Intent:** Enable teams to import requirements from existing systems and maintain synchronization with external tools.

| Story ID | User Story | Acceptance Criteria | Priority |
|----------|-----------|-------------------|----------|
| E1.1.1 | As a PM, I import GitHub issues into TraceRTM so that development work is traceable from the start. | GitHub import service fetches issues via API, creates items with all metadata (labels, assignees, milestones), links are preserved, import status tracked in `pipeline_runs`. | P0 |
| E1.1.2 | As a PM, I import Jira tickets into TraceRTM to maintain traceability with existing project management. | Jira import service authenticates via OAuth, maps Jira fields to TraceRTM items, handles custom fields, preserves issue hierarchy (epic/story/subtask). | P0 |
| E1.1.3 | As a developer, I import Linear issues to sync development work across tools. | Linear integration authenticates via API key, syncs issues bidirectionally, maps Linear states to TraceRTM statuses, handles webhooks for real-time updates. | P1 |
| E1.1.4 | As a PM, I ingest requirements via webhooks so external systems can push updates in real-time. | Webhook endpoint accepts JSON payloads, validates against schema, creates/updates items, supports authentication, logs all webhook deliveries. | P0 |
| E1.1.5 | As a PM, I perform bulk imports of requirements from CSV/JSON files. | Bulk import service validates file format, maps columns to item fields, handles errors gracefully, provides import preview, creates import summary report. | P1 |
| E1.1.6 | As a PM, I schedule periodic imports to keep external sources in sync. | Scheduler runs import jobs at configurable intervals, detects changes since last import, updates only modified items, sends summary notifications. | P1 |

#### E1.2: Specification Management

| Story ID | User Story | Acceptance Criteria | Priority |
|----------|-----------|-------------------|----------|
| E1.2.1 | As a PM, I create formal specifications with structured requirements so compliance is auditable. | Specification model supports hierarchical sections, version control, approval workflow, export to multiple formats (PDF, HTML, Markdown). | P0 |
| E1.2.2 | As a PM, I parse specifications from documents (Markdown, ReqIF, DOORS exports) into TraceRTM items. | Parsing service extracts structured requirements, preserves hierarchy, generates unique IDs, links sections, handles multiple formats. | P0 |
| E1.2.3 | As a PM, I manage specification versions with full change tracking. | Specification versioning tracks all changes, supports diff view, allows rollback, maintains audit trail, triggers notifications on major versions. | P1 |
| E1.2.4 | As a PM, I link specifications to projects, features, and architectural decisions. | Specifications have relationships to projects (1:N), features (N:M), ADRs (N:M), graph view shows all connections. | P1 |
| E1.2.5 | As a developer, I view requirements within specifications with full context and traceability. | Specification viewer shows hierarchical structure, inline requirement details, traceability indicators (coverage, links), export options. | P0 |

#### E1.3: Auto-Linking & Suggestions

| Story ID | User Story | Acceptance Criteria | Priority |
|----------|-----------|-------------------|----------|
| E1.3.1 | As a developer, I receive automatic link suggestions based on semantic similarity so traceability is maintained with minimal effort. | Auto-link service uses embeddings to compute similarity, suggests top N matches (configurable), provides confidence scores, allows batch acceptance/rejection. | P0 |
| E1.3.2 | As a developer, I see link suggestions when creating or editing items. | UI displays link suggestions panel during item edit, shows similarity scores and preview snippets, allows one-click acceptance. | P0 |
| E1.3.3 | As a PM, I configure auto-link rules based on keywords, tags, or custom patterns. | Auto-link configuration allows regex patterns, keyword lists, tag matching, custom scoring weights, per-project overrides. | P1 |
| E1.3.4 | As a developer, auto-linking detects and suggests links for newly imported requirements. | Import pipeline triggers auto-link analysis for each imported item, stores suggestions for review, sends notification summary. | P1 |

#### E1.4: Commit & Code Linking

| Story ID | User Story | Acceptance Criteria | Priority |
|----------|-----------|-------------------|----------|
| E1.4.1 | As a developer, my Git commits are automatically linked to requirements when I reference them in commit messages. | Commit linking service monitors Git webhooks, parses commit messages for item IDs (e.g., `#123`, `REQ-456`), creates links, updates item status if configured. | P0 |
| E1.4.2 | As a developer, I view all commits linked to a requirement for code change traceability. | Item detail view shows commit history with message, author, timestamp, diff URL, file changes summary. | P0 |
| E1.4.3 | As a PM, I track which requirements have associated code changes to measure implementation progress. | Progress service aggregates commit links, calculates % of requirements with commits, displays on dashboard, flags requirements without code. | P0 |
| E1.4.4 | As a developer, I link requirements to specific files and code ranges for precise traceability. | Code indexing service scans repositories, detects annotations (comments like `// REQ-123`), creates file-level and line-range links, keeps index synchronized. | P1 |
| E1.4.5 | As a developer, I view code references inline when reviewing requirements. | Requirement detail shows linked files with syntax highlighting, supports jumping to code in IDE via deep links, shows line numbers and context. | P1 |

---

### E2: Qualification & Analysis

#### E2.1: Requirement Quality Scoring

| Story ID | User Story | Acceptance Criteria | Priority |
|----------|-----------|-------------------|----------|
| E2.1.1 | As a PM, I receive quality scores for requirements based on completeness, clarity, testability, and consistency. | Quality scoring service analyzes text using LLM, scores 0-100 across 4 dimensions, provides actionable feedback, stores scores with timestamp. | P0 |
| E2.1.2 | As a PM, I view detailed quality assessment with specific improvement suggestions. | Quality report shows dimension breakdowns, highlights issues (ambiguous terms, missing acceptance criteria), suggests improvements, tracks history. | P0 |
| E2.1.3 | As a PM, I filter requirements by quality score to prioritize review efforts. | UI supports filtering by score range, sorting by dimension scores, bulk operations on low-quality items. | P1 |
| E2.1.4 | As a PM, I receive notifications when new requirements fall below quality thresholds. | Notification service monitors quality scores, sends alerts for scores <60 (configurable), includes item link and top issues. | P1 |
| E2.1.5 | As a PM, I track quality trends over time to measure process improvements. | Analytics dashboard shows quality score distribution, trends over time, top issues by category, team/project comparisons. | P2 |

#### E2.2: Graph Analysis & Validation

| Story ID | User Story | Acceptance Criteria | Priority |
|----------|-----------|-------------------|----------|
| E2.2.1 | As a developer, I detect circular dependencies in the traceability graph so issues are caught early. | Cycle detection service uses graph algorithms (Tarjan's), identifies all cycles, provides cycle paths, suggests break points, runs on-demand and scheduled. | P0 |
| E2.2.2 | As a PM, I validate graph consistency to ensure traceability integrity. | Graph validation checks: orphaned items, broken links, invalid link types, missing required links, generates validation report with severity levels. | P0 |
| E2.2.3 | As a PM, I view graph metrics (node count, edge count, density, clustering) to understand system complexity. | Graph metrics dashboard displays key statistics, trends over time, comparison across projects, export to CSV/JSON. | P1 |
| E2.2.4 | As a developer, I find all paths between two items to understand traceability chains. | Path finding service uses shortest path algorithms, displays all paths up to depth N (configurable), visualizes paths in graph view. | P1 |
| E2.2.5 | As a PM, I detect isolated subgraphs that may indicate missing traceability. | Subgraph detection identifies disconnected components, lists items in each component, suggests connections based on similarity. | P2 |

#### E2.3: Impact Analysis

| Story ID | User Story | Acceptance Criteria | Priority |
|----------|-----------|-------------------|----------|
| E2.3.1 | As a PM, I analyze the impact of changing a requirement so I understand downstream effects. | Impact analysis service traverses graph from item, finds all dependent items (tests, code, docs), calculates impact score, generates report with affected items. | P0 |
| E2.3.2 | As a developer, I see impact visualized in a graph view to understand change propagation. | Graph visualization highlights impacted nodes (color-coded by type/severity), shows link types, supports zoom/pan, exports to image. | P0 |
| E2.3.3 | As a PM, I receive impact warnings when modifying high-impact requirements. | UI displays impact warning modal before saving changes to high-impact items (>10 dependents), shows summary of affected items, requires confirmation. | P1 |
| E2.3.4 | As a PM, I perform "what-if" impact analysis for proposed changes. | Impact simulator allows temporary graph modifications, calculates impact without committing changes, compares multiple scenarios. | P2 |

#### E2.4: Critical Path & Dependencies

| Story ID | User Story | Acceptance Criteria | Priority |
|----------|-----------|-------------------|----------|
| E2.4.1 | As a PM, I identify the critical path through requirements to prioritize work. | Critical path service finds longest path through graph weighted by complexity/effort, highlights critical items, calculates slack time for non-critical items. | P0 |
| E2.4.2 | As a PM, I analyze dependency chains to optimize scheduling. | Dependency analysis identifies blocking items, suggests parallel work opportunities, detects long dependency chains (>5 levels), generates Gantt-style view. | P1 |
| E2.4.3 | As a developer, I see which requirements block my assigned items. | Item detail shows blocking items with status indicators, provides quick links, calculates "ready to start" status based on dependencies. | P1 |

#### E2.5: Coverage Analysis

| Story ID | User Story | Acceptance Criteria | Priority |
|----------|-----------|-------------------|----------|
| E2.5.1 | As a QA engineer, I track test coverage for requirements to ensure verification completeness. | Coverage service counts test links per requirement, calculates coverage %, identifies untested requirements, supports coverage by type (unit/integration/e2e). | P0 |
| E2.5.2 | As a QA engineer, I view coverage gaps in a dashboard with drill-down capability. | Coverage dashboard shows overall %, coverage by project/module, lists untested items, filterable by category, exportable. | P0 |
| E2.5.3 | As a PM, I track code coverage metrics linked to requirements. | Code coverage integration imports coverage reports (Cobertura, lcov), links to requirements via code index, displays line/branch coverage per requirement. | P1 |
| E2.5.4 | As a PM, I generate compliance reports showing requirement verification status. | Compliance report template includes coverage matrix, verification evidence links, approval signatures, exports to PDF with letterhead. | P1 |

---

### E3: Application & Tracking

#### E3.1: Item Management (CRUD)

| Story ID | User Story | Acceptance Criteria | Priority |
|----------|-----------|-------------------|----------|
| E3.1.1 | As a developer, I create items (requirements, features, test cases) with rich metadata. | Item creation form supports: title, description (Markdown), type, status, priority, assignee, tags, custom fields, attachments, relationships. | P0 |
| E3.1.2 | As a developer, I edit items with full version history tracking. | Item updates create history entries, support rollback, show diff view, track field-level changes, log user and timestamp. | P0 |
| E3.1.3 | As a developer, I delete or archive items with cascade options. | Soft delete by default (archived), hard delete requires confirmation, cascade options: archive dependents, reassign dependents, or block if dependents exist. | P0 |
| E3.1.4 | As a developer, I search items using full-text search with filters. | Search supports: text search across title/description, filters by type/status/assignee/tags, sorting, pagination, saved searches. | P0 |
| E3.1.5 | As a developer, I bulk-edit items for efficient updates. | Bulk operations: status change, tag addition/removal, assignee change, priority update, validation before commit, undo support. | P1 |
| E3.1.6 | As a PM, I use custom item types and fields for project-specific needs. | Item spec system allows defining custom types with fields (text, number, select, date, user), field validation rules, per-type workflows. | P1 |

#### E3.2: Link Management

| Story ID | User Story | Acceptance Criteria | Priority |
|----------|-----------|-------------------|----------|
| E3.2.1 | As a developer, I create links between items with typed relationships. | Link types: implements, tests, blocks, depends_on, relates_to, derives_from, verifies, conflicts_with. Link creation validates no cycles (if directed). | P0 |
| E3.2.2 | As a developer, I view all links for an item grouped by type and direction. | Item detail shows: outgoing links (grouped by type), incoming links (reverse relationships), link creation date and creator, quick navigation. | P0 |
| E3.2.3 | As a developer, I delete links when relationships change. | Link deletion requires confirmation, logs deletion event, updates graph immediately, triggers impacted item re-analysis. | P0 |
| E3.2.4 | As a PM, I define custom link types for project-specific relationships. | Link type configuration allows: name, directionality (directed/undirected), allowed item types, validation rules, color for visualization. | P1 |
| E3.2.5 | As a developer, I see link suggestions when viewing an item. | Link suggestion panel shows: AI-suggested links (by similarity), links from related items, recent links by others, quick-add buttons. | P1 |

#### E3.3: Status Workflow

| Story ID | User Story | Acceptance Criteria | Priority |
|----------|-----------|-------------------|----------|
| E3.3.1 | As a PM, I define custom workflows with states and transitions. | Workflow configuration: define states (name, color), allowed transitions, required fields per state, approval requirements, notifications. | P0 |
| E3.3.2 | As a developer, I transition items through workflow states with validation. | Status transition validates: allowed next states, required fields populated, approval obtained (if needed), logs transition with user/timestamp. | P0 |
| E3.3.3 | As a PM, I track time spent in each workflow state for cycle time analysis. | State transition history tracks entry/exit timestamps, calculates time in state, aggregates for analytics, identifies bottlenecks. | P1 |
| E3.3.4 | As a PM, I configure state-based automation (e.g., auto-link test cases when requirement enters "Ready for Test"). | Workflow triggers: on state entry/exit, execute actions (create link, send notification, update field), conditional logic support. | P1 |

#### E3.4: Progress Tracking

| Story ID | User Story | Acceptance Criteria | Priority |
|----------|-----------|-------------------|----------|
| E3.4.1 | As a PM, I track project progress through aggregated requirement status. | Progress dashboard shows: % complete by status, burndown chart, velocity trends, milestone tracking, filterable by project/assignee. | P0 |
| E3.4.2 | As a PM, I set and track milestones with deadline alerts. | Milestone system: define milestones with dates, associate items, track completion %, send alerts for approaching deadlines or overdue items. | P0 |
| E3.4.3 | As a developer, I view my assigned items with priority and deadline indicators. | User dashboard shows: assigned items, sorted by priority/deadline, status indicators, quick actions (update status, add comment), filters. | P0 |
| E3.4.4 | As a PM, I generate progress reports for stakeholders. | Report generator: select time range, projects, metrics, export to PDF/HTML, includes charts, summary statistics, trend analysis. | P1 |

#### E3.5: Feature & ADR Management

| Story ID | User Story | Acceptance Criteria | Priority |
|----------|-----------|-------------------|----------|
| E3.5.1 | As a PM, I track features as collections of related requirements. | Feature model: name, description, status, links to requirements/tests/docs, timeline, owner, custom fields, progress calculation. | P0 |
| E3.5.2 | As a developer, I document architectural decisions as ADRs linked to implementation. | ADR model: title, context, decision, consequences, status (proposed/accepted/deprecated), links to affected components, date, participants. | P0 |
| E3.5.3 | As a developer, I view ADRs relevant to requirements I'm implementing. | Requirement detail shows: linked ADRs, ADR status, quick links to full ADR, chronological ADR timeline for context. | P1 |
| E3.5.4 | As an architect, I search and filter ADRs by status, component, or keyword. | ADR search: full-text search, filters by status/component/author/date, tagging system, export to Markdown or PDF. | P1 |

---

### E4: Verification & Validation

#### E4.1: Test Management

| Story ID | User Story | Acceptance Criteria | Priority |
|----------|-----------|-------------------|----------|
| E4.1.1 | As a QA engineer, I create test cases linked to requirements for traceability. | Test case model: name, description, steps, expected results, type (unit/integration/e2e/manual), status, priority, links to requirements. | P0 |
| E4.1.2 | As a QA engineer, I organize test cases into test suites for execution management. | Test suite model: name, description, test case list (ordered), execution config, schedule, owner, test suite hierarchy support. | P0 |
| E4.1.3 | As a QA engineer, I manage test scenarios for BDD-style testing. | Scenario model: Given/When/Then format, linked to features, supports Gherkin syntax, executable via Cucumber/SpecFlow integration. | P1 |
| E4.1.4 | As a QA engineer, I track test case versions aligned with requirement versions. | Test case versioning: tracks changes, links version to requirement version, supports diff view, allows rollback, maintains history. | P1 |
| E4.1.5 | As a QA engineer, I bulk-import test cases from external tools (TestRail, Zephyr). | Test import service: authenticates with test management tools, maps fields, preserves test suite structure, handles attachments, generates import report. | P2 |

#### E4.2: Test Execution

| Story ID | User Story | Acceptance Criteria | Priority |
|----------|-----------|-------------------|----------|
| E4.2.1 | As a QA engineer, I execute test suites manually or via CI/CD integration. | Test execution: manual run with result recording, CI/CD trigger via API, supports parallel execution, captures logs/screenshots. | P0 |
| E4.2.2 | As a QA engineer, I record test results (pass/fail/skip) with evidence. | Test run model: status, start/end time, executor, environment, logs, screenshots, linked to test cases and requirements, immutable history. | P0 |
| E4.2.3 | As a developer, I view test execution history for requirements to understand stability. | Requirement detail shows: test execution timeline, pass/fail trends, flaky test detection, latest results per test, link to full test runs. | P0 |
| E4.2.4 | As a QA engineer, I configure execution environments for consistent testing. | Execution config model: environment variables, dependencies, browser/device matrix, resource allocation, timeout settings, reusable across suites. | P1 |
| E4.2.5 | As a QA engineer, I receive notifications when critical tests fail. | Notification rules: trigger on test failure (filterable by priority/tags), includes failure details, links to logs, configurable recipients. | P1 |

#### E4.3: Coverage Tracking

| Story ID | User Story | Acceptance Criteria | Priority |
|----------|-----------|-------------------|----------|
| E4.3.1 | As a QA engineer, I track which requirements have test cases linked. | Coverage report: lists all requirements, indicates test link presence, calculates coverage %, filterable by project/module, exportable. | P0 |
| E4.3.2 | As a QA engineer, I track test execution coverage (which tests have been run recently). | Execution coverage: shows last run date per test, identifies stale tests (not run in N days), calculates execution freshness %. | P1 |
| E4.3.3 | As a developer, I import code coverage reports and link to requirements. | Coverage import service: parses Cobertura/lcov/JaCoCo formats, links to requirements via code index, displays line/branch coverage per requirement. | P1 |
| E4.3.4 | As a PM, I generate coverage reports for compliance audits. | Compliance report: traceability matrix (requirement → test → result), coverage statistics, trend charts, evidence links, PDF export with signatures. | P0 |

#### E4.4: BDD & Scenario Testing

| Story ID | User Story | Acceptance Criteria | Priority |
|----------|-----------|-------------------|----------|
| E4.4.1 | As a QA engineer, I define BDD scenarios in Gherkin format linked to features. | Scenario editor: Gherkin syntax highlighting, autocomplete for steps, linked to feature model, validation against step definitions. | P1 |
| E4.4.2 | As a developer, I execute BDD scenarios via Cucumber/SpecFlow integration. | BDD execution: triggers Cucumber/SpecFlow runner, captures results, maps to TraceRTM test runs, updates feature status based on results. | P1 |
| E4.4.3 | As a PM, I view BDD scenario coverage for features. | Feature detail shows: linked scenarios, scenario execution status, coverage by Given/When/Then clauses, gaps in scenario coverage. | P2 |

#### E4.5: Verification Reports

| Story ID | User Story | Acceptance Criteria | Priority |
|----------|-----------|-------------------|----------|
| E4.5.1 | As a QA engineer, I generate verification reports showing requirement → test → result traceability. | Verification report: lists requirements, shows linked tests, displays latest results, calculates verification %, exports to PDF/HTML. | P0 |
| E4.5.2 | As a PM, I schedule periodic verification reports for stakeholders. | Report scheduler: configure report type, filters, recipients, schedule (daily/weekly), delivery via email or dashboard, attachment format options. | P1 |
| E4.5.3 | As a compliance officer, I generate audit trail reports with timestamps and signatures. | Audit report: chronological event log, includes all changes, shows who/when/what, supports digital signatures, immutable via blockchain, PDF export. | P1 |

---

### E5: Reporting & Analytics

#### E5.1: Traceability Matrix Generation

| Story ID | User Story | Acceptance Criteria | Priority |
|----------|-----------|-------------------|----------|
| E5.1.1 | As a PM, I generate traceability matrices showing requirement → code → test relationships. | Matrix generator: row=requirements, columns=tests, cells show link status, filterable by type/status, exportable to CSV/PDF, multiple matrix views. | P0 |
| E5.1.2 | As a PM, I customize matrix views to show specific relationship types. | Matrix configuration: select item types for rows/columns, choose link types to display, add calculated columns (coverage, status), save as template. | P1 |
| E5.1.3 | As a PM, I generate hierarchical matrices showing requirement decomposition. | Hierarchical matrix: shows requirement parent/child relationships, indented view, collapsible sections, preserves hierarchy in export. | P1 |
| E5.1.4 | As a compliance officer, I generate baseline matrices for version control. | Matrix baseline: snapshot at specific date/version, compare baselines to show changes, track requirement additions/deletions, audit log of matrix generation. | P1 |

#### E5.2: Analytics Dashboards

| Story ID | User Story | Acceptance Criteria | Priority |
|----------|-----------|-------------------|----------|
| E5.2.1 | As a PM, I view a project dashboard with key metrics (progress, coverage, quality, velocity). | Dashboard widgets: progress chart, coverage %, quality score distribution, velocity trend, burndown chart, configurable layout, real-time updates. | P0 |
| E5.2.2 | As a developer, I view a personal dashboard with my assignments and recent activity. | User dashboard: assigned items (by priority/deadline), recent updates, items needing attention, team activity feed, quick actions. | P0 |
| E5.2.3 | As a PM, I create custom dashboards with saved queries and visualizations. | Dashboard builder: drag-drop widgets, choose data sources (saved queries), configure chart types, share with team, set refresh interval. | P1 |
| E5.2.4 | As an executive, I view portfolio-level analytics across multiple projects. | Portfolio dashboard: project health scores, resource allocation, risk indicators, inter-project dependencies, milestone tracking, drill-down to project detail. | P2 |

#### E5.3: Custom Reports & Export

| Story ID | User Story | Acceptance Criteria | Priority |
|----------|-----------|-------------------|----------|
| E5.3.1 | As a PM, I create custom reports using a query builder. | Report builder: visual query interface, select fields/filters/grouping/sorting, preview results, save as template, schedule delivery. | P1 |
| E5.3.2 | As a PM, I export reports to multiple formats (PDF, HTML, CSV, JSON, Excel). | Export service: format-specific renderers, preserves formatting/charts, includes metadata (generation date, filters), email delivery option. | P0 |
| E5.3.3 | As a PM, I generate executive summaries with charts and KPIs. | Executive summary template: predefined KPIs, chart selection, trend indicators, commentary section, professional styling, PDF export. | P1 |
| E5.3.4 | As a developer, I access report data via REST API for custom integrations. | Reporting API: endpoints for report data, pagination support, filtering/sorting, rate limiting, authentication, OpenAPI documentation. | P1 |

#### E5.4: Metrics & Statistics

| Story ID | User Story | Acceptance Criteria | Priority |
|----------|-----------|-------------------|----------|
| E5.4.1 | As a PM, I track project metrics (velocity, cycle time, lead time, throughput). | Metrics service: calculates metrics from historical data, displays trends, identifies anomalies, configurable calculation rules, exportable. | P1 |
| E5.4.2 | As a PM, I view quality metrics (requirement quality scores, test pass rates, defect density). | Quality dashboard: quality score trends, pass rate by test type, defect density over time, quality gates status, drill-down to items. | P1 |
| E5.4.3 | As a PM, I track team productivity metrics (items completed, review time, rework rate). | Productivity dashboard: completion rate, time in review, rework %, team comparison, individual contributor stats, trend analysis. | P2 |
| E5.4.4 | As a PM, I set metric goals and receive alerts when thresholds are breached. | Goal system: define metric targets, configure alert thresholds, send notifications on breach, dashboard shows goal progress, historical goal tracking. | P2 |

#### E5.5: Visualization

| Story ID | User Story | Acceptance Criteria | Priority |
|----------|-----------|-------------------|----------|
| E5.5.1 | As a developer, I visualize the traceability graph with interactive exploration. | Graph visualization: force-directed layout, color-coded by type/status, zoom/pan, click to view details, filter by type/status, export to image. | P0 |
| E5.5.2 | As a PM, I view dependency graphs showing requirement relationships. | Dependency graph: hierarchical layout, shows link types, highlights critical path, indicates blockers, collapsible branches, export to SVG/PNG. | P0 |
| E5.5.3 | As a PM, I visualize coverage as heatmaps showing testing density. | Coverage heatmap: requirement grid with color intensity by test count, filterable by module/type, highlights gaps, clickable cells for drill-down. | P1 |
| E5.5.4 | As a PM, I view timeline visualizations showing requirement lifecycle. | Timeline view: swimlanes by type/assignee, bars show duration in states, milestone markers, filterable by date range, Gantt-style rendering. | P1 |

---

### E6: Collaboration & Integration

#### E6.1: Real-Time Collaboration

| Story ID | User Story | Acceptance Criteria | Priority |
|----------|-----------|-------------------|----------|
| E6.1.1 | As a developer, I receive real-time updates when items I'm watching are modified. | WebSocket service pushes updates for watched items, UI updates without refresh, shows who made change, highlights new content, subscribes on view. | P0 |
| E6.1.2 | As a team member, I see presence indicators showing who else is viewing an item. | Presence system: tracks active viewers per item, displays avatars, shows last active time, updates in real-time, privacy controls. | P1 |
| E6.1.3 | As a developer, I receive notifications for @mentions in comments. | Notification service: parses comments for @username mentions, sends in-app and email notifications, links to comment context, marks as read when viewed. | P0 |
| E6.1.4 | As a team member, I collaborate via threaded comments on items. | Comment system: threaded replies, Markdown support, @mentions, file attachments, edit/delete (with history), emoji reactions, pagination. | P0 |
| E6.1.5 | As a team member, I subscribe to item changes and receive configurable notifications. | Subscription system: watch individual items or queries, configure notification frequency (instant/digest), choose channels (in-app/email/webhook), unsubscribe option. | P1 |

#### E6.2: External Tool Sync

| Story ID | User Story | Acceptance Criteria | Priority |
|----------|-----------|-------------------|----------|
| E6.2.1 | As a PM, I sync TraceRTM with GitHub Projects for two-way updates. | GitHub sync: authenticates via GitHub App, bidirectional sync (issues, PRs, milestones), conflict resolution, webhook-driven updates, manual sync trigger. | P0 |
| E6.2.2 | As a PM, I sync TraceRTM with Jira for requirement tracking. | Jira sync: OAuth authentication, field mapping configuration, bidirectional sync, handles custom fields, conflict resolution, scheduled sync + webhooks. | P0 |
| E6.2.3 | As a PM, I sync TraceRTM with Linear for issue management. | Linear sync: API key authentication, bidirectional sync, maps states/priorities, handles Linear teams/projects, webhook-driven updates. | P1 |
| E6.2.4 | As a developer, I configure custom sync rules for external integrations. | Sync configuration: define field mappings, set sync direction (one-way/two-way), configure filters (which items sync), conflict resolution strategy, error handling. | P1 |
| E6.2.5 | As a PM, I view sync status and resolve conflicts manually when automatic resolution fails. | Sync dashboard: shows sync health, lists conflicts, provides side-by-side comparison, allows manual resolution, logs all sync operations. | P1 |

#### E6.3: Webhooks & Events

| Story ID | User Story | Acceptance Criteria | Priority |
|----------|-----------|-------------------|----------|
| E6.3.1 | As a developer, I configure webhooks to notify external systems of TraceRTM events. | Webhook system: configure target URL, choose event types (item created/updated/deleted), authentication (header/signature), retry logic, delivery log. | P0 |
| E6.3.2 | As a developer, I receive webhooks from external systems to update TraceRTM. | Webhook endpoint: validates signatures, authenticates sources, processes payloads, creates/updates items, logs deliveries, returns appropriate responses. | P0 |
| E6.3.3 | As a developer, I view webhook delivery history and debug failed deliveries. | Webhook log: shows all deliveries with status, payload, response, retry attempts, allows replay, filterable by status/time, searchable. | P1 |
| E6.3.4 | As a developer, I subscribe to event streams for custom integrations. | Event bus: NATS-based event streaming, topics by entity type and action, supports fan-out to multiple consumers, message ordering guarantees. | P1 |

#### E6.4: Notifications

| Story ID | User Story | Acceptance Criteria | Priority |
|----------|-----------|-------------------|----------|
| E6.4.1 | As a user, I receive in-app notifications for relevant events. | In-app notifications: notification bell icon with unread count, dropdown list, mark as read, links to related items, auto-mark on view. | P0 |
| E6.4.2 | As a user, I receive email notifications with configurable frequency. | Email notifications: immediate or digest (daily/weekly), configurable per event type, unsubscribe link, HTML emails with context, respects quiet hours. | P0 |
| E6.4.3 | As a user, I configure notification preferences per event type and channel. | Notification settings: matrix of event types × channels (in-app/email/webhook), enable/disable per cell, frequency options, global mute. | P0 |
| E6.4.4 | As a user, I receive mobile push notifications for critical events. | Mobile push: supports iOS/Android via Firebase, triggered for critical events (OAs, urgent assignments), deep links to app, respects device settings. | P2 |

#### E6.5: AI Chat Assistant

| Story ID | User Story | Acceptance Criteria | Priority |
|----------|-----------|-------------------|----------|
| E6.5.1 | As a user, I interact with an AI assistant to query traceability data conversationally. | Chat interface: conversational UI, interprets natural language queries, returns structured results, suggests follow-up queries, maintains context. | P1 |
| E6.5.2 | As a user, I ask the AI assistant to perform actions (create items, generate reports). | AI actions: supports commands (create/update/delete items, run reports, analyze impact), confirms before executing, provides feedback, handles errors gracefully. | P1 |
| E6.5.3 | As a user, I receive AI-powered insights and recommendations. | AI insights: proactive suggestions (missing links, quality issues, coverage gaps), explains reasoning, actionable recommendations, learns from feedback. | P2 |
| E6.5.4 | As a user, I integrate the AI assistant via Slack/Teams for team collaboration. | Bot integration: responds to messages in channels, supports slash commands, provides summaries, alerts teams to issues, configurable per channel. | P2 |

---

### E7: AI & Automation

#### E7.1: MCP Server & Tools

| Story ID | User Story | Acceptance Criteria | Priority |
|----------|-----------|-------------------|----------|
| E7.1.1 | As an AI agent, I query items via MCP tools with rich filtering. | MCP tools: `search_items`, `get_item`, `list_items` with filters (type, status, assignee, tags, date range), pagination, sorting. | P0 |
| E7.1.2 | As an AI agent, I create and update items via MCP tools. | MCP tools: `create_item`, `update_item`, `delete_item` with full field support, validation, error handling, returns created/updated item. | P0 |
| E7.1.3 | As an AI agent, I manage links via MCP tools. | MCP tools: `create_link`, `delete_link`, `get_links` with type filtering, validation (no cycles), returns link details. | P0 |
| E7.1.4 | As an AI agent, I query the traceability graph via MCP tools. | MCP tools: `get_graph`, `find_path`, `analyze_impact`, `detect_cycles` with graph query parameters, returns graph data or analysis results. | P0 |
| E7.1.5 | As an AI agent, I generate reports via MCP tools. | MCP tools: `generate_matrix`, `get_coverage`, `get_metrics` with configuration parameters, returns structured data or document. | P0 |
| E7.1.6 | As an AI agent, I access specifications and documentation via MCP tools. | MCP tools: `get_specification`, `get_adr`, `search_docs` with filtering, returns structured content, supports version parameters. | P1 |
| E7.1.7 | As an AI agent, I execute tests via MCP tools. | MCP tools: `run_test_suite`, `get_test_results`, `get_execution_status` with execution parameters, returns run ID and status updates. | P1 |

#### E7.2: Agent Coordination

| Story ID | User Story | Acceptance Criteria | Priority |
|----------|-----------|-------------------|----------|
| E7.2.1 | As an AI agent, I coordinate with other agents via the agent coordination service. | Agent coordination: register agent, heartbeat mechanism, agent discovery, message passing, lock acquisition (prevents concurrent modifications). | P1 |
| E7.2.2 | As an AI agent, I execute long-running tasks via agent sessions with checkpoint/resume. | Agent session model: creates session, tracks state, supports checkpoints, allows resume after failure, timeout handling, cleanup on completion. | P1 |
| E7.2.3 | As a system, I monitor agent health and performance. | Agent monitoring: tracks agent activity, detects stalls, measures response times, logs errors, alerts on anomalies, dashboard shows agent status. | P1 |
| E7.2.4 | As a system, I collect agent performance metrics for optimization. | Agent metrics: counts tool invocations, measures latency, tracks success/failure rates, identifies bottlenecks, exports to Prometheus. | P2 |

#### E7.3: Workflow Automation

| Story ID | User Story | Acceptance Criteria | Priority |
|----------|-----------|-------------------|----------|
| E7.3.1 | As a PM, I define automated workflows triggered by item state changes. | Workflow builder: visual designer, define triggers (state change, field update, schedule), add actions (update item, create link, send notification), conditional logic. | P1 |
| E7.3.2 | As a PM, I execute workflows via Temporal for reliability and monitoring. | Temporal integration: workflow definitions in code, execution history, retry logic, timeout handling, monitoring dashboard, activity functions. | P1 |
| E7.3.3 | As a PM, I schedule periodic workflows (e.g., nightly validation, weekly reports). | Workflow scheduler: cron-based scheduling, timezone support, execution history, skip if previous run still active, manual trigger option. | P1 |
| E7.3.4 | As a developer, I create custom workflow activities in Python/Go. | Workflow SDK: activity registration, input/output schemas, error handling, progress reporting, testable independently, documentation. | P2 |

#### E7.4: Code Analysis & Indexing

| Story ID | User Story | Acceptance Criteria | Priority |
|----------|-----------|-------------------|----------|
| E7.4.1 | As a developer, my code repositories are indexed for traceability. | Code indexing service: clones repos, parses source files, extracts annotations (comments with requirement IDs), stores file/line mappings, incremental updates. | P1 |
| E7.4.2 | As a developer, I search code by requirement ID to find implementations. | Code search: query by requirement ID, returns files and line ranges, syntax highlighting, supports multiple languages, filterable by repo/branch. | P1 |
| E7.4.3 | As a developer, code index updates automatically on Git push. | Git webhook integration: receives push events, triggers incremental re-index for changed files, updates links, notifies on new requirement references. | P1 |
| E7.4.4 | As a developer, AI analyzes code to suggest requirement links. | AI code analysis: analyzes function/class signatures and docstrings, compares to requirements, suggests links with confidence scores, learns from feedback. | P2 |

#### E7.5: AI-Powered Insights

| Story ID | User Story | Acceptance Criteria | Priority |
|----------|-----------|-------------------|----------|
| E7.5.1 | As a PM, AI suggests missing traceability links based on semantic analysis. | AI link suggestion: embeds item descriptions, calculates similarity, suggests links with confidence scores, provides rationale, learns from accept/reject. | P1 |
| E7.5.2 | As a PM, AI identifies requirements that may be outdated or duplicates. | AI requirement analysis: detects similar requirements across projects, flags potential duplicates, identifies outdated language patterns, suggests consolidation. | P2 |
| E7.5.3 | As a developer, AI generates requirement text from code analysis. | AI requirement generation: analyzes functions/classes, generates requirement descriptions, creates draft items for review, links to code, maintains human-in-loop. | P2 |
| E7.5.4 | As a PM, AI predicts requirement implementation effort. | AI effort estimation: analyzes requirement text and complexity, considers historical data, predicts effort (story points/hours), provides confidence interval. | P2 |

---

## 6. Non-Functional Requirements

| Category | Requirement | Target | Priority |
|----------|-------------|--------|----------|
| **Performance** | REST API response time | <200ms p95 for reads, <500ms p95 for writes | P0 |
| **Performance** | Graph query response time | <100ms p95 for depth ≤3, <1s for depth ≤5 | P0 |
| **Performance** | Search latency | <300ms p95 for full-text search | P0 |
| **Performance** | Real-time update latency | <100ms from event to WebSocket delivery | P1 |
| **Performance** | Import throughput | >1000 items/minute for bulk imports | P1 |
| **Scalability** | Concurrent users | Support 1000+ concurrent users | P0 |
| **Scalability** | Graph size | Support graphs with >1M nodes, >5M edges | P1 |
| **Scalability** | Database growth | Handle >10M items with consistent performance | P1 |
| **Availability** | Service uptime | 99.5% availability (excluding maintenance) | P0 |
| **Availability** | Data durability | Zero data loss on single component failure | P0 |
| **Availability** | Recovery time | RTO <4 hours, RPO <1 hour | P0 |
| **Security** | Authentication | Support SSO (SAML, OAuth), MFA, session management | P0 |
| **Security** | Authorization | RBAC with granular permissions, project-level isolation | P0 |
| **Security** | Audit trail | Immutable log of all changes via blockchain | P0 |
| **Security** | Data encryption | Encrypt at rest (DB, S3) and in transit (TLS 1.3) | P0 |
| **Security** | Secrets management | Vault integration for API keys, tokens | P0 |
| **Usability** | Learning curve | New users productive within 2 hours | P1 |
| **Usability** | Accessibility | WCAG 2.1 Level AA compliance | P1 |
| **Usability** | Mobile support | Responsive design, touch-optimized | P1 |
| **Maintainability** | Code coverage | >80% line coverage for critical paths | P0 |
| **Maintainability** | API versioning | Semantic versioning, deprecation notices >6 months | P0 |
| **Maintainability** | Documentation | API docs, user guides, architecture docs, runbooks | P0 |
| **Observability** | Metrics | Prometheus metrics for all services | P0 |
| **Observability** | Logging | Structured logging, centralized aggregation | P0 |
| **Observability** | Tracing | Distributed tracing for cross-service requests | P1 |
| **Observability** | Health checks | Liveness and readiness probes for all services | P0 |
| **Compliance** | Standards support | ISO 26262, DO-178C, FDA 62304 traceability patterns | P1 |
| **Compliance** | Data retention | Configurable retention policies, GDPR compliance | P1 |
| **Compliance** | Export formats | Support compliance-ready exports (PDF, OSLC ReqIF) | P1 |
| **Interoperability** | API-first design | All features accessible via REST and GraphQL APIs | P0 |
| **Interoperability** | Webhooks | Event-driven integration with external tools | P0 |
| **Interoperability** | Import/Export | Support common formats (CSV, JSON, ReqIF, Markdown) | P0 |

---

## 7. Technology Stack

**Backend:**
- **Python** (FastAPI) - REST API, business logic, MCP server
- **Go** (Echo) - High-performance services, graph operations, real-time features
- **PostgreSQL** - Primary relational database
- **Neo4j** - Graph database for traceability graph
- **Redis** - Caching and session management
- **NATS** - Event bus for async messaging
- **Temporal** - Workflow orchestration
- **S3-compatible storage** - File and artifact storage

**Frontend:**
- **React** + **TypeScript** - Web application
- **Electron** - Desktop application
- **Vite** - Build tooling
- **TanStack Query** - Data fetching and caching
- **Zustand** - State management
- **D3.js / Cytoscape.js** - Graph visualization

**AI/ML:**
- **MCP Protocol** - AI agent integration
- **OpenAI / Anthropic APIs** - LLM for analysis and generation
- **Embeddings** - Semantic similarity (sentence-transformers or API-based)

**Infrastructure:**
- **Docker** - Containerization
- **Process Compose** - Local development orchestration
- **Caddy** - Reverse proxy and TLS termination
- **Prometheus + Grafana** - Metrics and monitoring
- **Sentry** - Error tracking

**Development:**
- **Alembic** - Database migrations (Python)
- **Atlas** - Database migrations (Go)
- **pytest** - Python testing
- **Go testing** - Go testing
- **Vitest** - Frontend testing
- **Playwright** - E2E testing

---

## 8. Delivery Phases

### Phase 1: Foundation (Months 1-2)
**Goal:** Core data model, basic CRUD, simple graph
- E3.1: Item Management (CRUD)
- E3.2: Link Management
- E1.1: Import from GitHub (basic)
- E5.1: Simple traceability matrix
- E6.1: Basic notifications

### Phase 2: Intelligence (Months 3-4)
**Goal:** Analysis, quality, automation
- E2.1: Requirement Quality Scoring
- E2.2: Graph Analysis & Validation
- E2.3: Impact Analysis
- E1.3: Auto-Linking & Suggestions
- E7.1: MCP Server & Core Tools

### Phase 3: Testing & Validation (Months 5-6)
**Goal:** Test management, execution, coverage
- E4.1: Test Management
- E4.2: Test Execution
- E4.3: Coverage Tracking
- E4.5: Verification Reports
- E2.5: Coverage Analysis

### Phase 4: Collaboration & Integration (Months 7-8)
**Goal:** Real-time features, external integrations
- E6.1: Real-Time Collaboration
- E6.2: External Tool Sync (Jira, Linear)
- E6.3: Webhooks & Events
- E1.2: Specification Management
- E3.5: Feature & ADR Management

### Phase 5: Analytics & Insights (Months 9-10)
**Goal:** Reporting, dashboards, AI insights
- E5.2: Analytics Dashboards
- E5.3: Custom Reports & Export
- E5.4: Metrics & Statistics
- E5.5: Visualization
- E7.5: AI-Powered Insights

### Phase 6: Automation & Scale (Months 11-12)
**Goal:** Workflows, agent coordination, optimization
- E7.2: Agent Coordination
- E7.3: Workflow Automation
- E7.4: Code Analysis & Indexing
- E2.4: Critical Path & Dependencies
- E4.4: BDD & Scenario Testing

---

## 9. Success Criteria

**Launch Readiness:**
- All P0 stories implemented and tested
- >80% test coverage for core services
- <200ms p95 REST API latency
- 99% uptime during 2-week soak test
- Security audit passed
- Documentation complete (user guides, API docs, runbooks)

**Adoption Metrics (3 months post-launch):**
- 80% of development team active weekly
- >1000 items managed across projects
- >5000 links created (traceability established)
- >50 MCP tool invocations per day (AI agent usage)
- >90% user satisfaction (NPS survey)

**Business Impact (6 months post-launch):**
- 50% reduction in traceability gaps (measured by audit)
- 30% reduction in time to generate compliance reports
- 25% improvement in test coverage
- 40% reduction in time to assess change impact

---

## 10. Risks & Mitigations

| Risk | Likelihood | Impact | Mitigation |
|------|-----------|--------|-----------|
| Graph query performance degrades with scale | Medium | High | Implement caching, optimize Neo4j indexes, use materialized views for common queries |
| External integration APIs change/break | High | Medium | Version all integrations, implement adapter pattern, fallback to manual import |
| AI/LLM costs exceed budget | Medium | Medium | Implement token usage tracking, cache embeddings, use smaller models where appropriate |
| User adoption lags due to complexity | Medium | High | Invest in onboarding UX, provide templates and wizards, offer training materials |
| Data migration from legacy tools fails | Low | High | Thorough testing with production data clones, rollback plan, incremental migration option |
| Real-time WebSocket scale bottleneck | Medium | Medium | Implement horizontal scaling for WebSocket servers, use Redis pub/sub for distribution |
| Compliance requirements change | Low | High | Design extensible audit trail, maintain flexibility in export formats, stay current with standards |

---

## 11. Open Questions

1. **Compliance Standards Prioritization:** Which industry standards (ISO 26262, DO-178C, FDA 62304, etc.) should be prioritized for Phase 1 vs later phases?
2. **AI Model Selection:** Should we use API-based LLMs (OpenAI, Anthropic) or self-hosted models for sensitive data environments?
3. **Multi-Tenancy:** Is full multi-tenancy required (shared infrastructure, isolated data) or is project-level isolation sufficient?
4. **Mobile App:** Is a native mobile app required, or is responsive web sufficient for mobile users?
5. **Offline Support:** Do users need offline capabilities (especially for desktop app), or is always-online acceptable?
6. **Enterprise SSO:** Which SSO providers must be supported (SAML, OAuth, LDAP)? Is WorkOS sufficient or are custom integrations needed?
7. **On-Premise Deployment:** Is on-premise/air-gapped deployment a requirement, or is cloud-only acceptable?
8. **Licensing Model:** Per-user, per-project, or enterprise unlimited? How should AI features be monetized?

---

## Appendix A: Epic-to-Entity Mapping

| Epic | Related Models | Related Services | Related APIs |
|------|---------------|------------------|--------------|
| E1: Discovery & Capture | `item`, `specification`, `integration`, `github_project`, `external_link` | `import_service`, `github_import_service`, `jira_import_service`, `ingestion_service`, `auto_link_service`, `commit_linking_service` | `/integrations/*`, `/specifications/*` |
| E2: Qualification & Analysis | `requirement_quality`, `graph`, `graph_snapshot`, `graph_change` | `requirement_quality_service`, `graph_analysis_service`, `cycle_detection_service`, `dependency_analysis_service`, `impact_analysis_service`, `critical_path_service` | `/quality/*`, `/graph/analyze`, `/analysis/impact` |
| E3: Application & Tracking | `item`, `link`, `feature`, `adr`, `workflow_run`, `status_workflow` | `item_service`, `link_service`, `feature_service`, `adr_service`, `status_workflow_service`, `progress_service` | `/items/*`, `/links/*`, `/features/*`, `/adrs/*` |
| E4: Verification & Validation | `test_case`, `test_suite`, `test_run`, `test_coverage`, `scenario`, `execution` | `test_case_service`, `test_run_service`, `coverage_service`, `scenario_service`, `verification_service`, `execution_service` | `/tests/*`, `/execution/*`, `/coverage/*` |
| E5: Reporting & Analytics | `view`, `item_view`, `metrics` | `traceability_matrix_service`, `advanced_analytics_service`, `spec_analytics_service`, `stats_service`, `visualization_service` | `/reports/*`, `/analytics/*`, `/metrics/*` |
| E6: Collaboration & Integration | `notification`, `event`, `webhook_integration`, `github_app_installation` | `notification_service`, `event_service`, `webhook_service`, `sync_service`, `external_integration_service`, `github_project_service` | `/notifications/*`, `/webhooks/*`, `/websocket/*` |
| E7: AI & Automation | `agent`, `agent_session`, `agent_checkpoint`, `codex_agent`, `workflow_run` | `agent_coordination_service`, `agent_monitoring_service`, `ai_service`, `workflow_executor`, `code_index_service` | `/agents/*`, `/chat/*`, `/mcp/*` |

---

## Appendix B: Glossary

| Term | Definition |
|------|------------|
| **ADR** | Architecture Decision Record - documents significant architectural decisions |
| **BDD** | Behavior-Driven Development - testing approach using Given/When/Then scenarios |
| **Blockchain** | Immutable audit trail for compliance and tamper-evident logging |
| **Coverage** | Percentage of requirements with linked tests or code |
| **Critical Path** | Longest chain of dependencies determining minimum project duration |
| **Cycle** | Circular dependency in traceability graph (usually indicates an error) |
| **DAG** | Directed Acyclic Graph - graph structure with no cycles |
| **Gherkin** | Language for BDD scenarios (Given/When/Then format) |
| **Graph** | Network representation of items (nodes) and links (edges) |
| **Impact Analysis** | Process of determining downstream effects of a change |
| **Item** | Generic entity representing requirements, features, tests, etc. |
| **Link** | Relationship between two items (typed: implements, tests, depends_on, etc.) |
| **MCP** | Model Context Protocol - standard for AI agent tool integration |
| **Specification** | Formal document containing structured requirements |
| **Traceability** | Ability to trace relationships between requirements, code, and tests |
| **Traceability Matrix** | Table showing relationships between requirements and verification artifacts |
| **Workflow** | Sequence of states and transitions defining item lifecycle |

---

**End of Document**
