dependency

name	dependency
version	2.0.0
description	[Project Management] Use when you need to map and visualize feature dependencies between modules, services, and work items.

Quick Summary

Goal: Analyze and visualize dependencies between features, services, or work items to identify blockers and critical paths.

Workflow:

1. Identify Scope — Single feature, module, or full release
2. Classify Dependencies — Data, Service, UI, or Infrastructure types
3. Build Graph — Create Mermaid dependency diagram
4. Find Critical Path — Longest blocking chain; mark ready-to-start items
5. Deliver Report — Summary, graph, critical path, risks

Key Rules:

• Respect microservice boundaries (cross-service = message bus only)
• Flag circular dependencies as errors
• Not for package/npm upgrades (use package-upgrade instead)

Be skeptical. Apply critical thinking, sequential thinking. Every claim needs traced proof, confidence percentages (Idea should be more than 80%).

Dependency Mapping

Purpose

Analyze and visualize dependencies between features, services, modules, or work items to identify blockers, critical paths, and safe execution order.

When to Use

• Planning feature implementation sequence across modules
• Identifying what blocks a specific feature or work item
• Mapping cross-service dependencies (backend-to-backend, frontend-to-backend)
• Understanding critical path for a release or milestone
• Analyzing impact of changing a shared module or entity

When NOT to Use

• Single-service code changes with no cross-boundary impact -- just implement directly
• Performance analysis -- use arch-performance-optimization instead
• Security dependency auditing -- use arch-security-review instead
• Package/npm dependency upgrades -- use package-upgrade instead

Prerequisites

• Read the feature/PBI/plan files to understand scope
• Access to docs/project-reference/project-structure-reference.md for service boundary reference
• Understand the project's microservice boundaries (search src/Services/ for service list)

Workflow

Step 1: Identify Scope

Determine what to map:

• Single feature: Find all files, services, and entities it touches
• Module/service: Map all inbound and outbound dependencies
• Release/milestone: Map all features and their inter-dependencies

Step 2: Classify Dependencies

For each dependency found, classify by type:

Type	Direction	Description	Example
Data	Entity A requires Entity B	Foreign key, navigation property, shared ID	Employee requires Company
Service	Service A calls Service B	Message bus, API call, event consumer	Service A consumes entity events from Service B
UI	Component A embeds Component B	Shared component, library dependency	Feature form uses shared component library select
Infrastructure	Feature needs infra change	Database migration, config, new queue	New feature needs Redis cache key

Step 3: Build Dependency Graph

Use Mermaid syntax for visualization:

graph TD
    A[Feature A] -->|data| B[Feature B]
    A -->|service| C[Feature C]
    B -->|blocks| D[Feature D]
    C -->|blocks| D
    style D fill:#f96,stroke:#333

Step 4: Identify Critical Path

• Find the longest chain of blocking dependencies
• Mark items with no blockers as "ready to start"
• Flag circular dependencies as errors

Step 5: Deliver Report

Output structured dependency report (see Output Format).

Output Format

## Dependency Map: [Feature/Module Name]

### Summary

- Total items: N
- Ready to start: N (no blockers)
- Blocked: N
- Critical path length: N steps

### Dependency Graph

[Mermaid diagram]

### Critical Path

1. [Item A] -- no blockers, estimated: Xd
2. [Item B] -- blocked by: A, estimated: Xd
3. [Item C] -- blocked by: B, estimated: Xd

### Dependency Details

| Item | Type                  | Depends On | Blocks | Status        |
| ---- | --------------------- | ---------- | ------ | ------------- |
| ...  | data/service/UI/infra | ...        | ...    | ready/blocked |

### Risks

- [Circular dependency / tight coupling / single point of failure]

Examples

Example 1: Backend Cross-Service Feature

Input: "Map dependencies for adding a new Coaching feature in {ServiceA}"

Analysis:

graph TD
    E[Employee Entity - ServiceA] -->|data| C[Coaching Entity]
    U[User Entity - AuthService] -->|service| C
    C -->|service| N[Notification - ServiceB]
    C -->|UI| CF[Coaching Form Component]
    CF -->|UI| BC[shared-components select]

Critical path: Employee Entity -> Coaching Entity -> Coaching API -> Coaching Form Ready to start: Employee Entity already exists, shared component select exists Blocked: Coaching Entity creation, then API, then UI

Example 2: Frontend Module Dependency

Input: "What blocks the new Dashboard widget in {AnalyticsService}?"

Analysis:

graph TD
    GA[Source API - ServiceA] -->|service| GE[Event Bus Message]
    GE -->|service| GC[Consumer - AnalyticsService]
    GC -->|data| GS[Summary Entity]
    GS -->|UI| GW[Dashboard Widget]
    GW -->|UI| DC[Dashboard Container]

Blockers identified:

1. Event Bus Message producer must exist in ServiceA (exists: yes)
2. Consumer must be created in AnalyticsService (exists: no -- BLOCKER)
3. Summary Entity for aggregated data (exists: no -- BLOCKER)

Related Skills

• project-manager -- for sprint planning and status tracking
• feature-implementation -- for implementing features after dependency analysis
• arch-cross-service-integration -- for designing cross-service communication
• package-upgrade -- for npm/NuGet package dependency upgrades

---

[IMPORTANT] Use TaskCreate to break ALL work into small tasks BEFORE starting — including tasks for each file read. This prevents context loss from long files. For simple tasks, AI MUST ATTENTION ask user whether to skip.

Prerequisites: MUST ATTENTION READ before executing:

AI Mistake Prevention — Failure modes to avoid on every task:

Check downstream references before deleting. Deleting components causes documentation and code staleness cascades. Map all referencing files before removal. Verify AI-generated content against actual code. AI hallucinates APIs, class names, and method signatures. Always grep to confirm existence before documenting or referencing. Trace full dependency chain after edits. Changing a definition misses downstream variables and consumers derived from it. Always trace the full chain. Trace ALL code paths when verifying correctness. Confirming code exists is not confirming it executes. Always trace early exits, error branches, and conditional skips — not just happy path. When debugging, ask "whose responsibility?" before fixing. Trace whether bug is in caller (wrong data) or callee (wrong handling). Fix at responsible layer — never patch symptom site. Assume existing values are intentional — ask WHY before changing. Before changing any constant, limit, flag, or pattern: read comments, check git blame, examine surrounding code. Verify ALL affected outputs, not just the first. Changes touching multiple stacks require verifying EVERY output. One green check is not all green checks. Holistic-first debugging — resist nearest-attention trap. When investigating any failure, list EVERY precondition first (config, env vars, DB names, endpoints, DI registrations, data preconditions), then verify each against evidence before forming any code-layer hypothesis. Surgical changes — apply the diff test. Bug fix: every changed line must trace directly to the bug. Don't restyle or improve adjacent code. Enhancement task: implement improvements AND announce them explicitly. Surface ambiguity before coding — don't pick silently. If request has multiple interpretations, present each with effort estimate and ask. Never assume all-records, file-based, or more complex path.

Critical Thinking Mindset — Apply critical thinking, sequential thinking. Every claim needs traced proof, confidence >80% to act. Anti-hallucination: Never present guess as fact — cite sources for every claim, admit uncertainty freely, self-check output for errors, cross-reference independently, stay skeptical of own confidence — certainty without evidence root of all hallucination.

Understand Code First — HARD-GATE: Do NOT write, plan, or fix until you READ existing code.

1. Search 3+ similar patterns (grep/glob) — cite file:line evidence
2. Read existing files in target area — understand structure, base classes, conventions
3. Run python .claude/scripts/code_graph trace <file> --direction both --json when .code-graph/graph.db exists
4. Map dependencies via connections or callers_of — know what depends on your target
5. Write investigation to .ai/workspace/analysis/ for non-trivial tasks (3+ files)
6. Re-read analysis file before implementing — never work from memory alone
7. NEVER invent new patterns when existing ones work — match exactly or document deviation

BLOCKED until: - [ ] Read target files - [ ] Grep 3+ patterns - [ ] Graph trace (if graph.db exists) - [ ] Assumptions verified with evidence

• MANDATORY IMPORTANT MUST ATTENTION search 3+ existing patterns and read code BEFORE any modification. Run graph trace when graph.db exists.

MUST ATTENTION apply critical thinking — every claim needs traced proof, confidence >80% to act. Anti-hallucination: never present guess as fact.

MUST ATTENTION apply AI mistake prevention — holistic-first debugging, fix at responsible layer, surface ambiguity before coding, re-read files after compaction.

Closing Reminders

• MANDATORY IMPORTANT MUST ATTENTION break work into small todo tasks using TaskCreate BEFORE starting
• MANDATORY IMPORTANT MUST ATTENTION search codebase for 3+ similar patterns before creating new code
• MANDATORY IMPORTANT MUST ATTENTION cite file:line evidence for every claim (confidence >80% to act)
• MANDATORY IMPORTANT MUST ATTENTION add a final review todo task to verify work quality MANDATORY IMPORTANT MUST ATTENTION READ the following files before starting:

[TASK-PLANNING] Before acting, analyze task scope and systematically break it into small todo tasks and sub-tasks using TaskCreate.