context

name	context
version	1.0.0
description	[Utilities] Use when you need to load project context for current session.
disable-model-invocation	false

Quick Summary

Goal: Load project context for the current session (git status, branch info, recent changes).

Workflow:

1. Gather -- Run git status, branch info, recent commits
2. Analyze -- Identify current work context and pending changes
3. Present -- Summarize context for session awareness

Key Rules:

• Provides situational awareness at session start
• Shows branch, uncommitted changes, recent commits
• Non-destructive: read-only operation

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

Load Project Context

Load current development context to help with subsequent tasks.

Git Status

git status --short
git branch --show-current

Recent Activity

# Recent commits
git log --oneline -5

# Uncommitted changes
git diff --stat

Project Pattern Discovery

Read docs/project-config.json for project-specific module paths. Check modules[] for service/app list, or fall back to backendServices.serviceMap / frontendApps.appMap in older configs. If file not found, discover structure dynamically:

# Find backend service directories
find src/ -name "*.csproj" -maxdepth 4 | head -20

# Find frontend app directories
find src/ -name "package.json" -maxdepth 3 | head -10

# Find shared libraries
find . -path "*/libs/*" -name "package.json" -maxdepth 4 | head -10

Development Patterns

Backend: Clean Architecture + CQRS + Entity Events Frontend: Component framework + state management

Current Session Focus

Based on the git status, identify:

• What files are being worked on
• What feature/fix is in progress
• Any uncommitted changes that need attention

Summarize the current state to help with subsequent tasks.

---

[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.

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.

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

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