An LM Studio plugin that acts as your personal growth coach for the LLM era — tracking skills, learning sessions, goals, and resources, and generating personalised roadmaps to help you level up as an AI-era developer.
The skills that matter for developers are shifting fast. AI is replacing boilerplate work, amplifying system design and architecture, and making timeless fundamentals more valuable than ever. This plugin helps you:
Load the built plugin in LM Studio.
| Field | Default | Description |
|---|---|---|
| Data Path | ~/developer-growth | Where your growth data is stored |
| Your Name | — | Used to personalise reports |
| Current Role | Developer | e.g. Backend Engineer, ML Engineer, Student |
| Target Role | — | Where you want to be, e.g. AI Engineer, Staff Engineer |
| Years of Experience | 3 | Calibrates learning path depth and project difficulty |
| Weekly Learning Goal | 300 min | Target learning time per week for streak tracking |
| Max Search Results | 8 | Results returned per resource search |
The plugin tracks 18 skill areas across four tiers:
LLM-Era Core
Timeless Foundations (AI amplifies these, never replaces them)
cs_fundamentals — Algorithms, data structures, complexity, concurrencysoftware_architecture — Design patterns, modularity, system decompositiondata_engineering — Pipelines, ETL, data quality, streamingdevops_and_infra — CI/CD, containers, cloud, infrastructure as codeAdjacent High-Value
product_and_communication — Problem framing, stakeholder communication, shippingother — Anything else worth trackingrate_skill — Rate your proficiency in a skill (1–10)
get_skill_map — View your full skill map with ASCII progress bars
Returns all rated skills sorted by category with visual progress bars (█░).
assess_skill_gaps — Get role-specific gap analysis
Compares your ratings against expected levels for your target role. Returns critical gaps, growth areas, and prioritised next steps.
log_session — Record a learning session
format: reading, video, practice, project, course, podcast, otherget_stats — View learning statistics
Returns total hours, sessions per category, streak, weekly goal %, most studied topics, and recent momentum.
list_sessions — Browse past learning sessions
set_goal — Set a learning goal
status progresses through: active → completed / paused / abandonedupdate_goal — Update goal status or notes
list_goals — List all goals
Filter by: active, completed, paused, abandoned.
add_resource — Save a learning resource
list_resources — Browse your resource library
update_resource — Update resource status or rating
search_resources — Search curated AI learning sources on the web
Searches authoritative sources: eugeneyan.com, simonwillison.net, lilianweng.github.io, huyenchip.com, Arxiv, Hugging Face, and more.
generate_learning_path — Generate a phased learning roadmap
Returns a 4-phase plan: Foundation → Core Skills → Build Projects → Advanced Topics, with curated resources and project ideas at each phase.
generate_study_plan — Generate a weekly study schedule
Allocates time across your focus areas with daily session recommendations.
weekly_review — Run your weekly growth review
Summarises the past 7 days: sessions logged, time invested vs goal, progress on active goals, and suggested focus for next week.
explain_concept — Get a concept explained at your level
depth: beginner, intermediate, advancedgenerate_project_idea — Get a hands-on project idea to build a skill
scope: weekend, week, monthsearch_ai_trends — Search for current AI/ML developments
Fetches recent news, papers, and community discussions on a topic.
compare_ai_tools — Compare tools, frameworks, or approaches
Returns strengths, weaknesses, when to use each, and community consensus.
export_growth_report — Export a full growth report
format: summary (default) or detailedgrowth-report-YYYY-MM-DD.txtStarting out:
"I'm a backend engineer with 4 years of experience trying to move into AI engineering. Where should I start?"
The plugin will call assess_skill_gaps and generate_learning_path to give you a concrete, role-specific roadmap.
Daily tracking:
"I just spent 90 minutes going through the LangGraph docs and built a basic agent loop."
→ log_session(topic="LangGraph agents", durationMinutes=90, category="agents_and_orchestration", format="practice")
Weekly planning:
"Run my weekly review and suggest what to focus on this week."
→ weekly_review() + generate_study_plan()
Skill assessment:
"Rate my RAG skills at 4/10 — I understand the concept but haven't built a production system."
→ rate_skill(category="rag_and_retrieval", rating=4, notes="...")
Project ideas:
"Give me a weekend project to improve my LLM evaluation skills."
→ generate_project_idea(skill="llm_evaluation", scope="weekend")
Staying current:
"What's happening with reasoning models and inference-time compute right now?"
→ search_ai_trends(topic="reasoning models inference-time compute")
| Rating | Meaning |
|---|---|
| 1–2 | Heard of it, no hands-on experience |
| 3–4 | Read about it, minimal practice |
| 5–6 | Built something with it, understand core concepts |
| 7–8 | Comfortable, used in real projects |
| 9–10 | Deep expertise, could teach it |
All data is stored locally as JSON at ~/developer-growth/ (or your configured dataPath):
No data leaves your machine. No API keys required.
AI is replacing: Boilerplate code, simple CRUD, basic scripting, routine data transformation
AI is amplifying: System design, architecture decisions, domain expertise, evaluation and judgment
Timeless skills (more valuable than ever): Problem decomposition, deep CS fundamentals, communication, debugging mental models
The developers who thrive won't be the ones who know the most syntax — they'll be the ones who can decompose hard problems, evaluate AI output critically, design reliable systems, and ship products that matter. This plugin helps you build exactly those skills.
prompt_engineering — Prompt design, chain-of-thought, few-shot, system promptsrag_and_retrieval — RAG pipelines, chunking, hybrid search, re-rankingagents_and_orchestration — Tool use, multi-agent systems, LangGraph, CrewAIllm_evaluation — Evals, benchmarks, LLM-as-judge, regression testingai_assisted_coding — Using AI tools as a force multiplier in your workflowllmops_production — Deployment, observability, cost management, latencysystem_design_ai — Designing reliable, scalable AI-powered systemsfine_tuning_and_peft — LoRA, QLoRA, instruction tuning, DPOopen_source_llms — Local models, Ollama, LM Studio, GGUF, quantisationai_security_and_safety — Prompt injection, jailbreaks, guardrails, red-teamingvector_databases — Pinecone, pgvector, Qdrant, FAISS, embedding strategiesmultimodal_ai — Vision, audio, video models and pipelinestype: article, paper, repo, course, video, podcast, book, tool, otherstatus: want_to_read, in_progress, completed, archivedcd developer-growth-plugin
npm install
npx tsc
rate_skill(category, rating, notes?)
get_skill_map()
assess_skill_gaps()
log_session(topic, durationMinutes, category, format?, notes?, resourceUrl?)
get_stats()
list_sessions(limit?, category?, search?)
set_goal(title, description, category, targetDate?, milestones?)
update_goal(goalId, status?, notes?, completedAt?)
list_goals(status?)
add_resource(title, url, category, type?, description?, tags?)
list_resources(category?, type?, status?, search?)
update_resource(resourceId, status?, rating?, notes?)
search_resources(query, category?)
generate_learning_path(targetSkill, currentLevel?, timeframeWeeks?)
generate_study_plan(focusAreas, availableHoursPerWeek, durationWeeks?)
weekly_review()
explain_concept(concept, depth?)
generate_project_idea(skill, scope?)
search_ai_trends(topic?)
compare_ai_tools(toolA, toolB, useCase?)
export_growth_report(format?)
~/developer-growth/
growth.json # skills, sessions, resources, goals
growth-report-*.txt # exported reports