Init Context

Community

vicnaum

init-context

Build a complete mental map of a project through phased exploration so you can work effectively without rediscovering things. Use when the user wants to: (1) Onboard onto a new or unfamiliar codebase, (2) Get a full project overview or briefing, (3) Understand project architecture, structure, and open work, (4) Initialize context at the start of a deep work session, (5) Explore and summarize a repository end-to-end. Triggers on requests like "explore this repo", "get familiar with this project", "give me a project overview", "onboard me", "init context", or any request to deeply understand a codebase before working on it.

Overview

Publisher	vicnaum
Repository	`vics-agent-skills`
Skill name	`init-context`
Stars	53
Forks	5
Bundled files	Instructions only
Links	Skill source Repository

Markdown instructions
A SKILL.md file the model loads on demand, so it only costs tokens when a request actually matches.
Works with any LLM
AI skills are plain Markdown, not provider-specific code, so this works with GPT, Claude, Gemini, Grok, or a local model.
Self-contained
Everything the model needs lives in the instructions — no extra files to sync.
Open source
Published by vicnaum on GitHub. Read the source before you install it.

Installation

Install the Init Context AI skill in TypingMind to use it with any LLM, or drop it into another agent that reads SKILL.md.

Install in TypingMind

TypingMind installs a skill straight from its GitHub folder — it reads SKILL.md, bundles the resource files, and stores the result locally.

Open the app and go to Plugins → Skills.
Choose "Install from GitHub".
Paste the skill folder URL below and confirm.
https://github.com/vicnaum/vics-agent-skills/tree/main/skills/init-context
Enable the skill in any chat where you want it available.

Plugins → Skills → Add skill → From GitHub URL, then paste the folder URL and press Continue.

Install in another agent

Any agent that reads the Agent Skills format can use this skill — copy the folder into that agent's skills directory.

Claude Code — .claude/skills

git clone --depth 1 https://github.com/vicnaum/vics-agent-skills.git /tmp/vics-agent-skills
mkdir -p .claude/skills
cp -r /tmp/vics-agent-skills/skills/init-context .claude/skills/init-context

Restart Claude Code after copying so it picks up the new skill.

Use it in TypingMind

Enable Init Context in any TypingMind chat and the model takes it from there. Its name and description sit in the system prompt, and the moment a request matches, the model loads the full instructions itself — you never invoke it by hand, and it costs no tokens until it is actually used.

The model loads Init Context on its own as soon as a request matches it.

Works with any AI model

AI skills are plain Markdown instructions rather than provider-specific code, so Init Context is not tied to the model it was written for. Install it once in TypingMind and use it with GPT-5, Claude, Gemini, Grok, DeepSeek, Mistral, Llama, or a local model you run yourself — all on your own API keys.

Loaded only when it is needed
The system prompt carries just the name and description. The instructions are fetched on the first matching request, so an idle skill costs nothing.
Switch models mid-chat
Because the skill is instructions rather than code, changing model does not break it — the next model reads the same SKILL.md.

Skill instructions

This is the SKILL.md content the model loads. Read it before installing — a skill is instructions your model will follow.

Build a complete mental map of this project so you can work effectively without rediscovering things. Follow these phases:

Phase 1: Direct Reading (your own context)

Find and read key documentation files directly — do NOT delegate these, you need them in YOUR context:

Look for root-level markdown files: README, STATUS, CHANGELOG, CONTRIBUTING, ARCHITECTURE, ROADMAP, REFERENCE, WORKLOG, and any project-specific docs (CLAUDE.md, AGENTS.md, etc.)
Look for a CLAUDE.md or similar agent instruction file
Check for a .claude/ directory with project config or memory files
If the codebase is large - use a sub-agent with a layered-summary skill for the code sources folder to generate (or update, if exists) the AGENTS.md summaries

Phase 2: Sub-agent Exploration (parallel)

Based on what you learned in Phase 1, spawn sub-agents to explore the major areas of the codebase. Each agent should read all documentation files in its area, skim key source files, and return a structured summary of: what's there, how it works, key decisions, and where to look for what.

Typical areas to explore (adapt based on actual project structure):

Each major source directory — architecture, key modules, entry points, important types/interfaces
Tests & CI — test structure, CI config, how to run tests
Config & Infrastructure — deployment configs, environment setup, docker files, scripts
Documentation subdirectories — any docs/, wiki/, knowledge-base/, research/, or analysis/ folders
GitHub/GitLab history — previous commits list, closed PRs, closed Issues (using gh if available)
GitHub/GitLab current state — open issues, open PRs, recent commits and activity (gh issue list, gh pr list if available)

Adjust the number and focus of sub-agents based on project size. Small project = 2-3 agents. Large monorepo = 5-6 agents, iterative.

Phase 3: Fill Gaps

After receiving all sub-agent summaries, identify gaps in your understanding:

Are there key source files referenced in docs that you haven't seen?
Is the data flow / request lifecycle clear end-to-end?
Do you understand how to build, test, and run the project?
Is there anything that you're still missing and need to see?
Spawn additional sub-agents or read files yourself as needed
Check recent git log (git log --oneline -20) for context on latest changes

Phase 4: Synthesize

Provide a concise project briefing covering:

Project overview: What is this? What problem does it solve?
Current state: What phase/version? What works? What's in progress?
Architecture map: How the major pieces fit together, data flow, key abstractions
Open work: Issues, PRs, blockers, next steps
Key numbers: Any important metrics, benchmarks, or thresholds
Developer guide: How to build, test, run. Key commands.
Where to find things: Quick reference for common lookups (config, entry points, types, tests)

The goal: after this runs, you should have FULL project context and never need to ask "where is X?" or "what does Y do?" for the common cases.

Frequently asked questions

What does the Init Context AI skill do?

Why use Init Context on TypingMind?

Because you install it once and use it with any model. Init Context is plain Markdown rather than provider-specific code, so the same skill runs on GPT-5, Claude, Gemini, Grok, or a local model — and you can switch model mid-chat without it breaking. TypingMind runs on your own API keys, so you pay providers directly instead of a per-seat subscription, and your skills and chats stay in your own storage.

How do I install Init Context in TypingMind?

Open Plugins → Skills → Install from GitHub in TypingMind and paste https://github.com/vicnaum/vics-agent-skills/tree/main/skills/init-context. TypingMind reads its SKILL.md and installs it as a skill you can enable per chat.

Which AI models can use Init Context?

Any model you connect in TypingMind. AI skills are plain Markdown instructions rather than provider-specific code, so GPT, Claude, Gemini, Grok, and local models can all load this skill when a request matches it.

How many AI models can I use with Init Context?

As many as you like. As long as a model supports skills, you can use Init Context with it — GPT, Claude, Gemini, Grok, DeepSeek, Mistral, Llama and more — all on TypingMind with your own API keys.

Is the Init Context AI skill free?

It is published on GitHub by vicnaum. Check the repository for licensing terms. You only pay your own AI provider for the tokens you use.

What are AI skills?

An AI skill is a reusable instruction bundle that teaches an AI model how to do one specific task. It follows the open Agent Skills format: a SKILL.md file with a name and description, plus any scripts, templates or reference files the model may need. The model reads the instructions only when your request matches the skill, so an installed skill costs nothing until it is used.

How are AI skills different from plugins or MCP servers?

A plugin or MCP server gives a model new tools to call — code that runs somewhere and returns a result. An AI skill gives the model knowledge and process instead: how to approach a task, which steps to follow, what good output looks like. Skills are plain Markdown, so they need no server, no API key and no runtime, and they work with any model.

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Overview

Installation

Install in TypingMind

Install in another agent

Use it in TypingMind

Works with any AI model

Skill instructions

Phase 1: Direct Reading (your own context)

Phase 2: Sub-agent Exploration (parallel)

Phase 3: Fill Gaps

Phase 4: Synthesize

Frequently asked questions

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