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Context Loader

Community
Ibrahim-3d
context-loader

Load project context efficiently for Conductor workflows. Use when starting work on a track, implementing features, or needing project context without consuming excessive tokens.

Overview

PublisherIbrahim-3d
Repositoryorchestrator-supaconductor
Skill namecontext-loader
Stars
378
Forks
38
Bundled files
Instructions only
LicenseAGPL-3.0
Links
  • 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 Ibrahim-3d on GitHub. Read the source before you install it.

Installation

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

1

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.

  1. Open the app and go to Plugins → Skills.
  2. Choose "Install from GitHub".
  3. Paste the skill folder URL below and confirm.
  4. 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.
2

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/Ibrahim-3d/orchestrator-supaconductor.git /tmp/orchestrator-supaconductor
mkdir -p .claude/skills
cp -r /tmp/orchestrator-supaconductor/skills/context-loader .claude/skills/context-loader
Restart Claude Code after copying so it picks up the new skill.

Use it in TypingMind

Enable Context Loader 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 Context Loader 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 Context Loader 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.

Context Loader Skill

Efficiently load and manage project context for Conductor's context-driven development workflow.

Trigger Conditions

Use this skill when:

  • Starting work on a new track or feature
  • User mentions: "load context", "project context", "get context"
  • Beginning /orchestrator-supaconductor:implement workflow
  • Need to understand project structure without reading all files

Token Optimization Protocol

1. Respect Ignore Files

Before scanning files, check for:

  1. .claudeignore - Claude-specific ignores
  2. .gitignore - Standard git ignores
bash
# Check for ignore files
ls -la .claudeignore .gitignore 2>/dev/null

2. Efficient File Discovery

Use git for tracked files:

bash
git ls-files --exclude-standard -co | head -100

For directory structure:

bash
git ls-files --exclude-standard -co | xargs -n 1 dirname | sort -u

3. Priority Files (read_file First)

PriorityFile TypeExamples
1Manifestspackage.json, Cargo.toml, pyproject.toml
2Conductorconductor/product.md, conductor/tech-stack.md
3Trackconductor/tracks/<id>/spec.md, plan.md
4Configtsconfig.json, .env.example

4. Large File Handling

For files over 1MB:

  • read_file first 20 lines (header/imports)
  • read_file last 20 lines (exports/summary)
  • Skip middle content

Enforcement Rules (MANDATORY)

  1. Check file size via run_shell_command ls -la before reading
    • 500KB: read_file first 20 + last 20 lines only

    • 1MB: Skip entirely, log as "skipped: too large"

  2. Stop after Tier 1-3 files. Tier 4 (config files) only if task-specific.
  3. Never load completed tracks — only active track spec.md + plan.md.
  4. Maximum 15 files per context load. If more are needed, prioritize by tier.

Context Loading Workflow

1. Load CLAUDE.md (if exists)
2. Load conductor/product.md (project vision)
3. Load conductor/tech-stack.md (technical context)
4. Load conductor/tracks.md (completed work — prevents duplicate effort)
5. Load current track spec.md (requirements)
6. Load current track plan.md (tasks — check [x] vs [ ] status)

Evaluate-Loop Integration

This skill is used by multiple loop agents:

  • loop-planner — loads context before creating a plan
  • loop-executor — loads context before implementing tasks
  • conductor-orchestrator — loads context to determine current loop step

Critical: Always load tracks.md and check plan.md task markers to prevent duplicate work across sessions.

Response Format

After loading context, summarize:

## Project Context Loaded

**Product**: [one-line summary]
**Tech Stack**: [key technologies]
**Current Track**: [track name/id]
**Active Phase**: [current phase]
**Pending Tasks**: [count of [ ] tasks]
**Completed Tasks**: [count of [x] tasks]
**Loop Step**: [current Evaluate-Loop step — Plan/Execute/Evaluate/Fix]

Frequently asked questions

What does the Context Loader AI skill do?

Load project context efficiently for Conductor workflows. Use when starting work on a track, implementing features, or needing project context without consuming excessive tokens.

Why use Context Loader on TypingMind?

Because you install it once and use it with any model. Context Loader 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 Context Loader in TypingMind?

Open Plugins → Skills → Install from GitHub in TypingMind and paste https://github.com/Ibrahim-3d/orchestrator-supaconductor/tree/master/skills/context-loader. TypingMind reads its SKILL.md and installs it as a skill you can enable per chat.

Which AI models can use Context Loader?

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 Context Loader?

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

Is the Context Loader AI skill free?

Yes. It is published on GitHub by Ibrahim-3d under the AGPL-3.0 license. 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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