aakashH242

ctxsift-install

CtxShift is a skill that helps you focus on your tasks by reducing context clutter and enabling faster state recollections. \

aakashH242 0 Updated 1w ago

Resources

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GitHub

Install

npx skillscat add aakashh242/ctxsift

Install via the SkillsCat registry.

SKILL.md

Important Links:

  1. Home page - https://ctxsift.dev
  2. GitHub repo - https://github.com/aakashh242/ctxsift
  3. Latest benchmark - https://ctxsift.dev/benchmark-viewer.html

CtxSift Installation Process

You must perform the installation using the following steps -

  1. Ensure pre-requisites are present. Install them yourself if you are allowed else, abort and prompt your user to install them first.
  2. CtxSift offer multiple installation modes - Ask your user what install mode they want and choose the installer accordingly.
  3. Check system requirements and compare with requirement matrix below. Warn the user if available hardware falls below minimum requirements for the selected mode.
  4. Run ctxsift doctor yourself to verify installation was successful.
  5. Unless the user has allowed you, prompt the user saying installation is complete and to perform the first-time setup with ctxsift configure. You can also point the user to https://ctxsift.dev/docs/getting-started/configure/ to learn more on how to configure.

Prerequisites

Requirements Matrix

CtxSift uses a language model to compress tool outputs. This can be a model running locally or hosted remotely. See the requirements below for each scenario.

Compression Mode Minimum RAM Minimum VRAM Comments
Local, no GPU 8 GB N/A Both embedding and compression models are loaded into RAM
Local, with GPU 2 GB 8 GB Both embedding and compression models get loaded into VRAM
Remote, no GPU 4 GB N/A Only the embedding model gets loaded into RAM
Remote, with GPU 2 GB 4 GB Only the embedding model gets loaded into VRAM

Install Commands

# Install the base package - inference runs on CPU
uv tool install ctxsift

# Install with GPU add-ons - inference with GPU acceleration
uv tool install "ctxsift[gpu]"

# Enable quantization support on GPU
uv tool install "ctxsift[gpu,quant]"

# Install with LiteLLM included - use remotely hosted models for inference
uv tool install "ctxsift[remote]"

# Install the full package
uv tool install "ctxsift[all]"

If ctxsift is not found after installation, run:

uv tool update-shell

Then restart your shell and try ctxsift again.

First-time setup

Unless you are allowed explicitly, ask your user to run the below command to perform the first-time setup.
You can always recommend which model to use, based on the user's selected mode, by browsing the latest benchmark data from the link given above.

ctxsift configure

Verify and test your setup

# Verify
ctxsift doctor

# Test compression
echo "alpha\nbeta\ngamma" | ctxsift compress --intent exact-lines "Return only the first line, no explanations."

Troubleshooting

If you are having issues, read the docs at https://ctxsift.dev/docs