KanishkNoir

Cognikernel — Development skill for Claude Code

Development community

Persistent, structured project memory for Claude Code and Codex - event-sourced, typed, fail-open.

How to install Cognikernel

This entry records only its repository, not the path inside it, so there is no exact command to give. Open KanishkNoir/cognikernel and copy the folder into ~/.claude/skills/, or the file into ~/.claude/agents/.

What Cognikernel does

Persistent, structured project memory for Claude Code and Codex - event-sourced, typed, fail-open. Your agent stops re-deciding what you already decided.

Alternatives in Development

Claude Supermemory — Persistent memory across sessions and projects using Supermemory 2.3k ★
/remember — Save a finding or successful pattern to persistent hunt memory 1.2k ★
Projectmem — Open-source coding agent memory 766 ★

README

CogniKernel

[![PyPI](https://img.shields.io/pypi/v/cognikernel.svg)](https://pypi.org/project/cognikernel/) [![PyPI Downloads](https://static.pepy.tech/personalized-badge/cognikernel?period=total&units=NONE&left_color=BLACK&right_color=GREEN&left_text=downloads)](https://pepy.tech/projects/cognikernel) [![Python](https://img.shields.io/pypi/pyversions/cognikernel.svg)](https://pypi.org/project/cognikernel/) [![License](https://img.shields.io/github/license/KanishkNoir/cognikernel.svg)](LICENSE) [![Last commit](https://img.shields.io/github/last-commit/KanishkNoir/cognikernel.svg)](https://github.com/KanishkNoir/cognikernel/commits/main) [![Stars](https://img.shields.io/github/stars/KanishkNoir/cognikernel.svg?style=flat)](https://github.com/KanishkNoir/cognikernel/stargazers)

**Your AI coding agent has amnesia by design.** Every session starts from zero — it re-reads the same files, re-derives the same architecture, and re-asks questions you already answered last week. CogniKernel gives the *project* a memory that outlives any one session, so the agent stops paying the same cost twice:

  WITHOUT MEMORY                          WITH COGNIKERNEL
  ───────────────                          ─────────────────
  Session 1                                Session 1
    "explain the auth flow"                  "explain the auth flow"
    -> reads 12 files, learns it             -> reads 12 files, learns it
    -> session ends, all of it lost          -> session ends
                                              -> decisions captured & stored

  Session 2                                Session 2
    "explain the auth flow"                  already knows: the auth flow,
    -> reads 12 files again                  why Redis beat an in-process
    -> re-derives the same thing             cache, and the approach that
    -> session ends, nothing kept            was tried and abandoned
                                              -> picks up where it left off

  Session 3