commonplace

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SUMMARY

The theory of LLM wikis, running as one. A framework for agent-operated knowledge: typed, linked, review-gated markdown your agents execute.

README.md

Commonplace

The theory of LLM wikis, running as one.

Commonplace is a framework for agent-operated knowledge bases — LLM wikis in the sense Karpathy sketched: a persistent, linked markdown layer that AI agents write, navigate, review, and maintain. The framework ships a type system, writing conventions, agent skills, and Python commands for building such a wiki around your own work.

It is self-hosting, in the compiler sense. The theory of how to build LLM wikis lives in this repository as notes, and the methodology those notes lay out is executed here, not just described: LLM agents follow it to maintain the very wiki the theory lives in. The skills agents use to write, connect, and validate notes are themselves artifacts in the wiki, written and maintained the same way; the writing conventions govern the very files they are written in. Nothing here is documentation about a separate system. The wiki is the system, and reading this repo is watching it run.

The content is AI-generated through human-AI collaboration: a human directs the inquiry, and AI agents (Claude, ChatGPT, and others) draft, connect, and maintain the notes.

Rendered notes are available at https://zby.github.io/commonplace/. The HTML site is easier to browse than raw Markdown when reading across the KB.

What's in the box

kb/                          Knowledge base
  types/                     Global types (text, note, instruction, definition, index)
  notes/COLLECTION.md         Writing conventions (theoretical register)
  reference/COLLECTION.md     Writing conventions (descriptive register)
  instructions/COLLECTION.md  Writing conventions (prescriptive register)
  log.md                     Improvement log — one-line observations appended during traversal
  notes/                     Notes — the primary knowledge unit
    types/                   Note-local type templates (structured-claim)
    adr/                     Architecture Decision Records
    related-systems/         External system comparisons
  sources/                   Snapshotted external sources + analysis
  tasks/                     Work tracking (status encoded by directory)
  work/                      Workshop space — connect reports, ingest staging, explorations
  instructions/              Framework skills, local procedures, and operator guidance
    write/SKILL.md           Promoted framework skill source
    connect/SKILL.md         Promoted framework skill source
    ingest/SKILL.md          Promoted framework skill source
    evaluate-scenarios/SKILL.md  Measure scenario costs
    re-ingest.md             Instruction (not yet promoted to skill)
    review-gates/            Review gates grouped by bundle/lens name (e.g. semantic/)
    ...

test/
  scenarios/                 Scenario fixtures for cost decomposition and evaluation

src/commonplace/             Packaged operational engine
  cli/                       User-facing commands
  review/                    Review system commands + support modules
  lib/                       Shared runtime helpers
  docs/                      MkDocs hooks and documentation assets

Key ideas

Title as claim, not topic. Note titles are assertions that work as prose when linked: "approvals guard against LLM mistakes not active attacks" instead of "approvals system". Following links reads like a chain of reasoning.

Progressive refinement. Capture with zero friction — a file with no frontmatter is a valid text type with zero structural requirements. Add frontmatter to make it a note. Add Evidence/Reasoning/Caveats sections to make it a structured-claim. Structure is earned, not imposed.

Files, not database. Authored knowledge stays file-backed: universal interface, free versioning via git, zero infrastructure. Derived indexes solve scale problems without replacing the source of truth. The current scoped exception is the experimental review system, which stores review state in SQLite because that state behaves like local operational metadata rather than library content; see 010-review state should move to sqlite once reviews leave git and accumulate operational metadata.

The network IS the knowledge. Individual notes matter less than their relationships. Every link must articulate its relationship (extends, grounds, contradicts, exemplifies) — "related" is not a relationship. An unconnected note is invisible.

Externalized methodology. Knowledge accumulates in the KB, but the procedures for working with it — how to write, connect, validate — live in skills and docs, not in the agent's head. The agent reads them fresh every time. The KB is the memory; the skills are the manual.

Skills and instructions

Framework skills are sourced from kb/instructions/ and installed into consuming projects under kb/commonplace/instructions/cp-skill-*/ with a cp-skill- prefix. The prefix keeps them distinct from both a project's own skills and the commonplace-* CLI commands. commonplace-init creates .claude/skills/ and .agents/skills/ symlink projections for common runtimes, and other IDEs or agent runtimes should expose the same canonical skill directories through their own skill mechanism. Plain KB procedures remain under kb/instructions/ and load on demand. The project control-plane file (CLAUDE.md or AGENTS.md) still handles KB discovery and scoping.

Framework skills:

Skill Purpose
cp-skill-write Route and draft a note, index, or discovered specialized type
cp-skill-validate Check frontmatter, descriptions, types, links, structure
cp-skill-connect Discover connections and write a connect-report artifact
cp-skill-convert Convert raw text captures into structured notes
cp-skill-health-check Diagnose broken Commonplace installs, skill discovery, command PATH, and direnv state
cp-skill-ingest Ingest external source: snapshot → connect → classify → analyse
cp-skill-snapshot-web Capture a URL to kb/sources/
cp-skill-revise-iterative Iteratively revise a note without changing its claims
cp-skill-revise-autoreason Revise a note with AutoReason-style incumbent/revision/synthesis judging

Repo-local skills and procedures remain under kb/instructions/. Examples:

  • evaluate-scenarios — scenario-cost measurement for this repo's methodology work
  • Agent-memory-system reviews are handled by writing with the agent-memory-system-review type — workflow in kb/agent-memory-systems/types/agent-memory-system-review.md

Content workflow

Reading

Search the KB, read matching notes, follow links to deepen understanding. Link semantics (extends, grounds, contradicts) help the agent decide which connections are worth following. Good descriptions act as retrieval filters — they discriminate between similar notes so the agent reads fewer irrelevant ones.

Writing

  1. Search first — find related notes before writing
  2. Read the target collection's COLLECTION.md — each collection has its own writing conventions, quality goals, and default templates. For notes, read kb/notes/COLLECTION.md.
  3. Read the directory type — only if you're writing a specialized type (adr, index, related-system, or scenario in test/scenarios/). Skip this step for plain notes.
  4. Write the note
  5. Connect — link the new note from related notes and indexes. Use the cp-skill-connect skill or do it manually. Don't skip this — an unconnected note is invisible to future search.

Usage

Direct use (this repo)

Clone the repo and start working. The repo is a functioning knowledge base out of the box — skills, types, writing conventions, and methodology are all in place.

git clone https://github.com/zby/commonplace.git
cd commonplace

If you use direnv, make sure your shell has the direnv hook installed, then run direnv allow once after entering the repo. The .envrc sets PATH and UV_CACHE_DIR for the project. Start Codex or Claude Code from that direnv-loaded interactive shell so the runtime inherits the project venv; otherwise launch it with direnv exec . <command>.

Skills are installed under kb/instructions/cp-skill-*/ in this repo and exposed to local agent runtimes through .claude/skills/cp-skill-*/ and .agents/skills/cp-skill-*/ symlinks. Other runtimes should expose the same canonical skill directories in their own way. The root AGENTS.md provides the project routing layer. The kb/ directory is both the methodology and your workspace — new notes go alongside the existing ones.

This is the right mode when:

  • You want to explore or contribute to the Commonplace methodology itself
  • You want a standalone knowledge base without attaching it to another project
  • You're evaluating the system before installing it elsewhere

Installing into a project

Commonplace can be installed into any project as a Python package. See INSTALL.md for the setup flow.

Prerequisites

Tool Required Purpose
Agent runtime yes Codex, Claude Code, or another internal LLM/IDE that can load project instructions and expose the cp-skill-* skill directories
uv yes Install and run the Commonplace Python package
git yes Versioning, history-preserving renames in convert
ripgrep (rg) yes Structured search — frontmatter queries, keyword matching, link scanning
curl yes PDF downloads in snapshot-web
gh no GitHub issue/PR snapshots in snapshot-web and commonplace-github-snapshot

Commands

Install the package first, then use the commands directly:

commonplace-validate kb/notes
commonplace-relocate-note old-note "New note title" --apply
commonplace-relocate-note old-note --to kb/notes/definitions --apply
commonplace-github-snapshot <url>
commonplace-x-snapshot <url>

License

Commonplace is dual-licensed:

  • Code in src/ and package tooling: MIT
  • Knowledge-base content, documentation, templates, and bundled instructional artifacts: CC BY 4.0

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