Hypergraph

A substrate for autonomous research and engineering.

The goal is agents that carry out real research and real engineering over months without a human holding the thread — and the obstacle is not agent capability. It is that agents are made to work in a substrate that does not support the shape of the job. Chat logs are not memory. A codebase records what was kept, never what was tried and rejected. A task list rots the moment reality moves. So every fresh context re-derives what the last one already knew, repeats dead ends nobody wrote down, and quietly contradicts decisions it never saw. That failure is structural, not a prompting problem, and no amount of context window fixes it.

Hypergraph is an attempt at a substrate where those failures are not available. Knowledge has somewhere to go, being wrong is a first-class outcome, and the thing an arriving agent reads first is what is true now rather than everything that ever happened. Its unit of work is not a commit or a ticket — it is a claim with its evidence attached.

It maintains two graphs per project, kept as markdown files committed in your repo:

• Record graph — the append-only log of everything that happened: decisions, experiments, evidence, dead ends. Optimized for audit, not orientation.
• State graph — a small, single-writer, distilled projection of what is true now: architecture, what works, what's broken or open (the frontier), and accumulated negative knowledge.

Concretely: on a mature project, cold-start orientation over an append-only DAG means traversing thousands of nodes. With Hypergraph, a fresh agent reads the frontier in a handful of tool calls (≤ ~6 in our own use — whether that beats plain git on real work is an open benchmark question) and follows provenance slugs into the record graph only where the task demands history.

How it stays coherent with many parallel agents: knowledge lands record-first — every record node declares its ## State Impact (or none: <reason>), and a separate single-writer reconcile pass folds declared impacts into the state graph behind an append-only high-water mark. Nobody edits state inline. Forward work follows the same rule: new directions (including Operator directives) enter as decision record nodes whose impacts open Status: open state nodes — the frontier carries intent as claims about gaps, never as task lists.

Why "hypergraph"

Because of what connects the two graphs, and that connection is the actual bet.

Every state node cites the record nodes it derives from. One claim about the world is answerable to many pieces of evidence at once, and one piece of evidence bears on many claims — so the citation structure is not a tree or a second DAG. Its edges join sets of nodes to sets of nodes, across two graphs. That is a hypergraph, and it is what makes a claim auditable: you can always ask "what is this believed on the strength of", and get back a set you can read.

The two halves are at very different stages, and it is worth being honest about which is which:

• The record graph is established practice. An append-only, causally-parented log of what was done and why is a lab notebook, an ADR log, an experiment tracker. We are implementing a known good idea carefully, not inventing one.
• The state graph — and the hypergraph that falls out of it — is the novel part, and it is under active development. A single-writer distillation that stays small while its evidence base grows without bound; negative knowledge as a first-class citizen with scope and confidence; a frontier that is falsified by work rather than checked off. Whether that projection stays honest at scale, and whether agents actually orient better against it than against raw history, is the open research question this project exists to answer. It is being tested on live projects — this repo runs on itself, and the protocol has been adopted by others — and it is not finished.

If you are evaluating this, treat the record half as engineering and the state half as a hypothesis with encouraging early results.

Where the graphs live

In your repo. Each node is a committed markdown file under .hypergraph/graph/<record|state>/<slug>.md — frontmatter carrying identity and parent slugs, body carrying the content verbatim (local-adapter.md). Nothing to sign in to, nothing to install a server for: the graphs travel with the repo, work offline, merge through git, and check in CI.

There is no backend to choose. The protocol is still written against a thin abstract interface — ~10 operations — but that is a portability property, not a setting: it is what a replacement store would have to satisfy, and why nothing in the spec above the Storage section mentions files.

Optionally, hypergraph push mirrors your committed node files to a hosted Flywheel graph you own, so agents that aren't sitting in your working tree can read them. The mirror is a one-way, regenerable projection — your files stay canonical — and it is entirely a property of the CLI: the skills don't know it exists, and a project without it never touches that path (mirror.md).

Working in parallel

Several agents, a fork and a pull request, a colleague on another machine — the two graphs already split along the line git merges on, so the rule falls out of the invariants rather than adding machinery (SPEC: Collaboration):

Contributors record; the maintainer reconciles.

The record graph is append-only with one file per node, so concurrent branches produce new files and merge without conflict — and each record node arrives in the pull request as a file, so the claim is reviewed beside the code that justifies it. The state graph has a single writer (I3), so reconcile runs once on the default branch over everything that merged. Publishing follows the same line: the mirror is a build artifact of the default branch, so hypergraph push stands down at exit 0 on a feature branch or on a clone whose credentials don't own the mirror. Nobody needs a credential to contribute.

Two workflows in templates/github-actions/ make it enforceable: hypergraph check --since origin/<base> fails a pull request that changes files without recording anything, and a publish job refreshes the mirror on merge.

Dispatch

Parallel work can also be aimed: the hypergraph-dispatch skill points an agent at a target — a frontier node, a stated goal, or a region of the state graph — with a bounded budget of work units. The dispatch begins as a decision record node (Dispatch: <target>), which doubles as an advisory lane claim other dispatches read to avoid double work; the work arrives as its children; a closure line ends the lineage. Nothing new to reconcile against — a dispatched agent is a contributor, so the workflow above already covers it (SPEC: Dispatch and lanes).

The lane itself — an isolated worktree on a lane/<slug> branch — is managed by hypergraph dispatch open|ls|harvest|close, the local implementation of a small provider seam (backend/lanes.md): provision, inject, run, harvest, teardown. Harvest is a git merge; teardown refuses while unharvested. With no agent command configured, dispatch open provisions the lane and prints the manual steps, exit 0 — the same stand-down posture as push with no mirror.

What ships

• SPEC.md — the protocol: invariants I1–I8 + conventions.
• skills/ — the Claude skills: hypergraph-init, hypergraph-adopt (bring a project with a past under the protocol: legacy-graph import or authored prehistory, adoption epoch, AGENTS.md onboarding), hypergraph-record, hypergraph-reconcile, hypergraph-orient, hypergraph-dispatch.
• tools/hypergraph.py — uv script, and the offline core of a two-file CLI: check validates the mechanical invariants over JSON graph exports (CI-ready, nonzero exit on violations); render generates STATE.md (frontier first, architecture tree below); export/import/new/ update are the storage layer, hwm reports the reconciliation frontier, dispatch manages local lanes, and upgrade refreshes an adopted repo's copies of the skills and the AGENTS.md block (--graph runs the retroactive graph repairs, detect-only until --apply). The optional mirror's networked half (push's executing tail, sync's publish, mirror) lives in tools/hypergraph_mirror.py, loaded lazily — offline commands never import it.
• templates/ — the exact markdown shapes the checker parses.

Install

uv tool install hypergraph-protocol
hypergraph skills install          # → ./.claude/skills (project scope)

That is the whole install: the CLI from PyPI, and the skills into the repo you are working in (--user puts them in ~/.claude/skills instead). Nothing to clone, nothing to fork.

Updating later takes two commands, because it is two different things:

uv tool upgrade hypergraph-protocol   # the CLI — lives outside your repo
hypergraph upgrade                    # the copies — skills, AGENTS.md block, workflows

(hypergraph upgrade --graph is the third, rarer thing: retroactive graph repairs for a repo that adopted before a capability existed — detect-only until --apply, because those rewrite node files.)

skills install writes real files into your repo, so uv tool upgrade cannot see them and they go stale silently. hypergraph upgrade refreshes what is already there — it never installs what is not, so it will not drop CI into a repo that never had it, and drifted workflows are reported rather than overwritten (--workflows opts in). Your AGENTS.md block gets the same protection: adoption writes project-specific content inside those sentinels, so a block you have edited is reported and left alone, with the shipped version named for you to merge against (--agents-block opts in). It also stamps hypergraph_version: into the config, which is what lets check tell you which half is behind. Node files themselves need no migration: they are additive markdown, and an older CLI reads a newer graph.

Quickstart

Two routes in, depending on whether the project has a past. Both are Claude skills — run them in a session inside your project repo.

New project → hypergraph-init: creates both roots, a state skeleton mirroring your architecture, .hypergraph/config.yml, and STATE.md.

#   run hypergraph-init            → roots + state skeleton + config + STATE.md
#   ... do work; run hypergraph-record after each unit of work
#   run hypergraph-reconcile       → fold impacts into state, regenerate STATE.md
#   (fresh session) hypergraph-orient → frontier brief in a handful of tool calls

Existing project → hypergraph-adopt: a repo with real history, an existing hosted graph, or both. It surveys the repo (git shape, timeline signals, docs, churn), interviews you for what only you know, then either imports the legacy graph verbatim (hypergraph import --fork preserves node_ids and slugs, so provenance and the high-water mark stay valid) or authors honest prehistory from the repo itself. It draws an adoption epoch so legacy nodes are exempt from template compliance, distills a state graph from what the project actually knows, and installs the AGENTS.md onboarding. The import is a fork: the source graph stays frozen as the archive, and the repo becomes the continuing graph, owning its whole history with the original topology. The archive's artifacts do not travel — what travels is a repo-relative path, and those bytes live on someone else's store — so they stay on the archive and the adopted project says so. Evidence recorded from then on is an ordinary repo file and travels with the repo. After either route, the loop is the same.

The whole loop, in the repo — no account, no network:

hypergraph new record --title "Fixed the streaming parser" --body body.md \
    --parent <causal-slug> --impact "<state-slug> — status broken → working" --repo-auto
hypergraph export --config .hypergraph/config.yml     # node files → cache JSON
hypergraph check --record .hypergraph/cache/record.json \
    --state .hypergraph/cache/state.json --config .hypergraph/config.yml
git add .hypergraph/graph                             # the memory travels with the repo

Checker and renderer, standalone:

hypergraph check  --record .hypergraph/cache/record.json --state .hypergraph/cache/state.json
hypergraph render --state .hypergraph/cache/state.json --config .hypergraph/config.yml -o STATE.md

Visualization

Visualization lives outside this package. The contract is the JSON exports: export writes .hypergraph/cache/{record,state}.json, and any renderer that reads those files can draw the graphs — no import across the package boundary, no coupling to this tool's internals.

The maintained renderer is hypergraph-viz, a thin translator built on excaligraph (MIT): it reads the two exports and emits an editable Excalidraw scene, every node carrying a link: back to its markdown source.

Repo map

SPEC.md                     the protocol (invariants + conventions + versioning policy)
CHANGELOG.md                releases, and the labels that never shipped
docs/cli.md                 the CLI reference — 16 subcommands, the exit-code table
docs/example.md             a worked walkthrough over the CI-pinned fixture graph
backend/INTERFACE.md        ~10 abstract operations — the portability contract
backend/local-adapter.md    op → node files + hypergraph CLI (git-native; the one impl)
docs/internal/              mirror internals (mirror.md, flywheel.md) — not agent-facing
backend/lanes.md            the lane-provider seam for dispatch (local ships; box is future)
skills/hypergraph-*/        the skills (.claude/skills/ symlinks these)
templates/                  record-node / state-node / config shapes
templates/github-actions/   PR check + publish-on-merge workflows
tools/hypergraph.py         the offline core: checker + renderer + storage + dispatch (uv script)
tools/hypergraph_mirror.py  the mirror's networked half, lazily loaded by the core
tools/fixtures/             test fixtures (clean, violations, local-graph, epoch)
tests/                      pytest suites (checker, storage, mirror, split, dispatch, collaboration, adoption, upgrade)

This repo dogfoods itself: see .hypergraph/config.yml and STATE.md.

Developing the protocol itself

Only if you are working on this repo — adopters never clone it. In a dev checkout the CLI is uv run tools/hypergraph.py … ([tool.uv] package = false, so the bare hypergraph does not resolve here), and ./install.sh symlinks skills/ into ~/.claude/skills so an edit to a skill is live in the next session.

./install.sh                       # symlink the skills into ~/.claude/skills
uv run pytest tests/               # checker + storage + mirror suites
uv run tools/hypergraph.py sync --config .hypergraph/config.yml