omnigraph/AGENTS.md

OmniGraph — Agent Guide

This file is the always-on map for AI coding agents (Claude Code, Codex, Cursor, Cline) working in this repo. It is loaded into context on every turn, so it stays as a map plus the rules and invariants that need to be in scope at all times — the encyclopedia content lives under docs/. When you need depth, follow a pointer.

Required reading every session, every change:

1. docs/dev/invariants.md — the architectural invariants and deny-list. Apply to every PR, not only architecture work.
2. docs/dev/lance.md — the curated index of upstream Lance docs. Consult it before every task to identify which Lance pages are relevant. Then fetch every page in the matching domain section, plus every page that is even slightly relevant — not just the page whose title most obviously matches the task. Behavior is interlocked across pages (transactions reference index lifecycle; index lifecycle references compaction; compaction references row-id lineage), and skipping a "slightly relevant" page is how alignment misses happen. The index itself is not a substitute for reading the pages — never act on the index alone. Always fetch the FULL page content, not summaries — use curl -sL <url> | pandoc -f html -t markdown or paste the rendered page text manually. Tools that summarize pages (like Claude's WebFetch) drop load-bearing details — we have caught alignment misses (default flags, pub(crate) blockers, three-page sub-specs hidden behind navigation hubs) only after dumping the full markdown.
3. docs/dev/testing.md — the test-coverage map. Always check what already covers your change before writing a new test. Extending an existing test (an assertion, a fixture row, a parameterization) is preferred over a duplicated init_and_load() block. Walk the before-every-task checklist to identify existing coverage, run those tests as a clean baseline, and only add a new test fn or file when no existing one owns the area.

Tools that support @-imports (Claude Code) auto-include all three files via the imports below — note these must sit at column 0 (not inside a blockquote) for the parser to recognize them. Other agents (Codex, Cursor, Cline, …) must open them explicitly at the start of each session.

@docs/dev/invariants.md @docs/dev/lance.md @docs/dev/testing.md

CLAUDE.md is a symlink to this file — there is exactly one source of truth. Edit AGENTS.md.

Version surveyed: 0.4.2 Workspace crates: omnigraph-compiler, omnigraph (engine), omnigraph-cli, omnigraph-server Storage substrate: Lance 4.x (columnar, versioned, branchable) License: MIT Toolchain: Rust stable, edition 2024

---

Start here — what is this?

OmniGraph is a typed property-graph engine built as a coordination layer over many Lance datasets. Highlights:

• Storage: per node/edge type a separate Lance dataset; multi-dataset commits coordinated atomically through one __manifest table.
• Languages: a .pg schema language and a .gq query language, both Pest-based, with a typed IR.
• Multi-modal querying: vector ANN (nearest), full-text (search/fuzzy/match_text/bm25), Reciprocal Rank Fusion (rrf), and graph traversal (Expand, anti-join not { … }) in one runtime.
• Branches and commits across the whole graph: Git-style — every successful publish appends to a commit DAG; merges are three-way at the row level.
• Atomic per-query writes: mutate_as and load accumulate insert/update batches into an in-memory MutationStaging.pending per touched table; one stage_* + commit_staged per table runs at end-of-query, then ManifestBatchPublisher::publish commits the manifest atomically with per-table expected_table_versions CAS. A mid-query failure leaves Lance HEAD untouched on staged tables — no drift, no run state machine, no staging branches. Deletes still inline-commit; D₂ at parse time prevents inserts/updates and deletes from coexisting in one query.
• HTTP server: Axum + utoipa OpenAPI, bearer auth (SHA-256 hashed, optional AWS Secrets Manager). Cedar policy enforcement is engine-wide — every _as writer calls Omnigraph::enforce(action, scope, actor), so HTTP, CLI, and embedded SDK consumers all hit the same gate.
• CLI driven by a single omnigraph.yaml; multi-format output (json/jsonl/csv/kv/table).

Throughout the docs, capabilities are split into L1 — Inherited from Lance vs L2 — Added by OmniGraph.

---

Architecture at a glance

CLI (omnigraph)        HTTP Server (omnigraph-server, Axum)
        │                            │
        └─────────────┬──────────────┘
                      ▼
           omnigraph-compiler  ── Pest grammars, catalog, IR, lowering, lint, migration plan
                      │
                      ▼
           omnigraph (engine)  ── ManifestRepo, CommitGraph, RunRegistry, GraphIndex (CSR/CSC), exec
                      │
                      ▼
              Lance 4.x         ── columnar Arrow, fragments, per-dataset versions/branches, indexes
                      │
                      ▼
        Object store (file / s3 / RustFS / MinIO / S3-compat)

Full diagram and concurrency model: docs/dev/architecture.md.

---

Where to find each topic

Area	Read
User docs entry point (public CLI/API/operator docs)	docs/user/index.md
Developer docs entry point (architecture, invariants, testing, internals)	docs/dev/index.md
Architectural invariants & deny-list (read before any non-trivial proposal or review)	docs/dev/invariants.md
Lance docs index — fetch upstream Lance docs by problem domain	docs/dev/lance.md
Test coverage map — what's covered, what helpers to reuse, before-every-task checklist	docs/dev/testing.md
Architecture, L1/L2 framing, concurrency model	docs/dev/architecture.md
Storage layout, __manifest schema, URI schemes, S3 env vars	docs/user/storage.md
.pg schema language, types, constraints, annotations, migration planning	docs/user/schema-language.md
Schema-lint codes (OG-XXX-NNN), families, severity, suppression	docs/user/schema-lint.md
.gq query language, MATCH/RETURN/ORDER, search funcs, mutations, IR ops, lint codes	docs/user/query-language.md
Indexes (BTREE / inverted / vector / graph topology)	docs/user/indexes.md
Embeddings (compiler + engine clients, env vars, @embed)	docs/user/embeddings.md
Branches, commit graph, snapshots, system branches	docs/user/branches-commits.md
Transactions and atomicity (per-query atomic; branches as multi-query transactions)	docs/user/transactions.md
Direct-publish writes (the former Run state machine, now demoted to publisher CAS)	docs/dev/runs.md
Three-way merge and conflict kinds	docs/dev/merge.md
Diff / change feed (diff_between, diff_commits)	docs/user/changes.md
Query execution, mutation execution, bulk loader, load vs ingest	docs/dev/execution.md
optimize (compaction) and cleanup (version GC)	docs/user/maintenance.md
Cedar policy actions, scopes, CLI	docs/user/policy.md
HTTP server endpoints, auth, error model, body limits	docs/user/server.md
CLI quick-start	docs/user/cli.md
CLI command surface and omnigraph.yaml schema	docs/user/cli-reference.md
Audit / actor tracking	docs/user/audit.md
Error taxonomy and result serialization	docs/user/errors.md
Install (binary / Homebrew / source / channels)	docs/user/install.md
Deployment (binary / container / RustFS bootstrap / auth / build variants)	docs/user/deployment.md
CI / release workflows	docs/dev/ci.md
Code ownership (CODEOWNERS source of truth, roles, regeneration)	docs/dev/codeowners.md
Branch protection policy (declarative, applied via scripts/apply-branch-protection.sh)	docs/dev/branch-protection.md
Constants & tunables cheat sheet	docs/user/constants.md
Per-version release notes	docs/releases/

---

First principle: engineering is programming integrated over time

Software engineering is programming integrated over time (Winters, Software Engineering at Google). A line of code costs you at every future read, refactor, migration, and dependent change — not just at write-time. So the operative question for any change is: which option has the lower ongoing liability? Not "shorter now," not "fastest to ship," but which leaves the codebase narrower in the long run. Complexity should be earned — by demonstrated correctness, performance, or future-shape cost; never by speculation.

This is a decision lens, not a code-size rule. It cuts both ways. Sometimes the lower-liability option is:

• More code. A centralized dispatcher costs more lines than an ad-hoc heal hook, but each future change adds a match arm instead of a new hook scattered through the engine.
• Less code. Three similar lines that may diverge later cost less to maintain than a premature abstraction that has to be retrofitted every time a caller deviates.
• DRYing. Two copies of business logic that must stay in sync are a perpetual drift risk.
• Duplication. Two callers that look similar today but have independent evolution pressure shouldn't be wedged through a shared helper just because the lines match.
• Removal. A "just in case" code path with no caller is pure surface area: tests for it, docs that mention it, future changes that have to consider it.
• Addition. A migration framework, a typed error variant, a feature flag — each adds code now and lowers the cost of every future change in its surface.
• A new abstraction, when the absence forces every consumer to re-derive the same logic. Or flattening one, when the abstraction has accumulated more special-cases than the code it replaced.

When evaluating a design, ask: "what does this look like after 5 more changes like it?" If the answer is "this converges to one shape", cost is bounded. If it's "this forks every time", the option is mortgaging the future for present convenience — pick differently.

Tiebreakers when liability alone is silent

• Correctness > simplicity > performance. Lexicographic — give up performance for simpler code; give up simplicity for correct code; never give up correctness. The deny-list ("no silent failures," "no acks before durable persistence," "no reads of partial commits") is this rule's hard floor.
• Reversibility shapes evidence demand. Reversible changes wait for evidence: prefer prod metrics over napkin math over RFCs. Irreversible changes (substrate choice, on-disk format, database guarantees) earn an RFC, because by the time prod tells you they were wrong, you've shipped years of dependent code. Reviewers should spot both failure modes — RFC-ing a one-line config, and measuring-your-way into a substrate decision.

The always-on rules below and the deny-list in docs/dev/invariants.md are specific applications of this principle; when the rules are silent, fall back to it.

---

Always-on rules (load these into your working memory)

These are architectural rules that need to be in scope on every change. They're framed at the level that survives renames and refactors — the deeper implementation specifics (function names, lock names, branch-prefix conventions, enforcement points) live in the per-area docs and may evolve. The full architectural invariants and deny-list are in docs/dev/invariants.md; the deny-list is the fastest first-pass when reviewing any change.

1. Multi-dataset publish is atomic across the whole graph. A graph commit flips every relevant sub-table version visible together, in one manifest write. Don't introduce code paths that publish per sub-table outside the unified publish path — that loses cross-table snapshot isolation.
2. Snapshot isolation per query. A query holds one snapshot for its lifetime. Don't re-read the current head mid-query.
3. Mutations are atomic at the commit boundary. Multi-statement change queries publish one commit. Don't commit per-statement.
4. Bearer-token plaintext never persists in process memory. Tokens are hashed at startup; auth uses constant-time comparison; the actor id is server-resolved from the hash match and must not be settable by the client.
5. Reads always see the current index state for the branch they're reading. Indexes track the branch head, not historical snapshots. If you change index lifecycle, preserve this guarantee.
6. Stable type IDs survive renames. Schema migration relies on identity that's stable across rename — don't mint new IDs on rename.

Deny-list (fast-pass review filter — full reasoning in docs/dev/invariants.md)

If a proposal fits one of these, the burden is on the proposer to justify why this case is the exception:

• Synchronous-inline index updates for indexes expensive to build (vector ANN, FTS) — use the reconciler pattern.
• Custom WAL / transaction manager / buffer pool — Lance owns these.
• Job queue for state derivable from manifest — reconciler pattern instead.
• Per-feature lowering for shapes that share a structure (interfaces, wildcards, alternation) — use one mechanism.
• Eager materialization of cross-products in multi-hop — factorize; flatten only when needed.
• Ad-hoc IN-list filtering when SIP fits.
• String-flattened SQL filter generation when structured pushdown is available.
• In-process-only Dataset impls — Send + Sync, remote descriptors.
• Cost-blind plan choice — lowering-order execution is not a planner.
• Hidden statistics — if a metric matters for plan choice, it must be exposed through the trait surface.
• Side-channels for query semantics — search modes, mutations, polymorphism are first-class IR concepts.
• Discarding rank in retrieval — score and rank propagate as columns.
• State that drifts from the manifest — derive from observable state.
• Cloud-only correctness fixes — correctness is always OSS.
• Forking the codebase for Cloud — trait-extension only.
• Hand-rolling something Lance already does — check the spec first.
• Mutating in place state that should be immutable (Lance fragments, index segments) — new segments instead.
• Silent failures — OOM, timeout, partial result must all be surfaced and bounded.
• Shipping observable behavior as if it weren't part of the contract — output ordering, error-message text, timestamp precision, default-flag values, latency profile. Per Hyrum's Law, every observable behavior gets depended on once shipped; don't expose what you don't want to commit to.

---

Quick-reference flows

# Initialize an S3-backed repo
omnigraph init --schema ./schema.pg s3://my-bucket/repo.omni

# Bulk load
omnigraph load --data ./seed.jsonl --mode overwrite s3://my-bucket/repo.omni

# Branch + ingest a review batch
omnigraph branch create --from main review/2026-04-25 s3://my-bucket/repo.omni
omnigraph ingest --branch review/2026-04-25 --data ./batch.jsonl s3://my-bucket/repo.omni

# Run a hybrid (vector + BM25) query
omnigraph read --query ./queries.gq --name find_similar \
  --params '{"q":"trends in AI safety"}' --format table s3://my-bucket/repo.omni

# Plan + apply schema migration
omnigraph schema plan  --schema ./next.pg s3://my-bucket/repo.omni
omnigraph schema apply --schema ./next.pg s3://my-bucket/repo.omni --json

# Merge review branch back
omnigraph branch merge review/2026-04-25 --into main s3://my-bucket/repo.omni

# Compact + GC (preview, then confirm)
omnigraph optimize s3://my-bucket/repo.omni
omnigraph cleanup  --keep 10 --older-than 7d s3://my-bucket/repo.omni
omnigraph cleanup  --keep 10 --older-than 7d --confirm s3://my-bucket/repo.omni

# Stand up the HTTP server (token from env)
OMNIGRAPH_SERVER_BEARER_TOKEN=xxxx \
  omnigraph-server s3://my-bucket/repo.omni --bind 0.0.0.0:8080

# Cedar policy explain
omnigraph policy explain --actor act-alice --action change --branch main

---

Capability matrix — "Lens by default vs. added by OmniGraph"

Capability	L1 (Lance default)	L2 (OmniGraph adds)
Columnar storage on object store	✅ Arrow/Lance	URI normalization, S3 env-var plumbing
Per-dataset versioning + time travel	✅	snapshot_at_version, entity_at, snapshot-pinned reads across many tables
Per-dataset branches	✅	Graph-level branches (atomic across all sub-tables), lazy fork, system branch filtering
Atomic single-dataset commits	✅	Multi-table publish via three layers, NOT a single Lance primitive: (1) per-table Lance commit_staged for the data write, (2) __manifest row-level CAS via ManifestBatchPublisher for cross-table ordering, (3) the open-time recovery sweep for the residual gap between (1) and (2). All three layers ship; the four migrated writers (MutationStaging::finalize, schema_apply, branch_merge, ensure_indices) write a __recovery/{ulid}.json sidecar before Phase B and delete it after Phase C. The next Omnigraph::open (gated on OpenMode::ReadWrite) runs the sweep in db/manifest/recovery.rs: classify, decide all-or-nothing per sidecar, roll forward via single ManifestBatchPublisher::publish or roll back via Dataset::restore, and record an audit row in _graph_commit_recoveries.lance (queryable via omnigraph commit list --filter actor=omnigraph:recovery). Continuous in-process recovery (no restart needed between Phase B failure and recovery) is the goal of a future background reconciler. Engine writes route through a sealed TableStorage trait exposing stage_* + commit_staged as the canonical staged-write surface; documented inline-commit residuals (delete_where, create_vector_index, plus legacy append_batch / merge_insert_batches / overwrite_batch / create_*_index) remain on the trait until upstream Lance ships a public two-phase API (#6658, #6666) and the migration of every call site completes.
Compaction (compact_files)	✅	omnigraph optimize orchestrates over all node/edge tables, bounded concurrency
Cleanup (cleanup_old_versions)	✅	omnigraph cleanup with --keep / --older-than policy
BTREE / inverted (FTS) / vector indexes	✅	ensure_indices builds them on every relevant column; idempotent; lazy across branches
merge_insert upsert	✅	LoadMode::Merge, mutation update/insert/delete lowering
Vector search	✅	nearest() query op; embedding pipeline (Gemini / OpenAI clients); @embed in schema
Full-text search	✅	search/fuzzy/match_text/bm25 query ops
Hybrid ranking	—	rrf(...) Reciprocal Rank Fusion in one runtime
Graph traversal	—	CSR/CSC topology index, Expand IR op, variable-length hops, not { } anti-join
Schema language	—	.pg + Pest grammar + catalog + interfaces + constraints + annotations
Query language	—	.gq + Pest grammar + IR + lowering + linter
Schema migration planning	—	plan_schema_migration + apply_schema step types + __schema_apply_lock__
Commit graph (DAG) across whole repo	—	_graph_commits.lance with linear + merge parents, ULID ids, actor map
Per-query atomic writes	—	In-memory MutationStaging.pending accumulator + stage_* / commit_staged per touched table at end-of-query + publisher CAS via commit_with_expected (single manifest commit per mutate_as / load); D₂ parse-time rule keeps inserts/updates and deletes from mixing
Three-way row-level merge	—	OrderedTableCursor + StagedTableWriter, structured MergeConflictKind
Change feeds	—	diff_between / diff_commits with manifest fast path + ID streaming
Cedar policy	—	8 actions, branch / target_branch / protected scopes, validate/test/explain CLI. Engine-wide enforcement (MR-722): every _as writer (apply_schema_as, mutate_as, load_as, ingest_as, branch_create_as / branch_create_from_as, branch_delete_as, branch_merge_as) calls Omnigraph::enforce(action, scope, actor) — HTTP, CLI, embedded SDK all hit the same gate.
HTTP server	—	Axum, OpenAPI via utoipa, bearer auth (SHA-256, AWS Secrets Manager option), authorize_request at the HTTP boundary (resolves bearer→actor, applies admission control), NDJSON streaming export
CLI with config	—	omnigraph.yaml, aliases, multi-format output (json/jsonl/csv/kv/table)
Audit / actor tracking	—	_as write APIs + actor map in commit graph
Local RustFS bootstrap	—	scripts/local-rustfs-bootstrap.sh one-shot S3-backed dev environment

---

Maintenance contract for agents

When you change something user-visible, update the relevant docs/user/<area>.md in the same change. Use docs/user/index.md for public behavior and docs/dev/index.md for contributor/internal mechanics. Pointers from this file to those docs must keep working — CI enforces cross-link integrity via scripts/check-agents-md.sh.

When proposing or reviewing a non-trivial change, walk docs/dev/invariants.md — at minimum the deny-list and review checklist. Add to the deny-list when a new anti-pattern surfaces; relaxing an invariant requires the same review process as code.

Rules:

1. Update in the same PR. New endpoint, query function, CLI flag, env var, constant, schema construct, or invariant: update both the source code and the doc in the same change. Never split documentation drift into a follow-up.
2. Bump version on release. When a release boundary crosses (e.g. v0.3.1 → v0.3.2), update the version line at the top of this file and add a docs/releases/<version>.md describing the user-visible delta. Update docs/dev/architecture.md only if the architecture itself changed.
3. Write OSS-facing release notes. Release docs are public project history. Describe capabilities, behavior changes, breaking changes, upgrade notes, and user impact; do not reference private ticket systems, internal codenames, or planning shorthand that an outside contributor cannot inspect.
4. Keep versioning coherent. A release bump must update every published crate manifest, local path dependency constraint, Cargo.lock, generated API metadata such as openapi.json, and this file's surveyed version. Do not leave mixed package versions unless the release plan explicitly calls for them.
5. Keep docs audience-neutral. Prefer stable public identifiers (versions, PR numbers, public issue links, crate names, endpoint names) over organization-specific labels. If internal context is useful for maintainers, translate it into a durable public rationale before committing it.
6. Don't lie. If a section becomes wrong but you can't rewrite it fully right now, replace the wrong line with *(stale — needs update after <change>)* rather than leaving silently incorrect text. Then fix it ASAP.
7. Re-verify before recommending. If you cite a flag, env var, endpoint, or constant to the user or in code, grep for it in source first. Memory and docs go stale; the code is authoritative.
8. Keep AGENTS.md short. This file is always loaded into agent context, so every added line has a recurring context-window cost. Prefer pointers and terse invariants here; put detail in docs/.
9. Keep AGENTS.md a map, not an encyclopedia. New deep content goes into docs/. Add an entry to "Where to find each topic" instead of pasting prose into this file. The "Always-on rules" section is the exception — it's for invariants that should always be in scope.
10. Re-read on schema/query/IR changes. Edits to schema.pest, query.pest, ir/lower.rs, query/typecheck.rs, or query/lint.rs should trigger a re-read of docs/user/schema-language.md, docs/user/query-language.md, and docs/dev/execution.md to confirm they still describe reality.
11. Always make smaller commits. Each commit does one thing, compiles, and passes tests; mechanical refactors land separately from the behavior changes they enable.
12. Test-first for bug fixes. When fixing an identified bug, write a regression test that reproduces the failure first. Confirm it fails against the current code with the predicted symptom (not an unrelated error). Then land the fix in a separate commit and confirm the test turns green. The test commit lands just before the fix commit so the red → green pair is visible in git log and a reviewer can check out the test commit alone and reproduce the failure.
13. Correct by design over symptomatic patches. When a bug surfaces, identify the root cause and make the fix correct by construction. Don't patch the symptom. If the design admits the bug class, the fix is to close the class, not to add a guard around the latest instance. A symptomatic patch is acceptable only as a stop-gap, with an explicit note in the commit message and a follow-up issue tracking the design fix.

CI check: scripts/check-agents-md.sh verifies that docs links in this file and the audience indexes resolve, and that every canonical doc is linked from either docs/user/index.md or docs/dev/index.md. Run it locally before opening a PR if you've moved or renamed docs.