Knowledge graph

The knowledge graph is a deterministic, cache-backed graph of the magus domain. Every node and edge is EXTRACTED or rubric-INFERRED from workspace sources - no LLM pass, ever - so it is safe to rebuild implicitly and byte-for-byte reproducible from the same inputs. It is assembled from machinery magus already owns: the verified project dependency DAG, static magusfile extraction, the spell/module/diagnostic registries, markdown docs, and buzz source parsing.

It exists so agents and humans can ask "what is this, what touches it, how do these relate" and get a precise answer instead of grepping. Agents reach it over MCP; humans reach it through three verbs and the magus graph home.

What this graph is not

"Knowledge graph" now names architectures this one deliberately is not, and the distance is the point.

• Not open-world. General knowledge graphs are genuinely hard: ontology design, entity resolution, and modeling discipline that stays expensive at scale. magus never attempts that problem. The build domain hands it a closed ontology - the node kinds and relations above are the complete list - so there is no modeling step to do well or badly, and no linking judgment to trust.
• Not a second indexer. Most codebase graphs are built by a separate system that scans the repo and infers structure, and the drift between that system and your build stays invisible until it bites. This graph is assembled from the same declarations the build executes. A wrong edge is a broken build, and a broken build is loud.
• Not synthesized links. No pass ever guesses an edge - no LLM, no fuzzy matching, no "related notes" heuristics. Every edge is extracted or rubric-inferred from a source you can open, and magus explain prints each edge's provenance so the claim is checkable per edge, not per marketing page.
• Not agent memory. The graph is derived state: rebuilt from the workspace, never accumulated, never remembered. Memory is a different surface with the opposite contract - magus memory is a user-owned journal of named decisions, written deliberately, and it stays small precisely because the graph answers everything derivable.

The two-concept model

• query / explain / path READ the graph - daily retrieval.
• magus graph IS the graph - emit it (deps), export it (export), or measure its shape (stats).

magus query "<terms>"       # ranked node matches plus their neighborhood
magus explain <node>        # one node: its edges, provenance, blast radius
magus path <a> <b>          # the shortest chain of edges between two nodes
magus refs <symbol>         # where an ingested code symbol is defined and referenced
magus graph stats           # god nodes, orphans, doc coverage
magus graph export -o json  # the whole graph as node-link JSON
magus graph diff base.json  # what this branch changed vs an exported baseline
magus graph export --open            # explore it visually in your browser (data stays local)

Prefer a picture? magus graph export --open launches the interactive Graph Explorer seeded with your own workspace - a force-directed, searchable view of the same graph. Your data never leaves your machine: it rides in the URL fragment (or a local loopback server with --serve), never reaching the site. This site's own graph is the live demo.

The committed MAGUS.md routing table is the entry point: it lists every node kind with its count, the query that lists it, and the highest-degree anchor nodes, so an agent knows what exists before running anything.

Query grammar

magus query takes free-text terms (AND) plus field matchers. A matcher is field<op>value, where the operator is = (match), != (exclude), or =~ (regex). Terms are scored with the same leaf-anchored fuzzy match that powers magus where.

The : grammar (kind:spell, -kind:op) is the pre-= spelling, kept as a compat alias so existing invocations keep working; new queries should use =/!=/=~.

A query resolves terms to seed nodes, then collects the induced neighborhood up to a node budget (--budget, default 50), so a match on a high-degree node cannot pull in the whole graph.

Questions you can ask

Recipes for the graph as a lens on the workspace. Rebuild first with magus graph build if you want it fresh; combine field filters freely.

What programs does the workspace actually run? magus owns the task layer, so it knows the concrete tool behind every operation - not just the source.

magus query "kind=tool"                    # the workspace's toolchain (go, buf, docker, ...)
magus explain "tool:go"                    # every op and spell that runs go
magus explain "op:go:go-test"              # an op's base argv (the `argv` attr) and its tool
magus path "target:.:test" "tool:go"       # a target reaches its tool via target->op->tool

Each spell op carries the base argv it runs on an argv attr (rendered with empty charms) and uses the tool:<program> node for its argv[0] - the program, its own kind because it is an entity, not an operation. The op's spell uses the tool too, so magus explain tool:go lists every op and spell that runs go; a target reaches the tool through its existing target --uses--> op edge. (There is no per-target command node: its argv was always identical to the op's, so the op carries the model.)

So magus explain tool:go lists every op that runs go:

$ magus explain tool:go
tool:go   tool
tool: go
13 nodes reach this

used by (10)  op:go:go-build, op:go:go-clean, op:go:go-generate,
              op:go:go-mod-edit, op:go:go-mod-json, op:go:go-mod-tidy,
              op:go:go-run, op:go:go-test, op:go:go-vet, spell:go

View in Graph Explorer: http://127.0.0.1:7391/console/graph/#view=blast&node=tool%3Ago
(append &token=$(magus config token print) to open it authenticated)
(start the magus daemon if the graph does not load)

A target shows what it runs and what runs it, each relation in plain words:

$ magus explain target:.:test
target:.:test   target
Run the Go test suite; formats first.
source: .
engine: buzz
1 node reaches this

uses (2)    op:go:go-test, spell:go
depends on  target:.:format
part of     project:.

View in Graph Explorer: http://127.0.0.1:7391/console/graph/#view=blast&node=target%3A.%3Atest
(append &token=$(magus config token print) to open it authenticated)
(start the magus daemon if the graph does not load)

And path connects two nodes as a chain - a target reaches its tool through its op:

$ magus path target:.:test tool:go
target:.:test -> tool:go  (2 steps)

target:.:test
  uses  op:go:go-test
  uses  tool:go

(These blocks are generated by magus-examples from a fixture workspace and kept current by the drift gate; do not hand-edit the output.)

Where does a function or symbol live (as path:line), and where is it used?

magus refs <name>                          # the definition + every reference, each as path:line
magus explain "symbol:<id>"                # the node's `source` is the definition's path:line
magus query "kind=symbol <name>" -o json   # each match's `.source` is "path:line"

Symbol nodes carry their definition as source: "path:line", and refs returns every reference the same way. An agent (or an MCP tool) can read the exact line straight from the graph and edit surgically instead of loading the whole file.

Where does risk concentrate?

magus_insight lens=hotspots   # churn x complexity per project, with blast radius (MCP)
magus_insight lens=affinity   # projects that change together: hidden coupling
magus_insight lens=ownership  # author concentration and bus factor
magus explain <node>      # a node's edges and how many nodes reach it (blast radius)
magus path <a> <b>        # the shortest edge chain between two nodes

Which code lacks test coverage? magus runs the tests, so it owns the coverage profile - a pure code-graph tool cannot answer this.

magus explain "symbol:<id>"      # a function's coverage ratio + test_refs (test files that reference it)
magus query "kind=file" -o json  # each file node's attrs.coverage (covered/total statements)

After magus run test (or magus run ci), a coverage attr (with covered_stmts / total_stmts) folds onto file and symbol nodes, and test_refs counts the test files that reference a symbol. Sort symbols by coverage ascending for "what is untested", or cross it with insight hotspots to rank high-churn, low-coverage code first.

What does a target produce or consume, and is a file generated? magus indexes each target's declared magus\outputs / magus\inputs, so the graph knows the build's file flow - which a pure code-graph cannot.

magus explain "target:.:content-generate"   # the files a target produces and consumes
magus explain "doc:docs/spells/go.md"        # a "produced by" edge means it is generated

Each declared output/input becomes a produces / consumes edge to the file and doc node it matches, so a generated file is self-labeled by its producing target (no marker needed) and you can walk from a target to exactly what it writes.

Which markdown is what? Every authored markdown file in the workspace is a doc node tagged with a role from a universal filename convention - so it works in any repo.

magus query "kind=doc role=agent"    # the agent-instruction files (AGENTS.md, CLAUDE.md)
magus query "role:readme"            # every README, wherever it lives
magus query "kind=doc role=skill"    # skill definitions (SKILL.md)

Roles are readme, agent, skill, changelog, contributing, license, or a plain doc. Each doc attaches to the project whose directory holds it (project --contains--> doc), so from a project you reach its README and design notes as contextual docs.

Graph Explorer

magus graph export --open opens the graph in an interactive, force-directed Graph Explorer in your browser - privately. Your graph never leaves your machine: by default it rides in the link's URL #fragment (which browsers never send to a server), and --serve instead hands it to the page from an ephemeral 127.0.0.1 loopback server that serves once and stops. The hosted page is static; it decodes or fetches the graph locally.

magus graph export --open           # default: gzip'd into the URL fragment (small/medium graphs)
magus graph export --open --serve   # loopback server (no size limit; serves once, then stops)
magus graph export --open --print   # print the URL instead of opening a browser
magus graph export --open --url <base>   # point at a self-hosted mirror of the explorer

Open your target graph

To open the target dependency graph (the magus\needs DAG, not the knowledge graph) in the same explorer:

magus graph export --open --targets                # whole workspace
magus graph export --open --targets .              # scope to root project
magus graph export --open --targets docs        # scope to one project by path
magus graph export --open --targets --print        # print the URL instead of opening

The --targets path always uses the URL fragment (no loopback server); it is incompatible with --serve. An unknown project path exits with code 2 and lists valid paths.

The explorer's filter box speaks the same fielded grammar as magus query (kind:, project:, relation:, id:, free text, "quotes", -negation); a query dims non-matching nodes so the subgraph stands out. Beyond the filter: double-click a node for its local graph (its neighborhood, [/] to change depth), click a legend color to isolate a kind, and use the hubs/orphans lenses (the visual twin of magus graph stats). The page is fully client-side and data-agnostic - it also loads any graph.json from magus graph export -o json via the Open-file button or drag-and-drop. This site's own graph is the demo.

Schema

A node is a magus-domain entity with a stable, human-readable ID (<kind>:<qualified-name>, e.g. target:pkg/foo:build). The ID is stable across builds so external consumers and agent memory can key on it. A rename is a delete-plus-add.

Node kinds: project, target, spell, op, charm, module, method, diagnostic, doc, file, function, import, rationale, owner.

Nodes also carry static metadata the extractors already parse, surfaced as attributes so magus explain answers a question without a second describe: a project reports its engine and target_count, each target inherits its project's engine, and a doc page carries its frontmatter title and tags. Attributes are additive and absent when unknown, so they never bump the schema version.

Edges are directed and carry provenance and a confidence tag - extracted (1.0, from a parseable source) or inferred (a rubric score, from a fuzzy match).

Relations: depends_on, contains, uses, calls, imports, references, documents, rationale_for, owns. calls spans two layers: buzz function to buzz function, and code symbol to code symbol from a SCIP index.

Ownership is extracted from a committed CODEOWNERS file (checked at the repo root, .github/, or docs/): each owner becomes an owner node with an owns edge to every project and buzz file it covers, under GitHub's last-match-wins rule, with CODEOWNERS:<line> provenance. Only declared ownership is taken - blame-derived ownership is insight's job, not a graph edge - so "who owns the blast radius of this change" is one path query.

Both node-link JSON and GraphML carry a schema_version; external consumers and agent skills should check it, since a bump is a changelog event.

File layout

The graph lives under the cache dir at .magus/knowledge/, cache-owned and NOT committed by default - the build is cheap and deterministic, so committing derived data buys nothing (export exists for teams that want a snapshot).

.magus/knowledge/
  manifest.json        per-shard fingerprints and counts (the routing index)
  shards/<name>.json   one file per shard; SHARDS ARE AUTHORITATIVE

There is no continuously maintained merged graph.json: at scale, rewriting a merged file on every edit is an O(graph) write. Merging happens in memory at load time; the merged export is produced on demand. Shards are per-project plus singletons for the registry (spells/modules/diagnostics), docs, buzz sources, and run history (@runtime, below). A query loads the store, fingerprint-checks each shard, and rebuilds only the stale ones - the "cache that gets hit first". First run pays a full build; steady state is a fingerprint check. --refresh forces a full rebuild.

Two optional knobs bound and share the store. knowledge.max_size_mb soft-caps the shard directory: over the cap, least-recently-used shard files are evicted (their manifest entries stay, so an evicted shard is restored from the remote cache or rebuilt on the next query; 0, the default, is unlimited). When a remote build cache is configured, deterministic shards ride it - pushed on build, restored by fingerprint - so teammates and CI can reuse them. The @runtime shard is never pushed: it is local run history, not shareable derived data.

Runtime enrichment

Beyond the static graph, magus records which diagnostics (MGSxxxx codes) each target trips during real runs, as emits edges in the isolated @runtime shard. A run captures every fired diagnostic through one sink that also feeds the report stream, and persists the set to <cache>/knowledge/runtime.json. This answers "what has this target tripped" - history the static documents edge cannot. The same shard also folds observed performance onto target nodes from the local timing history: duration_p75_ms, cache_hit_rate, and run_samples, so an agent planning work sees a target's cost without a separate history query. It also folds each target's last_output_ref (the refxxxxxxxx id of its most recent captured run) and last_run_ok (true/false for that run) from the local output store, so an agent goes query -> target -> the last captured output in two hops (magus query output <ref>). Timings and refs for a target no longer in any magusfile are dropped rather than left as phantom nodes. This is the graph's only non-deterministic input, so it is quarantined: a distinct shard, excluded from remote export, derived from local run records rather than workspace sources.

Code symbols (SCIP ingestion)

magus never parses source code. To bring code symbols into the graph, it ingests a SCIP index file that a per-language indexer (scip-go, scip-typescript, ...) emits - so any language with an indexer works, with no magus code per language.

This is automatic. Every symbol-capable spell (go, ts, py, rust) exposes a reserved scip op that runs its indexer. Importing the language's spells is the entire opt-in: each project bound to such a spell is ingested with no knowledge: config. Build the index the same way you run any target:

magus run pkg/foo::scip   # forks the language's SCIP indexer

The index is a build artifact, so it lives under the magus cache dir, never in the source tree: magus hands the indexer the destination through a MAGUS_SYMBOL_INDEX environment variable it injects for the scip op, and reads that same path back at query time. The next graph query folds the symbols in.

The daemon keeps it fresh for you. While the daemon runs, background auto-indexing re-runs each symbol-capable project's scip op when its sources change, so symbols stay current with no manual step. It is deliberately unobtrusive: a burst of edits coalesces into one run (a quiet window), a project re-indexes at most once per interval, a run starts only when nothing else is running, and it cancels itself the moment your own work needs a slot. Each run goes through the normal path, so it shows up as an ordinary journaled job, not hidden work. It is on by default in the daemon; a one-shot CLI never auto-indexes. Tune or disable it under knowledge.symbol_indexing (disabled, quiet_seconds, min_interval_seconds). If an indexer is not installed the background run just fails and backs off - run magus run <project>::scip yourself, or index in CI.

An index that has not been built yet is simply skipped, so symbols appear once the scip target has run. To point a project at an index your own build already emits somewhere in the tree instead, override it:

# magus.yaml
knowledge:
  symbols:
    - project: pkg/foo
      index: build/custom.scip # a workspace-relative path magus reads as-is

Each ingested index becomes a per-project <project>@symbols shard: symbol nodes (keyed by their version-stripped SCIP moniker), defines edges from the defining file, references edges from each using file (one per file, carrying an occurrence count and capped lines), and calls edges between symbols.

A call edge is attributed, not inferred: SCIP records an enclosing range for each definition, so a reference occurrence that falls inside one was written in that definition's body, and the enclosing symbol is the caller. Two restrictions keep the relation honest. The callee must be something callable - an enclosing range spans the whole declaration, signature included, so most occurrences inside it are types and fields rather than calls. Callability is read off the moniker's SCIP descriptor suffix rather than the optional SymbolInformation.Kind, so it does not depend on an indexer choosing to populate a field: scip-typescript sets no kinds at all, and a kind-based rule would silently produce no calls for an entire language. And the callee must be defined in this workspace: a call into a dependency has no body to navigate to, and its usage is already recorded by the referencing file's references edge. A symbol seen only as a reference still gets a node, so cross-project usage resolves. Every indexed source file also becomes a browsable file node the edges land on, linked to the project that owns it - so a .go or .ts file sits in the graph the same way a .buzz file does, reachable from its project and the workspace. SCIP paths are relative to the indexer's root, so magus rebases them onto the project's workspace path; a nested project's files land under the right project, not the workspace root.

Both file and symbol nodes carry a language attr, so magus query language:go groups every Go source file and symbol - and language:buzz the buzz sources - one filter across everything the graph knows, however it was extracted (magus's own AST walk or a foreign SCIP index).

SCIP makes a document's language optional and not every indexer sets it (scip-typescript sets it on none), so magus falls back to the language the producing spell declares - the same declaration that made the project symbol-capable. A document that names its own language still wins, since one index may legitimately span several.

Symbol shards can dwarf the domain graph, so they are lazily loaded: the default magus query/magus graph stats/magus graph export --open/warm graph never touch them. They load only when a query is symbol-seeded - kind:symbol, a symbol: ID, relation:defines/references/calls, or the refs verb. magus refs <symbol> lists a symbol's definition and every referencing file (magus_refs over MCP, paginated). At very large scale a derived shards/@symbols.routing.json (symbol hash to referencing shard names, rebuilt with the shards) lets an exact-ID lookup load only the shards that mention the symbol rather than all of them; a missing routing file just falls back to loading all.

The third verdict: when an empty answer is not a fact

A lookup that returns nothing has two very different meanings, and collapsing them is how a blind spot gets recorded as a fact. magus query, magus explain, and magus refs all say which one they mean:

An unknown verdict names its cause. symbol-index-missing lists the projects whose declared SCIP index magus could not read, which magus graph build fixes. symbols-not-loaded means the lookup never consulted the symbol layer at all - a bare magus query someFunc searches domain entities, so it says nothing about whether a code symbol by that name exists, and magus refs someFunc is the verb that would know. coverage-unknown means the probe itself failed, so magus cannot say what it searched.

A verdict is not only for empty results: a populated list drawn from a half-indexed workspace is as misleading as an empty one, because the projects it omits are invisible either way. So a gap makes the answer unknown whether or not the lookup matched.

The verdict rides the structured output as an answer field, so an agent branches on answer.verdict rather than pattern-matching prose:

magus refs SomeSymbol -o json    # .answer.verdict, .answer.reason, .answer.gaps[]

Over MCP every verdict comes back as a result rather than an error, so an agent branches on the field in all three cases rather than pattern-matching an error string for one of them.

Exit codes follow the same split. refs and explain exit 2 on absent - the request cannot be carried out as stated, and magus verified that - and 1 on unknown, where the invocation was fine and a prerequisite artifact was missing. A refs lookup that resolved but found no references follows the verdict too, exiting 1 when magus could not verify the emptiness: "nothing uses this" is a negative claim like any other. magus query exits 0 when it can answer - it matched, or it verified the absence - and 1 when it cannot: nothing matched and the verdict is unknown, the case magus graph build fixes. It never exits 2, and it never fails on a populated result, whose unknown caveats rows that are facts already. An empty result set stays a legitimate answer to a search; a blind spot is not one, and a caller that reads it as "not in the graph" goes back to grepping.

The coverage probe is one stat per declared index, and it is skipped entirely when the symbol layer was irrelevant to the question - kind:author returning nothing has nothing to do with a missing symbol index, so nothing about one is reported. The probe deliberately does not decode each index to check it parses: that is a full unmarshal per lookup to catch a case the graph build already logs, while a never-built index is the case that actually occurs.

Git history (@vcs)

Opt-in, off by default: enable it to fold each file's git history onto its file node.

# magus.yaml
knowledge:
  vcs:
    enabled: true
    max_commits: 1000 # optional: bound the history walk (default 1000)
    authorship: true # optional: include author nodes + authored edges (default on)

When enabled and the workspace is a git repo, a @vcs shard adds four attrs to every file node: vcs_last_commit (short SHA of the most recent commit touching the file), vcs_last_modified (its date), vcs_last_author (who last touched it), and vcs_commits (commits touching the file within the window). It also mints an author node per contributor with an authored edge to each file they touched in the window - who edits what, so an agent can ask magus explain author:Ada or trace ownership. These edges are uncapped: max_commits already bounds the scan, so a dominant maintainer legitimately having many is a fact to teach, not a smell. Set authorship: false to keep only the per-file vcs_* attrs and drop the author layer.

The values are EXTRACTED from git and deterministic per commit, so the shard is remote-shareable like the other extracted shards. The git log walk is bounded by max_commits and keyed by an input fingerprint (schema, HEAD, the window, the dirty-file set, and the authorship flag), so the standard shard store reuses it whole and it re-runs only when one of those actually moves - never on the query path. A non-git workspace or a git error simply yields no shard. Because the vcs_* attrs vary by commit, magus graph diff strips them from both sides, so a file node is not reported as changed just because its last commit moved - the diff stays structural.

Human-authored notes

Everything else in the graph is DERIVED from the workspace: a doc from markdown, a rationale from a comment, a symbol from an index, an author from git history. Delete the graph, rebuild it, and all of that comes back.

A note is the exception. Its content originates with a person, nothing in the repository corroborates it, and no rebuild recovers it. That single property is why the store looks the way it does.

If you have played Dark Souls, you have already used this. Players there cannot talk to each other; they can only leave a short message on the ground where they are standing, and everyone who passes that spot afterwards reads it. A few are jokes. Most are someone who just got caught by something, telling you what caught them - and they beat any wiki, because they are lying exactly where you needed them.

That is what a note is for, and the rest of this section is the machinery that keeps the promise. Not documentation filed somewhere central and read by nobody: one sentence left at the spot in the code that earned it, for whoever arrives next. An anchor is how it stays at that spot when the code moves, verify is how it speaks up when the spot quietly stops meaning what the note said, and git is how the person who left it has their name on it.

Where a note goes, and what that means

There is one question that matters to a reader - may I act on this without checking it? - and it makes two tiers:

Between them sits one command. magus notes promote <record> opens an agent's draft in your editor, derives the note's anchors from the record's node refs, and writes it to the shared store - and it refuses a body you did not change, because promoting without reading is an agent's claim with your name on the commit.

That refusal is the whole boundary. An agent may still never write a note, but the rule it enforces is not really "a human typed this" - a person pasting an agent's prose into $EDITOR always passed it. What the store actually guarantees, and the stronger claim, is that somebody accountable pressed commit, which git records whether or not the first draft was theirs.

Writing a note straight into the committed tier is still supported and still the right move when the reasoning is already yours: magus notes edit opens a scaffold and gets out of the way.

knowledge:
  notes:
    shared: notes        # a directory IN the repo: committed, so git records who wrote each note

One sentence each, and the whole surface follows from them:

• notes.shared - a person stands behind it, the team has it, git says who. Must live inside the checkout; outside it there is no commit to attribute a note to and no review to have seen it, so "shared" would be a claim the location cannot back.
• knowledge.notes.private - superseded, still read. A second notes location, yours rather than the team's, anywhere on disk. It is no longer the recommended shape: line the stores up by property and it has no column of its own, because a private note and a memory record are both uncommitted, unattributed, unreviewed and unrecoverable. The one thing it had that memory did not was anchors, and notes promote closes that. Existing stores keep working; new workspaces should use the drafting tier instead.
• magus memory - an agent wrote it, only this machine has it, and every entry cites a ref a later reader can re-run.

Every note node carries a scope attr (shared or private), so a reader can always tell which of the two they are looking at without knowing which shard it came from.

What a note looks like, and living in a vault

Everything magus stores sits under one magus: frontmatter key. Nothing outside it belongs to magus, and nothing inside it belongs to anyone else:

---
tags: [architecture, cache]   # yours (or Obsidian's); magus never reads or rewrites these
aliases: [pairing]            # yours
magus:                        # magus's, all of it
  id: cache-pairing           # optional, stable identity - survives moving or renaming the file
  title: The two caches invalidate together
  anchors:
    - kind: symbol            # survives the code moving file and line; breaks on rename or delete
      target: "m internal/cache/Store#Put()."
    - kind: file              # a path, when no single symbol covers it
      target: internal/cache/cache.go
---

Nothing in the code says these must be cleared together.

That key is also the opt-in. A file with no magus: block is not a magus note, no matter what else is in it. This is what makes pointing notes.private at an Obsidian vault work: a vault of a few thousand files contributes only the handful you actually anchored, and the rest are read past in silence rather than reported as malformed notes.

Three consequences worth knowing:

• magus never rewrites your other frontmatter. When it records an anchor fingerprint it replaces the magus: block and leaves every other key, and their order, exactly as they were.
• id is what survives a reorganization. Without it a note is identified by its path, so renaming the file in Obsidian - which rewrites your [[wikilinks]] and knows nothing about magus - changes the note's identity and dangles anchors pointing at it. magus stamps an id on every note it creates; add one by hand to a vault note you intend to keep. Notes are looked up by id first, then by path.
• Nested folders are walked, dot-directories (.obsidian, .trash) are skipped, and a scan stops at 5,000 markdown files and says so rather than silently loading half a vault.

symbol, file, project, target, and note are the whole set. There is deliberately no line-anchored kind: a node ID is checkable, so its breakage is reportable, while a line number changes on the next edit above it with nothing to detect. Anchor as narrowly as the knowledge allows - a coarse anchor is more durable, and multiple anchors are how a note records something no single comment could hold ("these two caches must be invalidated together").

Staying honest

magus notes verify answers two questions per anchor:

• Does it still resolve? A renamed or deleted subject reports dangling-anchor, with the coarser anchor it degrades to. Nothing is ever re-pointed at a guess.
• Did the content change? A stored fingerprint of the anchored definition detects the more common and more dangerous case - the code still exists and quietly stopped saying what the note claims. The fingerprint ignores whitespace, so reformatting is free, and reacts to tokens, so a real edit is loud.

Recording that fingerprint is a deliberate human act: magus notes edit stamps it, because the person just had the note and its subject in front of them. Verify only ever reports.

Retrieval labels, and never reorders. A match whose subject has moved on carries its verdict and outrun_days so a reader can see "400 days behind its subject" beside the result, but it keeps its rank.

Ranking on staleness was tried and removed, because it points the wrong way. Code that keeps changing is where knowledge is worth most - relative churn is one of the better predictors of defect density - so demoting the prose about a moving subject hides it exactly where it is needed. Elapsed days measure calendar time rather than divergence: a note and its subject both untouched for a year are settled, not stale. And prose whose subject is gone is often the only surviving record of why it went, which is the last thing a search should bury. Systems that solved this in production reached the same answer - Google's g3doc carries a "last reviewed" byline, and Guru keeps an unverified card searchable and visible with its lapsed state shown. Both label. Neither demotes.

Exporting to external tools

magus emits; it does not render. To look at the graph, export it and open the file in a graph tool - files are the interface.

magus graph export -o json > graph.json       # node-link JSON (NetworkX, D3, ...)
magus graph export -o graphml > graph.graphml  # GraphML (Gephi, yEd, ...)

For a specific neighborhood rather than the whole graph, --select reuses the query engine, and the layout formats become available (they are unreadable on the full graph, so they require a scope):

magus graph export --select "kind=spell go" -o mermaid
magus graph export --select "project=pkg/foo" --budget 80 -o dot

Diffing against a baseline

magus graph diff reports what a branch did to the domain's shape: the nodes and edges added or removed, and (for nodes) which fields changed. Export a baseline on the base branch, then diff the working tree against it - the PR blast-radius artifact.

magus graph diff --rev HEAD~1                    # against a git revision, no export needed
magus graph diff --rev main -o markdown          # a CI comment vs the base branch

git stash && magus graph export -o json > /tmp/base.json && git stash pop
magus graph diff /tmp/base.json                  # against an export file
magus graph diff /tmp/base.json -o json          # machine-readable, with before/after

--rev builds the base graph from that revision's tracked files (domain-only, using the current config) in an isolated throwaway tree that never touches your real cache; it and the positional baseline are mutually exclusive, and it cannot be combined with --global (the base is a single-workspace build). A baseline file must be a whole-graph magus graph export -o json (symbol shards in it are matched automatically; pass --global if the baseline was global). Edge diffs are structural - an edge is identified by (source, target, relation), so a re-scored or re-provenanced edge that keeps those three is not reported as a change.

Global graph (across workspaces)

An org running magus across many repos can query all of them at once. Register extra workspace roots in config, then pass --global:

# magus.yaml
knowledge:
  workspaces:
    - ../api
    - ../web

magus query "kind=spell" --global   # matches across every registered workspace
magus graph stats --global          # union shape across repos

--global is available on query, explain, path, and magus graph export/stats. Each workspace's node IDs are namespaced by the workspace (api//spell:go, web//spell:go) so IDs from different repos cannot collide; the unqualified ID stays a readable substring, so magus explain go --global still resolves. A registered workspace that cannot be opened is skipped rather than failing the query. There is no cross-workspace edge inference - a union with qualified IDs only.

Extraction diagnostics

When extraction cannot resolve something cleanly it records a silent MGS7xxx code as a node attribute (visible via magus explain), rather than logging - so an implicit rebuild stays quiet while the ambiguity stays queryable. The first two are MGS7001 (a buzz import that resolves to no file) and MGS7002 (a doc citing an unregistered code).

For agents

The MCP daemon exposes the verbs as tools: magus_query, magus_explain, magus_path, magus_stats, and magus_refs (plus magus_output, which retrieves a target's captured output by ref). See MCP for wiring. Prefer these over grep to find and relate magus-domain entities; start from the MAGUS.md routing table, which is already in context in a fresh clone.

For a large result set, magus_query and magus_refs page: pass limit to cap the rows per response and echo the returned next_cursor to fetch the next page. The cursor is stateless and self-validating - it carries the query and a graph fingerprint, so a cursor reused against a different query or a graph that changed between pages is rejected rather than returning an incoherent slice.

magus agent install .agents/skills equips Codex with Agent Skills, and prints the always-on AGENTS.md block for you to paste - magus never writes that file. Claude Code uses magus agent install .claude/skills. The skills teach HOW to use magus (the repo's MAGUS.md says WHAT is in the workspace): knowledge-graph verbs, target-first execution, generated-file triage, and graph-grounded refactoring. They ship with the binary and teach only the tool surface, so they stay current with the magus version rather than the workspace. Each installed file carries a version footer, and magus doctor reports actionable drift after an upgrade. See Agents for the full host setup.

Prior art

Two projects shaped this design, and both deserve credit. The thread starts earlier than either: Andrej Karpathy's April 2026 post on X described keeping a raw folder of papers, notes, and screenshots and wanting to query across it without rereading every file. Graphify was built within days as a direct answer to that post, and the magus knowledge graph is a further step down the same path: the querying idea applied to the one domain a build tool already understands precisely.

Graphify established the pattern of a queryable, committable code knowledge graph with an honest audit trail, and its verb vocabulary was good enough that magus reuses it outright: query, explain, path. The two tools have different jobs, though. Graphify is a general corpus indexer - point it at any folder of code, docs, papers, or media and it extracts a graph, using an LLM pass for non-code content. magus only ever models its own domain, and its graph is assembled entirely from declarations it already verifies as a build tool (the project DAG, target sources and outputs, spell and module registries), so the build is deterministic, runs with zero LLM involvement, and stays cache-owned rather than committed. If you want a graph of an arbitrary corpus, Graphify is the right tool; the magus graph is narrower and, within its domain, checkable edge by edge.

Obsidian shaped the handoff-journal side: durable, linked markdown the user owns and any tool can read. magus borrows that files-first stance deliberately, but keeps the scope small: named decisions, plans, and pointers that a later person can reopen. It is not automatic agent memory. magus memory verify makes malformed, stale, and broken-linked entries visible instead of quietly skipping them.