trackinizer🐾

Epistemological database for agent and human efforts, beliefs, and findings.

Quick Start

# Mac:
#   # Required for quick install.
#   brew install uv
#   # Optional for a real Postgres backend; default uses pglite engine.
#   brew install postgresql@18 pgvector

# Ubuntu/Debian:
#   # Required for quick install.
#   sudo apt-get install -y curl
#   curl -LsSf https://astral.sh/uv/install.sh | sh
#   # Optional for a real Postgres backend; default uses pglite engine.
#   PG_MAJOR="$(apt-cache depends postgresql | grep -m1 -oP 'postgresql-\K\d+')"
#   sudo apt-get install -y postgresql "postgresql-$PG_MAJOR-pgvector"

uv tool install trackinizer

# Local server; web UI at http://127.0.0.1:8765.
trackinizer

# CLI to trackinizer server.
trax

Centralized agent database for inquiries (Issues + Artifacts), work, and knowledge. Three core tables (inquiries, edges, change_log) backed by Postgres (real or PGlite). FastAPI on top.

types/ is the design contract. Every other module is a realization of that contract over Postgres + HTTP.

The UI

The optional SPA (server/web.py) browses the same records the API serves.

Graph -- the whole inquiry web (Issues, Beliefs, Papers, Experiments, …) as typed nodes and edges.

Console -- live multi-agent chat, filterable by room and date.

Belief -- a record with its before/after relationship panels.

Paper -- abstract, authors, and cites edges to other papers.

Experiment -- outcome, labels, and links to the beliefs it proves or disproves.

The model

Everything in the system is an Inquiry, which has two variants: an Issue is a unit of "work" and an Artifact is the output of that work. Giving both a single type is what lets the same edges relate them -- work can produce knowledge, and knowledge can elicit more work, without crossing a type boundary.

Each row below lists the fields that class adds; every kind also has everything above it.

Inquiry                  # An effort, ongoing or completed.
│   id
│   seq
│   owner
│   account
│   status
│   title
│   description
│   labels
│   marginal_cost
│   subscribers
│   superseded_by
│   supersedes
│   produces
│   produced_by
│   created
│   modified
│
├── Issue                # Work to pursue.
│       issue_kind
│       validation
│       priority
│       narrows
│       narrowed_by
│       requires
│       required_by
│
└── Artifact             # Knowledge produced and cited.
    │   proves
    │   favors
    │
    ├── Experiment       # Empirical measurement.
    │       codechanges
    │       outcome
    │       config
    │       proved_by
    │       favored_by
    │
    ├── Belief           # Proposition.
    │       judgement
    │       confidence
    │       proved_by
    │       favored_by
    │
    ├── Paper            # Bibliographic source.
    │       abstract
    │       authors
    │       publication_type
    │       venue
    │       subvenue
    │       publish_date
    │       source
    │       google_scholar_cluster_id
    │       google_scholar_cites_id
    │       cites
    │       cited_by
    │
    ├── CodeChange       # One git commit.
    │       sha
    │
    ├── WebSearch        # One query.
    │       query
    │       provider
    │
    ├── WebResult        # One URL.
    │       url
    │
    └── AgentSession     # A captured CLI run.
            cli
            cli_session_id
            started
            ended
            rooms
            opened_by_api_key_id

Relationships are directed and every one has an inverse view, so a parent and a child describe the same edge from either end:

                              OLDER  (parent)

    {narrows,requires}     {produced_by,supersedes}     {proves,favors}
            ▲                         ▲                        ▲
            │                         │                        │
          Issue ┄┄┄┄┄┄┄┄┄┄┄┄┄┄┄┄┄▷ Inquiry ◁┄┄┄┄┄┄┄┄┄ {Belief,Experiment}
            │                         │                        │
            ▼                         ▼                        ▼
{narrowed_by,required_by}  {produces,superseded_by}  {proved_by,favored_by}

                               NEWER  (child)

• Parents are always older than children, on each edge's own clock: creation-time for every edge except requires, which is completion-time.
• Any Inquiry can be produced_by older ones (its origins) and superseded_by others (M:N knowledge surgery).
• An Issue can be narrowed_by (broader to narrower) or required_by (it is the prerequisite another waits on). Both are Issue to Issue.
• proves / favors go from any Artifact to a Belief or Experiment -- anything may cite, only a claim may be cited. They carry a valence in [-1, 1]: sign is polarity, magnitude is weight. proves votes in the proof predicate; favors is context that informs but does not vote.
• cites / cited_by is Paper to Paper and stands apart from the six above: a bibliographic fact we record rather than a claim we reason over. No valence, no scheduling effect, and exempt from the acyclicity rule, since mutual citation is real data and not a cycle we own.

See docs/epistemy.md for why each verb is named what it is.

Storage

Three tables carry the model and other tables support them.

Per-kind detail that does not fit one row lives in its own table, keyed back to inquiries(id) and deleted with it:

Auth is three more: users, api_keys (scrypt-hashed, prefix-indexed), and allowlist.

The typed fields on Inquiry (produces, supersedes, citation lists) are projections the Store fills by reading edges -- the edge table is the real storage.

Package dependency graph

Four layers, two legs sharing one contract spine. An arrow means "imports / depends on" and points toward the dependency.

┌──────────────┐                      ┌──────────────┐
│    trax      │                      │    server    │   leaves: nothing
│    (CLI)     │                      │  (__main__)  │   imports these
└──────┬───────┘                      └──────┬───────┘
       │                                     │
       ▼                                     ▼
┌──────────────┐                      ┌──────────────┐
│   client     │                      │     api      │   server leg adds
│ (httpx SDK)  │                      │  (FastAPI    │   Store; client leg
│              │                      │   handlers)  │   adds httpx
└──────┬───────┘                      └──────┬───────┘
       │                                     │
       └──────────────┬──────────────────────┘
                      │  both import
                      ▼
              ┌───────────────┐
              │     wire      │   transport contract = THE API
              │  bodies       │   definition (request/response
              │  routes       │   models, route table, filters, refs)
              │  filters      │
              │  refs         │
              └───────┬───────┘
                      │
                      ▼
              ┌───────────────┐
              │     types     │   domain dataclasses;
              │  inquiries    │   imports nothing internal
              │  edges        │
              │  change_log   │
              │  cost         │
              └───────────────┘

Two legs, one shared spine:

• client leg: trax → client → wire → types
• server leg: server/__main__ → server/api → wire → types

The whole point of this split: types/ + wire/ + client/ form a self-contained client distribution. wire/ and client/ never import api, server, store, web, fastapi, asyncpg, or trax, so a published Python client carries no server dependencies.

Layering rules

1. types/ is a closed island. Nothing in types/ imports anything outside it. Everything else eventually imports from it. The dataclasses, Protocols, and ColumnSpec metadata in types/ are the data design contract; the rest of the package realizes it.

2. wire/ is the API contract; it is the single definition of the HTTP surface. It holds the Pydantic request/response bodies (FieldSet[T], FieldOp[T], FieldMutation, Submit*, edge bodies), the Filter/Ref shapes, and the route table the server registers from and the client builds requests from. It imports types/ and nothing else internal. Server and client both derive from it, so neither hand-writes a path or a body shape -- that is what prevents server/client/doc drift.

3. client/ is the standalone SDK; trax is a thin CLI over it. client/ is wire/ + httpx. trax owns only CLI concerns (grammar, parsing, rendering) and calls client.Client. Neither client/ nor wire/ may import the server side or the CLI.

4. No cycles. Each arrow above goes one direction. server/primitives.py imports server/setter_dispatch.RUNTIME_HOOKS and mutates it at import time (late-binding the results / codechanges validators). server/store.py imports primitives, so the side effect lands before any Store instance is constructed.

5. server/sql.py is orthogonal. It loads assets/schema.sql from disk. server/schema_gen.py substitutes generated bodies into the loaded text at bootstrap; the two never import each other.

6. server/api/ is the HTTP boundary. Routes are thin: pydantic-validate the wire body, call one Store method, serialize the result. Anything non-trivial belongs in server/store.py, not in a route.

Reading order

Pick one of these orders depending on what you came in for.

• "What does Trackinizer model?" Start in types/. Read inquiries.py, then edges.py, then change_log.py. Read docs/design.md for the model and philosophy.

• "What is the HTTP API / how do I avoid drift?" Start in wire/routes.py: the route table is derived from the ColumnSpec metadata in types/inquiries.py. The server registers handlers by iterating it (server/api/edit.py, edge.py), the client builds requests from it (client/client.py), so neither hand-writes a path. server/api/routes_drift_test.py and assets_drift_test.py fail if a handler or the SPA diverges from the table.

• "How does a submit reach the database?" server/api/submit.py → wire/bodies.py (body validation) → server/store.py (submit_X) → server/primitives.py (insert_inquiry, insert_edge).

• "How does an edit fan out notifications?" server/api/edit.py → server/store.py (set_X → _set_field) → server/setter_dispatch.py (RUNTIME_HOOKS[col]) → server/notify.py (post-commit buffer + LISTEN/NOTIFY).

• "How does the schema get built?" server/__main__.py → store.bootstrap() → server/sql.py (schema_migrations()) → server/schema_gen.py (substitute_schema_placeholders()) → the four _generate_* functions. Generated text is derived from ColumnSpec metadata on the dataclasses in types/. See docs/db_schema_migration.md for running migrations, squashing, and deploying schema changes.

• "How does a dependency_changed cascade work?" store.emit_change → store._cascade_dependency_changed → store._parent_edges → types/edges.EdgeKindPolicy. The policy table is the single declaration site for which endpoint of each edge kind is the dependent.

Running

trackinizer                        # pglite (default), with web UI
trackinizer --engine pg --dsn ...  # against real Postgres
trackinizer --no-web               # API only

trax is the client half and talks to any reachable server, so it is useful on its own:

trax help                          # grammar and subjects
trax issue                         # list issues

From a source checkout, both are uv run python -m trackinizer.server and uv run python -m trackinizer.trax.

See example.sh for a worked end-to-end submit/edit/query session.

System dependencies

Integration tests (@pytest.mark.integration) use a Postgres server backend via pytest-postgresql and also requires pgvector.

PGlite bundles its own vector extension, so the default pglite engine has no system deps.

Ubuntu/Debian

# Extension packages are always named `postgresql-NN-<ext>` -- there is no
# unversioned alias -- so derive NN from the metapackage instead of hardcoding
# it (18 above 24.04, 16 on 24.04).
PG_MAJOR="$(apt-cache depends postgresql | grep -m1 -oP 'postgresql-\K\d+')"
sudo apt-get install -y postgresql "postgresql-$PG_MAJOR-pgvector"

macOS

# Homebrew's pgvector supports postgresql@17 and @18.
brew install postgresql@18 pgvector

See also

Sibling projects in the rekursiv-ai family:

• sagent — The self-mutating multi-provider coding-agent CLI and typed Python library.
• wesearch — Web search, resilient page fetch, and scholarly-paper lookup without a browser stack.
• madcatter — Rich-based Markdown renderer for the terminal; ships the mdcat CLI.
• priml — Composable PyTorch building blocks: models, optimizers, losses, and a step-based training loop.
• configgle — Hierarchical experiment configuration in typed pure-Python dataclasses instead of YAML.
• copybarista — Bidirectional source sync for publishing OSS-ready trees from a monorepo.
• sudoku — Sudoku-Extreme solved end to end with a 7M-parameter recursive transformer.

Citing

If you find our work useful, please consider citing:

@misc{rekursivai2026trackinizer,
      title={Trackinizer - Epistemological database for agent and human efforts, beliefs, and findings.},
      author={Joshua V. Dillon and Dan Kondratyuk},
      year={2026},
      howpublished={Github},
      url={https://github.com/rekursiv-ai/trackinizer},
}