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RAC — lint and diff product requirements written in Markdown.

Project description

Lore

Lore — agents that know why. Deterministic. Read-only. No RAG, no guessing.

Quickstart · How it compares · How it works · Docs · CLI · Changelog

CI PyPI Python Typed License: Apache 2.0

Give your coding agent the decisions your team already made — so it stops re-doing things you ruled out.

Lore keeps your team's recorded knowledge — requirements, decisions, designs, roadmaps, and prompts — as typed Markdown in your repo and serves it read-only to Claude Code, Cursor, and Claude Desktop over MCP, so the agent cites your decisions instead of violating them. No RAG, no embeddings, no model call to decide what's relevant — retrieval is deterministic and reproducible. It is built on RAC — Requirements as Code, the open-source engine underneath; the package, CLI, and MCP server ship under the rac name.

How it compares

Lore isn't a search index or a memory tool — it's the deterministic system of record an agent grounds against. Fuzzy retrieval (RAG, agent memory) is good at finding what's near a loose question; Lore is good at returning the exact, current decision and declining the ones you've superseded. They compose well — recall fuzzily, then verify in Lore.

Lore Fuzzy retrieval (RAG / agent memory)
Good at the exact, current decision finding what's near a question
Retrieval deterministic, reproducible similarity-ranked, varies by run
Role source of truth, read-only a fast index or working copy
In CI enforced (rac validate / rac gate) not its job

Quickstart

  1. Install the engine:

    pip install rac-core
    
  2. Scaffold identity and your first artifact:

    rac quickstart
    
  3. Connect your agent (Claude Code, from your repo root):

    claude mcp add lore -- rac mcp
    
  4. Enforce in CI so bad knowledge never lands:

    rac validate rac/ && rac gate rac/
    

Install

Command Gets you
pip install rac-core the rac CLI + the lore MCP server
pip install 'rac-core[ingest]' + DOCX / HTML import
pip install 'rac-core[ingest-all]' + PDF / PPTX / XLSX import
pip install 'rac-core[explorer]' + the terminal Explorer (rac explorer)

Requires Python 3.11+. uv tool install rac-core also works.

How it works

How Lore works: typed Markdown in your repo flows through the deterministic rac engine into the read-only lore MCP server, which serves your agent.

  • Typed Markdown, in your repo. Every artifact is plain Markdown with a tiny frontmatter envelope; the engine classifies it deterministically and validates it against a per-type schema.
  • Read-only at serve time. The MCP server only ever reads; the trust boundary is human PR review, and the agent cannot mutate the store.
  • Enforced at write time. rac validate and rac gate reject malformed artifacts, broken or ambiguous links, and references to superseded decisions — in CI, before the knowledge lands.
  • Air-gapped by design. The engine makes no LLM calls and no network calls; the only egress is a consent-gated, content-free usage ping that is off by default, and regulated installs can prove it stays off with rac telemetry off --enterprise (security posture, ADR-086).

Connect your agent

Claude Code (from your repo root):

claude mcp add lore -- rac mcp

Claude Desktop / Cursor (mcpServers in the client config):

{
  "mcpServers": {
    "lore": { "command": "rac", "args": ["mcp", "--root", "/absolute/path/to/your/repo"] }
  }
}

Author and enforce artifacts

rac quickstart             # set up identity + scaffold your first artifact
rac new decision adr.md    # scaffold a typed artifact (mints the id)
rac validate rac/          # check every artifact in a directory
rac inspect requirement.md # see its type and completeness
rac review rac/            # full repository review, worst problems first
rac gate rac/              # the merge gate: validate + relationships + review

Import an existing decision

Already have decisions in Confluence, Notion, or loose Markdown? The rac-import agent skill turns one existing document into one valid artifact, with a human-review step before anything is written:

rac skill install rac-import

Then ask your agent, in plain language: "import this decision doc into Lore." It drafts from only what your document says, shows you the proposed type, title, and relationships to confirm, scaffolds with rac new, and closes on rac validate. For multi-format or bulk conversion, use the rac-ingest skill.

Export the corpus

rac export rac/ --html --out lore.html   # the Portal: the whole graph, one file
rac export rac/ --okf                    # a conformant Open Knowledge Format bundle
rac export rac/ --documents              # JSONL for memory/RAG backends
rac export rac/ --graph                  # the typed decision graph for graph backends

The --documents and --graph modes feed external memory, RAG, and graph tools so an agent can recall fuzzily there and then verify in Lore — see the CLI reference. The connectors themselves live in the separate lore-connectors companion.

Python API

The engine is a library too; its public surface is rac.__all__.

from rac import parse_file, classify, find_artifacts

art = parse_file("rac/decisions/adr-001-markdown-first.md")
print(classify(art).type)                  # -> "decision"

result = find_artifacts("rac/", "caching")  # returns a SearchResult
for hit in result.matches:
    print(hit.id, hit.title)

How it relates to OKF

Google's Open Knowledge Format (OKF) standardises the carrier — a Git tree of Markdown with YAML front matter — and is deliberately permissive. RAC writes that same carrier and adds what OKF leaves to the consumer: write-time enforcement in CI. rac validate and rac relationships --validate reject malformed artifacts, broken links, and references to superseded decisions, deterministically, before the knowledge lands. rac export --okf turns any RAC repo into a conformant OKF bundle — so the two compose rather than compete.

Who it's for

  • Teams running coding agents heavily (Claude Code, Cursor) tired of the agent ignoring decisions the team already made.
  • Teams who already write ADRs and want those decisions to actually shape what the agent does.
  • Anyone who wants the why behind their software versioned alongside the code.

Documentation

Full documentation: https://itsthelore.github.io/rac-core/

Origin

Lore is the product surface of RAC — Requirements as Code, the open-source engine underneath; the package, CLI, and MCP server ship under the rac name, and lore is the server identity and brand. Wayfinder, the deterministic prompt-complexity router, began as a route experiment inside RAC and was split into its own tool — routing is a runtime concern, not a knowledge one.

Repository layout

rac-core/
  src/rac/        the engine: CLI, core, services, output, the in-process MCP
                  server (rac mcp), and bundled skills, templates, and git hooks
  rac/            the dogfood corpus — requirements, decisions, designs, roadmaps,
                  and prompts that govern the project itself
  tests/          per-service batteries plus core / cli / artifacts coverage (ADR-027)
  docs/           the documentation site (MkDocs)
  examples/       the grounding demo, woven into the corpus and the test fixtures
  rac-localview/  the Portal / graph viewer, vendored into the engine

Test

pip install -e .[dev]
python -m pytest

ruff check, ruff format --check, and mypy src/ run in CI alongside the per-service batteries (ADR-027).

Project status

Lore is early and evolving quickly. The MCP server ships today. Contributions, ideas, and experiments welcome — see CONTRIBUTING.md.

License

Apache License 2.0.

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