189 lines
13 KiB
Markdown
189 lines
13 KiB
Markdown
# Architecture Decision Records
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A running log of decisions and *why*. Format per entry: Context · Decision · Rationale ·
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Alternatives rejected · Status. Newest decisions extend the log; supersede rather than delete.
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---
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## ADR-001 — Two memory types, kept as separate systems
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- **Context**: Earlier attempts to make one tool serve both "what happened" and "how do we do
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X" felt forced (e.g. trying to make memsearch filter knowledge by tags).
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- **Decision**: Model **episodic** memory and **semantic/knowledge** memory as two separate
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systems with different tools.
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- **Rationale**: They have different lifecycles (episodic accretes and decays; knowledge is
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deliberately maintained), different write paths (auto-captured vs curated with guardrails),
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and different query patterns ("when did we…" vs "how do we…"). Separation dissolves the
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earlier integration tension entirely.
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- **Alternatives rejected**: One unified store (memsearch-for-everything, or OpenBrain's single
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`thoughts` table) — conflates the two and forces awkward filtering.
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- **Status**: Accepted.
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## ADR-002 — memsearch for the episodic layer
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- **Context**: Need timeline/"what happened" memory (Goal 3) that's NL-queryable and lazy.
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- **Decision**: Adopt **memsearch** (Zilliz) off-the-shelf for episodic memory.
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- **Rationale**: It already implements the OpenClaw daily-notes + "dreaming" pattern and the
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markdown-as-truth / disposable-shadow-index philosophy we'd otherwise build. Embedded
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**Milvus Lite** (single file), hybrid BM25+vector+RRF search, local ONNX embeddings (no API
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key/cost), a FileWatcher that handles deletions — **no Docker, no server**. Two-line install.
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- **Alternatives rejected**: claude-mem (MCP-based — Claude must actively call search; opaque
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blobs vs readable markdown; overkill features). Hand-building daily notes + dreaming
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ourselves (reinventing a solved tool).
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- **Status**: Accepted.
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## ADR-003 — Flat vault with namespaced tags, not folders
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- **Context**: Connelly/Huryn organize by folders (`tools/`, `domain/`). User wants a flat
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Obsidian vault with tags as virtual indexes, and cross-cutting filters (client × tool ×
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convention).
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- **Decision**: One **flat markdown vault**; organize via **namespaced, nested tags**
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(`tool/`, `client/`, `domain/`, `convention/`, `scope/`). Slashes are valid Obsidian nested
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tags, so `#tool` matches all children.
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- **Rationale**: A note can carry several namespaces at once (`tool/semrush` +
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`client/sesame3g` + `convention/react-ts`) — folders can't express that. Enables "filter by
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client+tool to narrow the index." Enumerable virtual indexes ("what clients/tools exist").
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- **Alternatives rejected**: Folder hierarchy (single-axis; can't do cross-cutting filters).
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Pure-prefix path filtering via memsearch `source_prefix` (would force directories back in).
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- **Trade-off accepted**: Tags give the *human/Obsidian* free filtering, but the *AI* gets
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nothing for free from tags — we must materialize them into a queryable index (see ADR-004).
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- **Status**: Accepted.
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## ADR-004 — SQLite + Sequel (Ruby) tag index as the knowledge-layer cache
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- **Context**: The AI can't use Obsidian tags directly; tag filtering needs a machine-queryable
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index. A previous `~/Documents/SecondBrain/` tag database was lost track of.
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- **Decision**: A small **Ruby program using the Sequel ORM over SQLite**, exposed as a **CLI**.
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Schema: `files(path, mtime, summary, scope)`, `tags(name)`, `files_tags` join
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(`many_to_many`). The summary is a **column on `files`** (an attribute), not a join.
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- **Rationale**: Normalized `tags` table makes enumerating the vocabulary a first-class cheap
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query (the "virtual index" goal). The `summary` column is what turns the index from a
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*finder* into a *router* — the AI sees enough to pick a file without opening it (progressive
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disclosure, low tokens). Ruby + Sequel + CLI keeps the contract clean and the DB swappable;
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the AI never touches SQLite directly.
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- **Failure-mode guard (the lost-SecondBrain lesson)**: **markdown is always authoritative; the
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SQLite file is a disposable cache** that is never synced and can be rebuilt from frontmatter
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anytime (`index update --rebuild`).
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- **Alternatives rejected**: Plain-markdown generated `INDEX.md` (must regenerate; grep-at-scale
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is token-heavy). Frontmatter grep on demand (scales badly). Milvus/Postgres for knowledge
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(overkill; QMD/memsearch prove SQLite is enough — see ADR-006/008).
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- **Query output**: returns **path + summary + matched tags** (option C) — tags are cheap and
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show *why* a result matched, useful for cross-client queries.
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- **Status**: **Superseded by ADR-010** (Graphify replaces the Ruby/SQLite tag index). The
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`summary` + namespaced-tag frontmatter this ADR introduced is **retained as note metadata**;
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only the bespoke Ruby/SQLite index and its CLI are dropped.
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## ADR-005 — Structured-first; semantic search over the vault deferred
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- **Context**: Tag filtering ("client/sesame3g + tool/semrush") may miss notes whose wording
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doesn't match the query ("how do we use semrush" vs a note titled "search analytics
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integration").
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- **Decision**: Ship the knowledge layer **structured-only** (tags + summaries). **Defer**
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meaning-based search over the vault until it demonstrably bites.
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- **Rationale**: Structured tagging is the lightweight/fast thing the user wants, and the
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summary+tag design is built to make it work. Follow the video's "only level up when it bites."
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- **Status**: **Superseded by ADR-010.** The premise (ship structured-only, bolt on semantics
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later) no longer holds: Graphify makes the knowledge layer a graph from day one, giving
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structured *and* connection-based recall together. The "only level up when it bites" instinct
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carries forward to whether a *vector* layer is ever needed on top of the graph.
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## ADR-006 — QMD as the (deferred) semantic-over-knowledge layer
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- **Context**: When ADR-005's structured-only proves insufficient, we want a set-and-forget
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semantic layer over the vault, local and Docker-free.
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- **Decision**: Earmark **QMD** (github.com/tobi/qmd) for that role; do **not** install yet.
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- **Rationale**: Local markdown search using **SQLite + FTS5/BM25 + local vector embeddings
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(EmbeddingGemma-300M GGUF) + LLM rerank**; CLI + optional **MCP server**; no Docker, no API
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keys. Validates that SQLite + a local vector model suffices (no Milvus/Postgres for
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knowledge). Complements the tag index (QMD filters by path/collection context, not
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first-class frontmatter tags), so it adds semantic recall without replacing structured
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filtering.
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- **Alternatives rejected**: Pointing memsearch at the vault (mixes episodic and knowledge
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corpora; its filtering is path-prefix not tags). A bespoke embedding index (reinvents QMD).
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- **Status**: **Superseded by ADR-010.** Graphify's knowledge graph fills the
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semantic-recall role (traversal/`explain` over connections) without a separate vector system,
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so QMD is no longer earmarked. Revisit a vector layer only if graph traversal demonstrably
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misses cases where embedding similarity would win.
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## ADR-007 — Lazy freshness: write-hook + session-start reconcile, no daemon/cron
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- **Context**: The cache must reflect new/edited/deleted/renamed notes without becoming a
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resource hog or going stale on renames.
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- **Decision**: **Option A (lazy).** A `PostToolUse` hook updates the index on **AI** writes
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(single-file, prunes on delete). **Manual** edits are caught by a **session-start reconcile**
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(`index update --since` + prune of vanished paths). **No daemon, no cron.**
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- **Rationale**: The AI is the primary writer, so write-time hooks give event-driven freshness
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with no polling. The user rarely edits the vault by hand, so a session-start reconcile is
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enough; a continuous `inotify` daemon (the `listen` gem) would add an always-on process to
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manage/sync for negligible benefit. Matches the user's "lazy sync is fine" stance.
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- **Alternatives rejected**: `inotify`/`listen` daemon (live freshness, but always-on process
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to manage — unnecessary). Cron reconcile ("seems silly" per user; session-start covers it).
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- **Status**: Accepted.
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## ADR-008 — Markdown-as-truth; sync the vault, not the indexes
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- **Context**: Must be accessible on a VPS / multiple machines but run local-fast (Goal 4).
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- **Decision**: Sync the **markdown vault** to the VPS via **git or Syncthing** (choice deferred
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to build time). **Graphs/indexes (Milvus Lite, Graphify `graphify-out/`) are rebuilt per
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machine and never synced.**
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- **Rationale**: Markdown is plain text — git/Syncthing sync it trivially; lazy (hourly or
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continuous-async) is enough. Indexes are disposable caches; syncing binary DBs invites
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conflicts for no gain. Local reads stay fast; ownership and portability stay with the user.
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- **Alternatives rejected**: **OpenBrain / Mem0** hosted DBs — always-remote, adds per-query
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latency and monthly cost, conflicts with local-fast; ownership weaker (Mem0 especially).
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Only worth it for real-time cross-tool memory, which the user called overkill.
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- **Status**: Accepted.
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## ADR-009 — Package as a global Claude Code plugin with skills
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- **Context**: Every project, on every machine, should know how to use the vault — write
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conventions, query patterns, the hooks, and the CLI — without per-project setup.
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- **Decision**: Ship hooks + scripts + CRUD know-how as a **global Claude Code plugin with
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skills**, installed at the user level.
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- **Rationale**: Skills carry the "when to write / what conventions / how & when to query"
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guidance to the model; the plugin registers the session-start / session-end / PostToolUse
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hooks and wires up Graphify (extraction/update/query + MCP server). Global install =
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consistent behavior everywhere; single source of truth for the conventions themselves.
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- **Status**: Accepted (to be built — see 04-build-plan.md).
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## ADR-010 — Graphify knowledge graph as the knowledge layer (supersedes ADR-004/005/006)
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- **Context**: ADR-004 specced a hand-built Ruby/Sequel/SQLite tag index (+ CLI) as the
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machine-queryable layer over the vault, with ADR-005/006 deferring meaning-based recall to a
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future QMD vector layer. Before building any of it, we evaluated **Graphify** (`graphify`,
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PyPI `graphifyy`) — a tool that turns a folder into a queryable knowledge graph (local
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tree-sitter AST for code, local-SLM entity/relationship extraction for docs). See
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`06-graphify-evaluation.md`.
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- **Decision**: Use **Graphify as the knowledge-layer engine** over the vault, with a **local
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Ollama** backend for doc extraction and free AST for per-project code graphs. **Drop** the
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Ruby/SQLite tag-index CLI (ADR-004) and the earmarked QMD layer (ADR-006); **retain** the
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`summary` + namespaced-tag frontmatter from ADR-003/004 as note metadata.
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- **Rationale**: One off-the-shelf tool delivers both what the tag index was for (structured
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retrieval) and what QMD was deferred for (connection/meaning-based recall via graph
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traversal + `explain`) — without writing or maintaining a bespoke index, and without a vector
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store. Code graphs come free. Keeps the markdown-as-truth, no-Docker, no-API-key, local-first
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properties (extraction runs against local Ollama). Net scope reduction: the entire Ruby build
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(old critical-path Step 2) and the QMD layer are removed.
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- **What's retained / changed**: `summary` stays the human-written router hint Graphify does not
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generate; namespaced tags stay useful for Obsidian filtering and as node attributes. How
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tightly metadata should feed graph queries is a **build-time refinement**, not settled here.
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- **Trade-off accepted**: Graphify's `--update` doesn't prune deleted nodes (stale-node drift) —
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mitigated by a periodic `--force` rebuild on the session-start staleness check (ADR-007's lazy
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model still applies). Graphify also moves fast (flags are version-dependent; anchored to
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v0.8.30) and its headline token-savings numbers are corpus-dependent — benchmark our own.
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- **Alternatives rejected**: Building the Ruby/SQLite index as originally planned (more code to
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own; no semantic recall); adding QMD as a second system on top (two stores where one graph
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suffices).
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- **Status**: Accepted (to be built — see 04-build-plan.md and 06-graphify-evaluation.md).
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## Rejected tools (summary)
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| Tool | Why rejected for our use |
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| MemPalace (L4) | Storage not readable markdown; isolated drawers (knowledge not interconnected); fights self-managing + cross-linking goals |
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| Recall / LightRAG (L5) | Content knowledge bases / deep research, not operational memory; Recall = hosted, you don't own data; LightRAG = enterprise overkill |
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| OpenBrain / Mem0 (L6) | Always-remote DB → latency + cost; conflicts with local-fast lazy-sync; only pays off for real-time cross-tool memory (user: overkill) |
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| Postgres / Milvus server | Unnecessary — Graphify's local graph (knowledge) + Milvus Lite (memsearch episodic) cover everything locally with no Docker |
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| claude-mem | MCP-based (Claude must call search); opaque blobs vs readable markdown; feature overkill |
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| Ruby/SQLite tag index CLI; QMD vector layer | Superseded by Graphify before build — one knowledge graph replaces both the structured index and the deferred semantic layer (ADR-010) |
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