Initial M4 mapping put wiki/entities/* in tier=note. Post-M4 eval
regressed qwen35-9b-fast from rank 2 → off top-5: knowledge entries
that cite the entity in passing now outscore the entity page itself
(1.5× weight vs 1.0×).
Entity anchor pages are durable facts about concrete things — they
map cleanly to the knowledge/facts/ slot in the post-M3 layout
target. Promote them now so the path inference matches.
Eval re-run after deploy is in infra#72.
The eval set under brain/eval/qa-2026-05.md showed BM25 top-1 at 20%
with 5 of the missing slugs being short focused knowledge entries
that lost to long aggregate docs on raw term-frequency. Tier weighting
addresses that without touching the BM25 algorithm itself.
How
- Result struct gains a Tier field, populated during the file walk
via extractTier (frontmatter wins, path prefix as fallback —
mirrors the graph.inferTierFromPath logic so the two callers stay
in lockstep).
- After the existing sort (and optional hybridMerge), do a final
stable re-sort by float64(Score) * tierWeight(Tier). Knowledge
×1.5, note ×1.0, inbox ×0.3, unknown ×1.0.
- hydrate() (vector-only hits) also fills Tier so re-ranking covers
the hybrid path.
Test covers the load-bearing case: a long note-tier doc with raw=10
loses to a short knowledge-tier doc with raw=8 after weighting
(8×1.5=12 vs 10×1.0=10).
Measurement gate is in infra#72: re-run brain/eval/score.py against
the live brain after this image lands; close the issue when top-1
hit rate lifts by ≥10 absolute points.
extract.go now reads `tier:` and `topic:` from YAML frontmatter, with
a path-based fallback when frontmatter is absent (the pre-M3 state on
every existing entry):
knowledge/* → tier=knowledge
notes/* → tier=note
wiki/** → tier=note (sources + concepts + entities are I-level)
inbox/**, raw/**, sessions/**, clips/** → tier=inbox
Frontmatter wins when present — covers the M3-migrated case where an
entry's path may not match the tier the author chose for it.
UpsertEntity persists both columns. M1's schema already has them.
Backfill on next pod start populates tier for the whole corpus
without any file moves; M3 will follow up with the actual layout
migration and explicit frontmatter writes.
Schema-only change. DDL adds tier + topic on fresh tables and uses
ADD COLUMN IF NOT EXISTS on existing tables (idempotent across pod
restarts). New conditional indexes match the wing/hall pattern.
No behavior change in this commit — UpsertEntity still writes only
the original columns; tier + topic stay '' on every row. M2 plumbs
the parser through. The empty default means existing queries are
untouched until the rest of the chain lands.
Part of infra#72 — brain DIKW tier redesign.
classifyByPath had a hole: paths like wiki/index.md or wiki/<slug>.md
(direct children of wiki/, no subdirectory) hit the default branch and
wrote Wing=parts[1] — which IS the filename, not a wing. Symptom in
brain_entities: rows like (slug=index, wing=index.md) and
(slug=autobe-..., wing=autobe-evaluation-pattern-....md).
Fix: when len(parts) < 3 (no subdirectory at all), fall through to
Type=knowledge and let frontmatter set wing/hall if present.
Add brain/eval/ artifacts at the same time:
- qa-2026-05.md — 20 hand-authored Q→expected-slug pairs covering the
homelab knowledge corpus across mcp, dex, gitops, postgres, go,
models, methodology
- score.py — calls brain_query for each pair, scores top-1 + top-3,
emits per-question detail. BRAIN_MCP_TOKEN via env.
Pre-fix baseline against the live brain: top-1 = 20% (4/20),
top-3 = 65% (13/20). Six hard misses where the expected slug doesn't
even land in the top-5.
Used to gate the phase 2 DIKW redesign (infra#62 follow-up): if
phase 1 fixes (this parser fix + 20 backlink authoring on top
orphans) lift top-1 by <10 absolute points, structure is the
bottleneck and the tier redesign is justified.
Commit 4 of Track A — the no-shelfware close-out the grill demanded.
brain_answer now folds the 1-hop outgoing neighbourhood of its top
BM25/rerank hit into the LLM's context as a <related> block when
BRAIN_GRAPH_ENABLED is on. With the flag off the prompt is byte-for-
byte identical to the pre-Track-A behaviour, so existing tests still
pass without modification.
The hop list contains slug, edge_type, doc_path — no extra retrieval
pass, no second LLM call, no file reads. The model can ignore the
block when irrelevant; when it adds signal we get GraphRAG for free.
Refs: docs/superpowers/specs/2026-05-homelab-training-graph-next-step.md
in infra repo + grill addendum item "Track A: GraphRAG wiring into
brain_answer is mandatory in same commit chain (no shelfware risk)".
Co-Authored-By: Claude Opus 4.7 (1M context) <noreply@anthropic.com>
Commit 3 of Track A. The MCP server now publishes a new tool that
opens the brain knowledge graph (entities + wikilink edges) for
external consumers (claude.ai connectors, gitea-mcp, agentsquad).
- tools_graph.go: brain_graph handler dispatches by op:
neighbors — 1-hop outgoing from slug, optional edge_type filter
subgraph — every reachable slug within depth hops (≤6)
path — shortest directed path src→dst within depth (≤8)
Returns slug + entity metadata + edge_type + hop distance.
- server.go: handleCall routes "brain_graph" to brainGraph.
- handlers.go: tool descriptor with the op enum + per-op required
fields documented in the description.
- server_test.go: TestServerToolsList expects brain_graph in the
listing.
The tool returns an error when BRAIN_GRAPH_ENABLED is unset — same
shape as brain_answer when the answer LLM is unconfigured.
Co-Authored-By: Claude Opus 4.7 (1M context) <noreply@anthropic.com>
Commit 2 of Track A. Service stays a no-op until BRAIN_GRAPH_ENABLED=
true; flipping it on creates the schema (idempotent), starts indexing
every successful write, and optionally backfills the existing brain
dir.
- internal/graphsync: best-effort wrapper around graph.Extract +
graphstore. IndexDoc reads docPath under brainDir, parses, upserts
entity + replaces edges. BackfillFromBrainDir walks wiki/ +
knowledge/. Both are no-ops on nil store so callers wire
unconditionally.
- mcp.Server gains WithGraph builder + graphsync.Store field.
brain_write, brain_ingest, brain_ingest_raw, brain_tunnel call
indexInGraph after success — failures slog.Warn but never
propagate (graph is augmentation, not correctness).
- cmd/server gates the wiring on BRAIN_GRAPH_ENABLED=true (default
off so first rollout doesn't surprise). BRAIN_GRAPH_BACKFILL=true
triggers a one-shot walk of the brain dir on boot.
Co-Authored-By: Claude Opus 4.7 (1M context) <noreply@anthropic.com>
Foundation for Track A (GraphRAG on top of existing wiki). Two new
packages, both unwired — service behaviour unchanged until commit 2
hooks the pipeline.
- internal/graph: pure parser. Extract() walks markdown + frontmatter
and emits one Entity + N wikilink Edges per doc. Dedupes per (dst,
line), ignores self-references, classifies hall/concept/entity/
source/knowledge from path layout.
- internal/graphstore: pgx-backed PGStore mirroring vectorstore's
shape. Idempotent Init() creates brain_entities + brain_edges with
indexes on src_slug, dst_slug, src_doc, wing, type. Operations:
UpsertEntity, ReplaceEdgesForDoc (tx), DeleteByDoc, Neighbors,
Subgraph (recursive CTE, depth ≤6), Path (shortest path, depth ≤8).
Schema lives on the shared postgres18 instance alongside the
brain_embeddings table — no new datastore. See
docs/superpowers/specs/2026-05-homelab-training-graph-next-step.md
in infra repo + infra#62.
Co-Authored-By: Claude Opus 4.7 (1M context) <noreply@anthropic.com>
Second port of the MCP chassis (gitea-mcp was first, commit 658f4ba).
Closes the chassis-adoption loop on the two highest-LOC consumers.
Changes:
- Drop ingestion/internal/auth/ entirely (jwt.go + jwt_test.go +
protected_resource.go + protected_resource_test.go) — chassis provides
JWTValidator + ProtectedResourceHandler with identical semantics.
- Drop ingestion/internal/mcp/auth.go (BearerAuth function, ~65 LOC)
and the integration test auth_test.go (~200 LOC) — chassis
BearerMiddleware replaces it. Static-Bearer-or-Dex-JWT precedence and
RFC 9728 resource_metadata challenge behavior preserved 1:1.
- cmd/server/main.go: import chassis as `chassisauth`, rewire the three
call sites. Use realm="brain" in the BearerMiddleware call so a 401
challenge identifies the resource as the brain MCP.
OAuth client_credentials handler (ingestion/internal/oauth) stays —
chassis v0.1.0 covers only the JWT path; OAuth flow is a candidate for
chassis v0.2.0 once a second MCP needs it (rule of three).
Net delta: -~330 LOC of duplicated auth code; +1 import; +1 GOPRIVATE
env requirement on dev machines (documented in the spike handoff
2026-05-22-mcp-chassis-spike.md).
task check green (lint + test + vet + govulncheck).
Co-Authored-By: Claude Opus 4.7 (1M context) <noreply@anthropic.com>
Closes infra#50.
Adds an internal/metrics package with a hand-rolled Prometheus
exposition layer (stdlib + sync/atomic only — no new dep) and wraps the
HTTP mux with a timing middleware. Every request emits one observation
on the `brain_query_duration_seconds` histogram labeled by
`path` (request Pattern, low cardinality) and `status` (2xx/3xx/4xx/5xx).
Dependency choice: hand-rolled rather than github.com/prometheus/client_golang
because the surface needed is small (one histogram + bucket constants)
and the repo CLAUDE.md keeps deps stdlib + jwx + testify only. ~150 LOC
of code + tests is cheaper than the chart of transitive prometheus deps.
Endpoints:
- GET /metrics — OpenMetrics text exposition, no auth (cluster-internal)
Wire format pinned by tests in internal/metrics/metrics_test.go. The
ServiceMonitor that drives the kube-prometheus-stack scrape lives in
infra/k3s/apps/supervisor/ (separate commit on mathias/infra).
After this image deploys, the canary alert from
docs/superpowers/specs/2026-05-homelab-architecture-review.md becomes
wireable:
histogram_quantile(0.95,
sum(rate(brain_query_duration_seconds_bucket[5m])) by (le))
> 1.5 * histogram_quantile(0.95,
sum(rate(brain_query_duration_seconds_bucket[5m] offset 7d)) by (le))
Co-Authored-By: Claude Opus 4.7 (1M context) <noreply@anthropic.com>
Removes the TODO in Sync that left files static after their first embed.
Edits to brain/wiki/ and brain/knowledge/ now surface in subsequent
syncs without manual /backfill-embeddings calls.
Approach
- Store interface: KnownPaths → KnownPathsWithTime returning path →
updated_at. Callers compare against file mtime to detect edits.
- PGStore: SELECT path, updated_at FROM brain_embeddings.
- Sync groups known chunks by parent path and tracks the EARLIEST
updated_at per parent. A file is stale when its mtime is after that
oldest chunk's timestamp — any chunk older than the file means at
least one chunk hasn't been refreshed since the last edit.
- Stale-path rewrite: delete every old chunk for the parent (handles
"file shrunk → fewer chunks → orphan rows at higher #NNNN" cleanly),
then re-chunk + re-embed + re-upsert.
Tests
- New: TestSync_ReembedsFileWhenMtimeNewer — file mtime forced into the
future vs store updated_at; Sync deletes old chunk + upserts fresh one.
- New: TestSync_SkipsFileWhenMtimeOlder — file mtime backdated; Sync is
a no-op (no upserts, no deletes).
- Updated: stubStore.known is now map[string]time.Time. A zero value
resolves to a far-future sentinel so existing "skip if already known"
tests keep passing without per-test setup.
- pg_test renamed KnownPaths integration → KnownPathsWithTime; asserts
updated_at is non-zero and within 5s of insert wall-clock.
Backward compat
- brain_embeddings rows pre-dating this change carry valid updated_at
values (column was always populated via `DEFAULT now()` + ON CONFLICT
`updated_at = now()`). No migration needed. Live pod will start
re-embedding any file whose source has been edited since its chunks
were originally written.
Closes gitea/mathias/hyperguild#23.
Long markdown files (>~8KB) silently failed to embed because nomic-embed-text
on iguana has a 2048-token context. embed sync logged errors=1 every cycle
with no useful body until #37 added per-item logging — three files exceed
the ceiling: finbert source (8 KB), koala-machine-state (7.1 KB),
litellm-absorption (8.8 KB). Curated knowledge entries should never be
vector-blind.
Approach: chunk-before-embed, no schema change.
vectorstore/chunk.go (new)
- ChunkMarkdown splits at H1/H2 boundaries; sections over maxBytes are
further split at paragraph boundaries, packing greedily under budget.
- NumberChunks assigns "<parent>#NNNN" storage paths (1-based, zero-padded
to 4 digits — handles files with up to ~10k sections in stable sort order).
- ParentPath strips the chunk suffix for retrieval-side dedup.
vectorstore/sync.go
- After ChunkMarkdown produces N pieces, each is embedded + upserted as a
separate brain_embeddings row at "<parent>#NNNN". maxChunkBytes = 4000
(≈1000 nomic tokens, well under the 2048 ceiling with headroom for
unicode/code blocks).
- "Already embedded?" check now reduces known paths to parent set via
ParentPath, so the first chunk hit short-circuits the file.
- Delete walk also reduces via ParentPath; when a parent file disappears,
every chunk row (and any pre-existing bare-path row, for backward
compatibility with rows written before this change) gets dropped.
search/search.go
- hybridMerge collapses chunk-path vector hits to parent via ParentPath
before scope check, RRF accumulation, and hydration. A file with three
chunk hits returns one result row, not three.
Backward compatibility: pre-existing bare-path rows in brain_embeddings
keep working — ParentPath returns them unchanged, knownParents handles
them as if they were "wiki/foo.md#NNNN" hits, sync skips re-embed, and
search dedup is a no-op for them. No migration required to ship.
Tests:
- chunk_test.go covers short / heading split / oversized section /
content preservation / chunk numbering / parent-path stripping.
- sync_test.go adds long-file chunking, single-chunk-row short file,
skip-if-any-chunk-known, delete-all-chunks-of-disappeared-file.
Existing tests updated for #NNNN paths.
- search_test.go adds chunk-paths-dedupe-to-parent.
Closes gitea/mathias/infra#38.
The embed sync goroutine only walked brain/wiki/. brain/knowledge/ (112
curated entries, per CLAUDE.md the most-important brain content) had zero
coverage in brain_embeddings — vector retrieval was blind to it. Hybrid
BM25 + pgvector retrieval would never surface a curated knowledge entry
via the vector arm.
Extract the per-root walk into a loop over a small subdir list and add
"knowledge" alongside "wiki". scanDirs is package-level so it stays a
single source of truth for what gets embedded.
Also log each failing item's path + error string from StartSync.
Previously only the aggregate count was logged, so a persistent
`errors=1` per cycle was opaque. With per-item warnings, the actual
ollama "input length exceeds the context length" surface immediately.
Refs gitea/mathias/infra#37 (this commit covers the knowledge/ scan
bug; the long-file chunking bug is a separate change.)
Wires nomic-embed-text (iguana ollama) + pgvector on the shared
postgres18 into brain_query / brain_answer via Reciprocal Rank Fusion.
Pure BM25 stays the default; setting BRAIN_PG_DSN and BRAIN_EMBED_URL
together opts in. Setting one without the other is misconfiguration →
exit 1.
New packages:
- internal/embed
Client.Embed(ctx, text) → []float32 via POST {URL}/api/embed.
Defaults to nomic-embed-text:latest (768 dim). nil-on-empty-URL so
callers gate on a single nil check.
- internal/vectorstore
PGStore wraps a pgxpool against postgres18. Init creates
brain_embeddings(path PK, vector(768), updated_at) + HNSW cosine
index idempotently. Upsert / Delete / Search / KnownPaths.
Sync(brainDir, store, embedder) diffs brain/wiki/ against the store
and upserts new files / deletes removed ones; StartSync runs it on
a ticker (default 300s). Integration tests gated by BRAIN_PG_TEST_DSN.
- scripts/brain-embeddings-init.sql
One-time DBA setup: brain DB, brain_app role, vector extension,
GRANTs. Idempotent.
Search layer:
- search.QueryOptions gains Vector + Embedder fields.
- QueryContext is the cancellable variant; Query stays for callers.
- When both are set, BM25 (top-N) and pgvector (top-4N) candidates
merge via Reciprocal Rank Fusion (k=60, Cormack et al. 2009 — no
tuning knob, robust to scale differences between rankers).
- Vector-only hits are hydrated from disk so callers see uniform
Result records (path, title, excerpt, wing, hall, score).
- Wing/hall filters still apply to vector candidates via path-prefix.
- On embedder/vector errors the search falls back to BM25 — embedding
outage degrades quality but doesn't take the brain offline.
MCP wiring:
- mcp.Server.WithHybridRetrieval(v, e) opt-in setter, same shape as
WithReranker.
- brainQuery and brainAnswer pass the wired vector/embedder through
to search.QueryContext.
REST:
- POST /backfill-embeddings drives Sync synchronously. Returns
{added, deleted, errors[]}. 503 when feature is unconfigured.
cmd/server/main.go:
- BRAIN_PG_DSN + BRAIN_EMBED_URL together enable hybrid; one alone
→ exit 1.
- vectorAdapter bridges *PGStore (returns []Hit) to
search.VectorSearcher (which takes []VectorHit) without either
package importing the other.
- BRAIN_EMBED_SYNC_INTERVAL (default 300s) controls the background
Sync ticker.
Backend pivot from Qdrant to pgvector recorded in DECISIONS.md
2026-05-18 (supersedes 2026-04-08): postgres18 already runs in
databases/ ns, Qdrant was never deployed, one engine beats two.
Dependency: github.com/jackc/pgx/v5 — modern, native pgvector via
parametric vector literals.
Tests:
- embed.Client: empty-URL nil, request shape, dimension, upstream
error propagation, empty-text rejection.
- vectorstore.PGStore: dimension validation (unit); upsert/search/
KnownPaths (integration, BRAIN_PG_TEST_DSN-gated).
- vectorstore.Sync: adds new files, skips known, deletes
disappeared, skips _index.md, no-op when nil, collects embedder
errors.
- search.Query: hybrid promotes vector-only hits via RRF; falls
back to BM25 on embedder error.
Closes hyperguild#8.
Adds an opt-in cross-encoder rerank step between BM25 retrieval and LLM
synthesis. With BRAIN_RERANKER_URL set, brain_answer retrieves BM25
top-20, scores each excerpt against the query via Qwen3-Reranker on
Ollama, drops the "no" answers, and forwards up to 5 surviving sources
to the LLM. Unset, behaviour is unchanged (BM25 top-10 → LLM).
The reranker is a *filter*, not a re-ranker: Qwen3-Reranker emits a
binary yes/no token under its native chat template, and ties within the
"yes" set are broken by BM25 rank — what got retrieved first stays
ahead.
New package ingestion/internal/reranker:
- Client with URL, Model, HTTP fields.
- New(url, model) returns nil on empty url so callers can treat
"feature disabled" as a single nil check.
- Score(ctx, query, docs) issues one /api/generate call per doc using
the Qwen3-Reranker yes/no chat template (verbatim, because the model
was trained on this exact wording). Parses the first non-think token.
Wiring:
- mcp.Server gains a WithReranker fluent setter to keep NewServer
signature stable.
- brain_answer's BM25 limit jumps to 20 only when a reranker is wired,
to give the filter something to do.
- cmd/server/main.go reads BRAIN_RERANKER_URL (+ optional
BRAIN_RERANKER_MODEL, default dengcao/Qwen3-Reranker-0.6B:F16).
Tests cover: nil-on-empty-url, ordered yes/no scoring, request shape
(model, prompt contents, yes/no template), ambiguous response → 0,
empty doc slice, upstream-error propagation, plus an end-to-end
brain_answer integration that proves only the relevant note reaches the
LLM when noise.md is rejected.
Closes hyperguild#7.
Adds a minimal RFC 8414 + RFC 6749 client_credentials flow so claude.ai's
custom-MCP integration (no static-Bearer field in the UI) can exchange a
client_id + client_secret pair for the existing BRAIN_MCP_TOKEN and use
it as a Bearer on /mcp. No JWTs, no refresh, no expiry — the rest of
the auth middleware is unchanged.
New package ingestion/internal/oauth:
- MetadataHandler(issuer): serves /.well-known/oauth-authorization-server
with grant_types=[client_credentials] and both
token_endpoint_auth_methods (post + basic).
- TokenHandler(cfg): serves /oauth/token. Validates client_id and
client_secret via constant-time compare; returns BRAIN_MCP_TOKEN as
access_token. RFC 6749 §5.2 error JSON on bad grant / bad creds.
Wiring in cmd/server/main.go: opt-in by setting both OAUTH_CLIENT_ID and
OAUTH_CLIENT_SECRET. Setting only one is misconfiguration → exit 1.
Mounts both endpoints with no auth; MCP_RESOURCE_URL supplies the
issuer.
Also pivots issue #8's vector backend from Qdrant to pgvector (see
DECISIONS.md 2026-05-18) — Qdrant was never deployed and postgres18 with
pgvector already runs as the project default; supersedes 2026-04-08 for
this use case.
Tests cover post-auth, basic-auth, wrong secret, bad grant, GET
rejection, malformed Basic header, and Basic without colon.
Closes hyperguild#5.
Adds the `brain_tunnel` MCP tool and auto-tunnel behaviour for
`brain_write`, so concepts that appear in multiple wings become
navigable from any of them.
New surface in package brain:
- WriteTunnel(brainDir, src, tgt) — appends a `## See also` bidirectional
wikilink between two notes in different wings. Idempotent (link not
duplicated on re-call) and reuses an existing See also section.
- DetectTunnels(brainDir, content) — walks brain/wiki/, returns
TunnelCandidates for notes whose title appears in content. Tags
whole-word case-insensitive hits as Exact=true and substring-only hits
as Exact=false.
- AutoTunnel(brainDir, src, content) — wraps DetectTunnels: writes
cross-wing exact matches, stages fuzzy matches into
brain/raw/tunnel-candidates-<YYYY-MM-DD>.md for human review.
MCP wiring:
- `brain_tunnel` tool: explicit manual link (source, target).
- `brain_write` with wing+hall now triggers AutoTunnel on the new
content. Failures are logged and never abort the primary write.
readTitleAndCreated also humanises the slug fallback (hyphens → spaces)
so titleless notes participate in content matching.
Closes hyperguild#16.
Tests: idempotency, same-wing rejection, missing-note rejection,
See-also reuse, exact/fuzzy detection, slug fallback, MCP tool happy
path, auto-tunnel hook (cross-wing exact → linked; same-wing → skipped;
fuzzy → candidates file).
Reorders BearerAuth so a valid BRAIN_MCP_TOKEN match wins instantly and
never emits WWW-Authenticate. Adds RFC 9728 resource_metadata challenge
header on 401 (only when MCP_RESOURCE_URL is configured) so claude.ai's
OAuth-discovery path still works.
Why: claude CLI on koala/flamingo with `.mcp.json` `Authorization: Bearer
$BRAIN_MCP_TOKEN` was being kicked into RFC 7591 dynamic client
registration against Dex (static-only) and dying. Cause was the auth
middleware running JWT validation first and emitting an OAuth challenge
on the fall-through 401 even when the caller had a valid static token.
Inverting the precedence and gating the challenge on resourceMetadataURL
keeps the LAN/Tailscale CLI path silent and only invites OAuth discovery
on actually-unauthenticated requests.
Regression guards in the test file:
- valid static Bearer 200 has no WWW-Authenticate
- 401 with resourceMetadataURL set carries the challenge
- 401 with empty resourceMetadataURL emits no challenge
Closes hyperguild#9 in code. Live verification (claude CLI on koala
listing brain tools) blocked on ingestion image rebuild + redeploy.
Adds a two-dimensional address (wing, hall) to brain notes. A wing is a
topic domain (e.g. jepa-fx, hyperguild); a hall is one of a closed
vocabulary of memory types (facts, decisions, failures, hypotheses,
sources). Notes route to brain/wiki/<wing>/<hall>/<slug>.md with
wing/hall/created_at YAML frontmatter, making the directory a valid
Obsidian vault.
Changes:
- new package ingestion/internal/brain (NotePath, ValidHalls, Sanitise,
BuildWingIndex, BuildAllWingIndexes)
- api.WriteNote refactored to WriteNoteOptions; wing+hall routes to
brain/wiki/, otherwise falls back to brain/knowledge/ (legacy)
- search.Query → QueryOptions with optional Wing/Hall filtering; Result
carries wing/hall extracted from frontmatter or path segments
- MCP tools brain_write and brain_query gain optional wing/hall params
(hall enum-validated); new brain_index tool regenerates _index.md MOC
- POST /index REST endpoint mirrors brain_index
- brain_write auto-rebuilds the wing's _index.md after a wing+hall write
- scripts/migrate-brain-halls.sh migrates flat brain/wiki/{concepts,entities}/
into the new layout (dry-run by default, --commit applies)
All existing tests pass; new tests cover wing/hall write routing, scope
filtering, invalid hall rejection, _index.md generation, and migration
script paths.
Closes hyperguild#1.
Adds two new LLM-backed MCP tools to the ingestion service:
- brain_answer(query): BM25 retrieval + LLM synthesis → answer + sources
- brain_classify(text): classifies doc into type/title/tags via LLM
Adds llm.Router for primary→fallback routing (berget.ai → iguana).
Wired via BRAIN_LLM_PRIMARY_URL/BRAIN_LLM_FALLBACK_URL env vars;
no-op when unset so existing deployments are unaffected.
Co-Authored-By: Claude Sonnet 4.6 <noreply@anthropic.com>
Adds pass-rate to the CLI README's subcommand block. Updates CLAUDE.md
to note the new /pass-rate endpoint alongside the existing brain
HTTP REST API surface. Updates the session_log MCP tool's
final_status description to reflect the new pass|fail|skip vocabulary
introduced by Plan 5's SKILL.md instrumentation; the aggregator
still accepts legacy ok|error|skipped values for backwards compat.
Adds a new HTTP GET handler at the ingestion pod that walks
brain/sessions/*.jsonl, filters by skill name and timestamp window
(default 7d, accepts Nh and Nd), normalizes legacy status vocabulary
(ok->pass, error->fail, skipped->skip), and returns aggregated counts
plus pass_rate.
Pass rate is null when pass+fail == 0, distinguishing 'no data' from
'always passes'. Plan 6 routing pod will check for null before
making decisions.
Route registration in cmd/server/main.go lands in a follow-up commit.
The ingestion server now exposes both REST and MCP on the same port
(3300). MCP shares brainDir, pipeline config, and LLM client with the
REST handlers — single source of process state.
Co-Authored-By: Claude Opus 4.7 (1M context) <noreply@anthropic.com>
Appends a JSON line to brainDir/sessions/<session_id>.jsonl using the
session package copied in Task 2. Required for upcoming pass-rate
logging.
Co-Authored-By: Claude Opus 4.7 (1M context) <noreply@anthropic.com>
Wraps pipeline.Run with the existing LLM client. Mirrors the HTTP
/ingest and /ingest-path semantics — accepts either path or
content+source, validates mutual exclusion, surfaces an explicit error
when the LLM client is not configured (test-mode).
ctx is threaded through to pipeline.Run for cancellation.
Co-Authored-By: Claude Opus 4.7 (1M context) <noreply@anthropic.com>
Wraps pipeline.RunRaw directly. Same dry-run semantics as the HTTP
/ingest-raw endpoint. Test exercises a single concept page; asserts
returned path and that no file is written under dry_run.
Co-Authored-By: Claude Opus 4.7 (1M context) <noreply@anthropic.com>
api.WriteNote captures the file-write logic that was previously inline
in Handler.Write. The existing HTTP endpoint now delegates to it; the
new MCP brain_write tool reuses the same function. Path-traversal
guard is strengthened to explicitly reject filenames containing path
separators or "..", so the rejection is surfaced before filepath.Base
strips the suspicious component (the previous defense-in-depth prefix
check became unreachable for these inputs after Base normalisation).
HTTP error code for caller-input errors shifts from 500 to 400, which
is semantically correct and not exercised by any existing test.
Co-Authored-By: Claude Opus 4.7 (1M context) <noreply@anthropic.com>
Wraps the existing search.Query function. Same BM25 over
brain/knowledge/ and brain/wiki/ that the HTTP /query endpoint serves.
Plan note: handleCall switch replaces the single-line stub from Task 1
— no unknownToolError type to remove since Task 1 inlined the error.
Co-Authored-By: Claude Opus 4.7 (1M context) <noreply@anthropic.com>
Copy of internal/session from the supervisor module — the ingestion
service needs it for the upcoming session_log MCP tool. The supervisor
copy will be removed in the supervisor-retirement plan; until then
the two packages are intentionally identical and pinned (no edits).
Co-Authored-By: Claude Opus 4.7 (1M context) <noreply@anthropic.com>
Adds an MCP HTTP handler under ingestion/internal/mcp. Implements
initialize, tools/list, and the JSON-RPC notification skip from prior
work. Tool dispatch is stubbed (returns unknown-tool error) and will be
filled in by subsequent tasks.
Co-Authored-By: Claude Opus 4.7 (1M context) <noreply@anthropic.com>
Allows callers to provide pre-structured RawPage data directly, bypassing the
LLM extraction step. The pipeline still handles slug computation, frontmatter,
link canonicalization, source back-references, and dedup — only the extraction
is skipped. Useful when a more capable model or manual curation produces the
structured data.
Co-Authored-By: Claude Opus 4.6 (1M context) <noreply@anthropic.com>
- Change prompt to reflect new output format: title, type, subtype, domain, content
- Remove slug/path generation responsibility from LLM — pipeline now handles it
- Wikilinks change from [[slug|Display Name]] to [[Display Name]] only
- LLM no longer includes frontmatter or paths in output
docs(schema): update LLM output format and wikilink convention for Level 3
- Specify JSON schema: title, type, subtype, domain, content fields
- Remove frontmatter requirements from schema output (handled by pipeline)
- Simplify wikilink format to [[Display Name]] — no slug or pipe
- Pipeline now responsible for slug generation and frontmatter construction
These changes shift slug/frontmatter generation from LLM to pipeline,
reducing cognitive load on the model and improving control over output.
Co-Authored-By: Claude Sonnet 4.6 <noreply@anthropic.com>
Strips slug authority from the LLM. The new RawPage type carries only
{title, type, subtype, domain, content} — no paths or frontmatter.
Pipeline will derive slugs deterministically (Task 4).
pipeline.go gets a temporary bridge stub (TODO task4) to keep the
package compiling between tasks.
Co-Authored-By: Claude Sonnet 4.6 <noreply@anthropic.com>
