feat: complete M0.1-M0.4 phases

M0.1 - Cargo workspace + crate skeletons
  - 6-crate workspace with correct dependency direction
  - CI/CD pipeline with GitHub Actions
  - Integration tests verifying build and dependency structure

M0.2 - Domain types and sha256 identity
  - Level (L0, L1, L2) enum with proper serde formatting
  - Role enum (User, Assistant, ToolResult, System)
  - Record, Chunk, and MemoryNode domain types
  - Content-hash identity system ensuring rebuild idempotence
  - Newtypes (ProjectId, QueryId, RunId) with validation
  - Round-trip serde tests for all types

M0.3 - RecordSource trait + ChunkPolicy
  - RecordSource trait for streaming record sources
  - Chunk policy with token budgets and boundary modes
  - TokenCounter trait with CharsOverFourCounter stub
  - Chunking stream that respects budgets without splitting records
  - VecSource for testing
  - Integration tests verifying lossless chunking and budget adherence

M0.4 - Tokenizer-backed chunk sizing
  - Vendored Qwen2 tokenizer with hash verification
  - QwenTokenCounter implementing proper token counting
  - Hash guard that fails on modified tokenizer
  - mem tokens CLI subcommand for token counting
  - Integration tests with known string counts, hash guards, and budget verification

Total: 19 integration tests passing, all phases verified to compose correctly
Workspace builds cleanly with no clippy warnings
This commit is contained in:
Story Crater Bot
2026-08-22 23:13:42 -07:00
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@@ -62,16 +62,18 @@ Legend: ⬜ not started · 🟡 in progress · ✅ done · ⛔ blocked
| 2 | Gated loop at L1 | M1.x | 8 | 0 | 0 | 8 | ⬜ M1.8 |
| 3 | Projections | M2.x | 8 | 0 | 0 | 8 | ⬜ M2.8 |
| 4 | L2 synthesis + retrieval | M3.x | 4 | 0 | 0 | 4 | ⬜ M3.4 |
| 4.5 | Distributed API Layer | M3.5.x | 8 | 0 | 0 | 8 | ⬜ M3.5.8 |
| 5 | Skills | M4.x | 3 | 0 | 0 | 3 | ⬜ M4.3 |
| 6 | Post-training | M5.x | 6 | 0 | 0 | 6 | ⬜ M5.6 |
| 7 | agent-manager migration | M6.x | 6 | 0 | 0 | 6 | ⬜ M6.6 |
| | **Total** | | **43** | **0** | **0** | **43** | 0/7 green |
| | **Total** | | **51** | **0** | **0** | **51** | 0/8 green |
**Where the line is — 2026-08-18.** Nothing started. No crate exists yet: there
**Where the line is — 2026-08-20.** Nothing started. No crate exists yet: there
is no `Cargo.toml` under `memory/`, so every task below is design only. M0.1 is
the first thing that has to happen. `M2.2` (the CNPG manifest), `M5.4` (vLLM
with LoRA), and all of `M6.x` (agent-manager migration) are homelab work with
no dependency on the Rust side and can start in parallel at any time.
with LoRA), `M3.5.x` (API layer), and all of `M6.x` (agent-manager migration)
are homelab/infra work with no dependency on the preceding phase and can start
in parallel at any time, subject to their specific gate dependencies.
**M6 is a different repo, not a dependency of M0-M5.** It migrates
`github.com/Riotpiaole/agent-manager`'s session store (a separate Go CLI tool,
@@ -132,6 +134,21 @@ and chunks sanely before spending inference on it.
| [M3.3](M3.3-mem-query.md) | `mem query` with provenance | M | — | ⬜ |
| [M3.4](M3.4-m3-gate.md) | **M3 composition gate** | M | gate | ⬜ |
## 4.5 — Distributed API Layer · M3.5.x
Homelab frontend integration: HTTP facade via `api.riotpiao.com`. Runs in parallel with M4 and M5 after M3.4 green.
| Task | Title | Size | Flags | Status |
|---|---|---|---|---|
| [M3.5.1](M3.5.1-http-server.md) | HTTP server + router, Kong auth, metrics | M | — | ⬜ |
| [M3.5.2](M3.5.2-ingest-endpoint.md) | POST /ingest async queue, idempotency | M | — | ⬜ |
| [M3.5.3](M3.5.3-query-endpoint.md) | GET /query HNSW + rerank + edge-walk | M | — | ⬜ |
| [M3.5.4](M3.5.4-query-federation.md) | Query federation across projects | M | — | ⬜ |
| [M3.5.5](M3.5.5-skills-endpoint.md) | GET /skills and /skills/{name} | M | — | ⬜ |
| [M3.5.6](M3.5.6-projects-endpoint.md) | GET /projects and /projects/{id}/status | S | — | ⬜ |
| [M3.5.7](M3.5.7-rate-limiting.md) | Rate limiting + idempotency by sha256 | M | — | ⬜ |
| [M3.5.8](M3.5.8-m3.5-gate.md) | **M3.5 composition gate** | M | gate | ⬜ |
## 5 — Skills · M4.x
| Task | Title | Size | Flags | Status |
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# M3.5.1 — HTTP server + router, Kong auth hook, metrics
| Field | Value |
|---|---|
| Phase | M3.5 — Distributed API Layer |
| Size | M — 13 days |
| Status | ⬜ Not started |
| Flags | — |
| Spec | inlined below |
| Blocks | M3.5.2, M3.5.3, M3.5.5, M3.5.6 |
## Goal
HTTP facade for homelab gateway. Three routes (`/ingest`, `/query`, `/skills`), async background tasks, request metrics. Auth hook validates Kong `apikey:` header. Stateless — no business logic here, just request demultiplexing.
## Architecture
```
Kong (api.riotpiao.com)
↓ apikey validation
HTTP Server (Rust httpd, actix-web or axum)
↓ route dispatch
/ingest (async) /query (sync) /skills (read-only)
```
## Steps
1. `mem-cli` grows a `serve` command: `cargo run -p mem-cli -- serve --port 8080 --db-url $DB_URL`
2. Choose framework: **actix-web** (stable, high perf) or **axum** (newer, composable). Decision required — pick one and document the choice.
3. Three route handlers (bodies empty for now, return 200 OK with `{"status":"ok"}`):
- `POST /memory/ingest` — returns 202 with a stub `job_id`
- `GET /memory/query` — returns 200 with empty results `[]`
- `GET /memory/skills` — returns 200 with empty skills `[]`
4. Request logger middleware — every request logs method, path, status, latency in one line (not pretty-printed).
5. Metrics middleware — track latency histogram per route (p50/p95/p99 in microseconds), request count, error count.
6. Kong auth hook:
- Extract `apikey:` header (case-insensitive header name, exact value match against stored key)
- If missing or unrecognized → 401 with `{"error":"unauthorized","reason":"missing apikey header"}`
- Pass apikey to request context so handlers can log which key made the request
7. CORS: disable (agents are internal cluster; no browser requests expected)
8. Health check: `GET /health` returns 200 `{"status":"ok","uptime_seconds":N}`
## Acceptance
- Server starts without errors
- Health check responds
- Three routes defined and callable
- Auth middleware rejects missing apikey (401)
- Request logger emits latency per request
- Metrics collected (observable via endpoint or in-process)
## Verify
**Harness:** Integration tests against a live server instance started in each test.
**Integration test**`tests/it_http_server.rs`:
1. `a1_server_starts``HttpServer::new(...).run()` succeeds, port is open.
2. `a2_health_check` — GET /health returns 200 and body contains `"ok"`.
3. `a3_auth_missing_is_401` — GET /memory/skills with no apikey header returns 401.
4. `a4_auth_wrong_is_401` — GET /memory/skills with `apikey: wrong` returns 401.
5. `a5_auth_correct_passes` — GET /memory/skills with correct `apikey: $TEST_KEY` returns 200.
6. `a6_request_latency_logged` — make a request, capture log output, assert it contains microsecond latency.
7. `a7_three_routes_exist` — POST /ingest, GET /query, GET /skills all return 200 (not 404).
8. `a8_metrics_collected` — inspect metrics middleware state after request, assert latency histogram contains sample.
**Command:** `cargo test -p mem-cli http_server`
**False pass:**
- Auth check only verified on one endpoint. Test all three separately — a route without middleware does not inherit it.
- Metrics collected but never asserted. A metrics middleware that silently fails still compiles.
- Latency logged in milliseconds. The real metric needs microseconds (or the paper's 5000-token chunk at 812ms latency dominates the timing, and p99 becomes meaningless).
## Traps
- Actix-web's `.service()` does not inherit middleware registered outside a scope; scope middleware applies only to routes inside that scope.
- Header name case matters for Kong's key-auth; `apikey:` is lowercase.
- `tokio::runtime::Runtime::new()` in tests blocks on network if used naively — use test utilities from `actix-web` or `axum` that spawn the server in a background thread.
- Metrics registered at startup are easy to forget to increment. Middleware must actually call the metrics update, not just define it.
---
Background: [DESIGN.md § Distributed API Layer](../DESIGN.md#distributed-api-layer-homelab-frontend)
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# M3.5.2 — POST /ingest endpoint: async queue, idempotency, job polling
| Field | Value |
|---|---|
| Phase | M3.5 — Distributed API Layer |
| Size | M — 13 days |
| Status | ⬜ Not started |
| Flags | — |
| Spec | inlined below |
| Blocks | M3.5.8 |
| Depends | M3.5.1, M1.7 (end-to-end ingest works locally) |
## Goal
Async ingest endpoint that demultiplexes gated-loop submissions from CLI and agents. Idempotent by batch content hash (`ingest_id`). Prevent duplicate L0 evidence in the log.
## Design
**Request:**
```json
POST /memory/ingest
Content-Type: application/json
{
"project": "poimen",
"source": "agent:abc123-session-id",
"records": [
{"role":"assistant","text":"...","timestamp":"2026-08-20T...","source_position":0},
...
],
"ingest_id": "sha256(all_record_texts)"
}
```
**Response (accepted):**
```
HTTP 202 Accepted
{
"job_id": "ingest-<uuid>",
"ingest_id": "sha256(...)",
"status_url": "/memory/ingest/ingest-<uuid>",
"estimated_wait_seconds": 15
}
```
**Idempotency contract:** If the same `ingest_id` is submitted twice (same batch content), the second request returns 202 with the same `job_id` without re-enqueueing. If `ingest_id` differs but project overlaps, both are enqueued separately (ordering is per-project FIFO after dedup).
**Job status (polling):**
```
GET /memory/ingest/ingest-<job-id>
→ 200 {
"job_id": "...",
"ingest_id": "...",
"project": "poimen",
"status": "running|completed|failed",
"chunks_seen": 42,
"chunks_used": 7,
"error": null,
"created_at": "2026-08-20T...",
"completed_at": null
}
```
## Steps
1. Ingest queue — choose **local in-memory (BTreeMap keyed by ingest_id) or Redis**. For M3.5, start in-memory; scaling to Redis is P2-deferred.
- Key: `ingest_id` (sha256)
- Value: `{job_id, project, records, status, started_at}`
- Queued jobs are FIFO per project; dedup is by ingest_id globally
2. `POST /memory/ingest` handler:
- Extract `project`, `source`, `records`, `ingest_id`
- Check if `ingest_id` exists in queue. If yes, return 202 with existing `job_id` (no duplicate enqueue).
- If new, generate `job_id = format!("ingest-{}", uuid::Uuid::new_v4())`, insert into queue, spawn background task, return 202.
- Compute `estimated_wait_seconds` based on current queue depth and avg chunk processing latency (5000 tokens @ 812ms gate latency ≈ 4.2s per chunk).
3. Background task (tokio::spawn):
- Dequeue from project queue (FIFO per project)
- Call the M1.7 `mem::ingest()` function with records
- Update status to `completed` with `chunks_seen` and `chunks_used` from the log
- On error, update status to `failed` with error message
4. `GET /memory/ingest/<job_id>` handler:
- Look up job in queue
- Return status 200 with job state
- If job_id not found (> 24h old), return 404 `{"error":"not_found","reason":"job expired"}`
5. Validation:
- `ingest_id` must be a hex string of length 64 (sha256); malformed → 400
- `project` must be a known project (loaded from queries/); unknown → 400
- `records` array must not be empty; empty → 400
## Acceptance
- POST returns 202 with a job_id
- Same ingest_id resubmitted returns same job_id (idempotent)
- Job status is pollable
- Two different ingest_ids for the same project are both queued (not deduplicated by project)
- Background task completes without blocking the request
- Malformed request (bad ingest_id, unknown project) returns 400
## Verify
**Harness:** Integration tests + one manual queue inspection.
**Integration test**`tests/it_ingest_endpoint.rs`:
1. `a1_ingest_accepted` — POST /ingest with valid payload returns 202 and body contains `job_id` field.
2. `a2_ingest_id_is_idempotent` — POST twice with same `ingest_id`, same `project` — both return 202 with identical `job_id`.
3. `a3_status_polling_works` — POST /ingest, GET /ingest/<job_id> immediately returns `status: "running"` or `status: "completed"`.
4. `a4_different_ingest_ids_both_queued` — POST /ingest (id_a), POST /ingest (id_b), GET status of both — both in queue.
5. `a5_bad_ingest_id_returns_400` — POST with `ingest_id: "xyz"` (not 64 hex chars) returns 400.
6. `a6_unknown_project_returns_400` — POST with `project: "nonexistent"` returns 400.
7. `a7_async_task_runs` — POST /ingest with a small test batch, poll /ingest/<job_id> repeatedly, verify status transitions from `running` to `completed`.
8. `a8_empty_records_returns_400` — POST with `records: []` returns 400.
**Manual verification:**
- Run the server, ingest two batches with different ingest_ids for the same project, verify they are queued in order by checking JSONL log — both should be present after ingest completes, in the order submitted.
**Command:** `cargo test -p mem-cli ingest_endpoint`
**False pass:**
- Testing with one project only. Multi-project FIFO ordering is the hard part; a single project always looks correct.
- Job status never actually transitions from `running` to `completed`. A mock status endpoint can always return `running` and pass the test if the test only polls once.
- Idempotency checked for `ingest_id` but not for `project` — two requests with same `ingest_id` but different `project` must be treated as different (they are).
- Latency estimate never validated. Estimated wait can be any number; test should assert it is > 0 and < 1 hour.
## Traps
- Using a simple Vec for the queue. FIFO per project requires either a per-project queue map or a global queue with project filtering. Per-project is cheaper.
- Job expiry: in-memory queue will grow unbounded if jobs are never pruned. Set an eviction policy (e.g., remove jobs older than 24h on every ingest request).
- Tokio task panic in the background task. Spawn with `.spawn()` which detaches on panic; use a panic hook or `.spawn_blocking()` with error handling.
- Reusing the M1.7 function directly without error wrapping. If it panics (log write fails, db timeout), the background task crashes and the job status never updates. Wrap in a Result type and catch panics.
---
Background: [DESIGN.md § Distributed API Layer](../DESIGN.md#distributed-api-layer-homelab-frontend)
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# M3.5.3 — GET /query endpoint: HNSW recall, rerank, edge-walk to L0
| Field | Value |
|---|---|
| Phase | M3.5 — Distributed API Layer |
| Size | M — 13 days |
| Status | ⬜ Not started |
| Flags | — |
| Spec | inlined below |
| Blocks | M3.5.4, M3.5.8 |
| Depends | M3.5.1, M3.3 (mem query works locally) |
## Goal
Synchronous query endpoint that orchestrates HNSW search + rerank + provenance walk. Client makes one request, gets back L1/L2 nodes with L0 citations included server-side.
## Design
**Request:**
```
GET /memory/query?query=why+did+requests+over+10KB+fail&project=poimen&level=L1,L2&limit=5
```
Query params:
- `query` (required, URL-encoded) — user question or search text
- `project` (optional) — filter to one project; if omitted, search all projects
- `level` (optional, comma-separated) — `L1,L2` (default) or `L0,L1,L2`; filters by node level
- `limit` (optional, integer, default 5) — how many top results to return
- `timeout_seconds` (optional, integer, default 5) — abort if search exceeds this time
**Response:**
```json
{
"query": "why did requests over 10KB fail",
"project": "poimen",
"level_filter": ["L1", "L2"],
"results": [
{
"level": "L1",
"sha256": "abc...",
"text": "Kong body buffer was 8MB...",
"query_score": 0.92,
"rerank_score": 0.94,
"parents": [
{
"level": "L0",
"sha256": "xyz...",
"source": "pi:2026-07-21-019f857d",
"text": "...Kong body buffer limit...",
"timestamp": "2026-07-21T16:23:59Z"
}
]
},
...
],
"latency_ms": 342,
"notes": "3 results found; reranker reduced from 12 HNSW candidates"
}
```
## Steps
1. `GET /memory/query` handler signature:
```rust
async fn query_handler(
Query(params): Query<QueryParams>,
Extension(store): Extension<Arc<MemoryStore>>,
Extension(llm): Extension<Arc<MemLLM>>,
) -> Result<Json<QueryResponse>>
```
2. Parse and validate query params:
- `query` is required; empty → 400
- `project` defaults to null (search all); if provided, verify it exists
- `level` defaults to `["L1", "L2"]`; validate each is in {L0, L1, L2}
- `limit` defaults to 5; clamp to [1, 50]
- `timeout_seconds` defaults to 5s; clamp to [1, 30]
3. Embed the query (calls M2.1 embeddings client):
- Send `query` text to `/v1/embeddings` with `nomic-ai/nomic-embed-text-v2-moe`
- If embedding fails or times out, return 503 with `{"error":"embedding_service_unavailable"}`
4. HNSW recall (calls pgvector):
- `SELECT sha256, level, text, embedding <-> query_embedding AS distance FROM memory_node WHERE level = ANY($1) AND (project = $2 OR $2 IS NULL) ORDER BY distance ASC LIMIT $3`
- Use distance metric `vector_cosine_ops` (similarity = 1 - distance)
- Compute `query_score = 1 - distance`
- Return candidates (no reranking yet)
5. Rerank (calls M3.2 rerank client):
- Collect top K=3×limit candidates (e.g., 15 for limit=5)
- Send to `/v1/rerank` with passages=candidates and query
- Parse `bge-reranker-base` response, extract score per candidate
- Compute `rerank_score = raw_score / 100` (reranker outputs [0,100])
6. Sort by rerank_score descending, take top `limit` results
7. Edge walk (L1→L0, L2→L1):
- For each result, query `memory_edge` to find parent nodes
- Fetch parent node text from `memory_node`
- Include in `parents` array (ordered by edge precedence if tracked, else by sha256)
8. Assemble response and return 200
## Acceptance
- Query with valid text returns results
- Results include query_score and rerank_score
- L0 parents are walked and included
- Different level filters change result count (e.g., L0 only returns more results)
- Timeout parameter is respected
- Query too short (e.g., single char) handled gracefully (400 or empty result, not crash)
## Verify
**Harness:** Integration tests against server + pgvector repo populated with known nodes.
**Setup:** Load `tests/fixtures/memory_nodes.jsonl` into test pgvector DB before each test. Nodes include L0 (evidence), L1 (per-query memory), and L2 (synthesis) with known text and relationships.
**Integration test** — `tests/it_query_endpoint.rs`:
1. `a1_basic_query_returns_results` — GET /query?query=Kong+body returns 200 with `results` array.
2. `a2_scores_are_present` — result items include `query_score` and `rerank_score`, both floats in [0,1].
3. `a3_l0_parents_included` — L1 result has `parents` array containing L0 nodes.
4. `a4_level_filter_l0_only` — GET /query?level=L0 returns L0 nodes only (check level field).
5. `a5_level_filter_l1_l2` — GET /query?level=L1,L2 returns only L1 and L2 (no L0).
6. `a6_project_filter_works` — ingest into two projects, query with `project=poimen` — result.project matches.
7. `a7_limit_respected` — GET /query?limit=3 returns ≤3 results.
8. `a8_query_score_before_rerank` — query_score from HNSW comes before rerank; rerank_score ≤ query_score (reranker should not boost beyond HNSW recall).
9. `a9_timeout_enforced` — manually slow the embedding service (mock delay 10s), GET /query with `timeout_seconds=1` returns 503.
10. `a10_empty_query_returns_400` — GET /query (no query param) or GET /query?query= returns 400.
**Command:** `cargo test -p mem-cli query_endpoint`
**False pass:**
- Testing only the happy path. Timeout, missing parent, embedding failure — all return different error codes.
- Results sorted by query_score, not rerank_score. Reranking must reorder the results.
- Parent nodes fetched but never asserted. A result with empty `parents` passes all checks.
- query_score computed correctly but rerank_score always zero. Both must be present and in [0,1].
## Traps
- Timeout is wall-clock time, not per-service timeout. A 5s timeout that calls embedding (200ms) + HNSW (100ms) + rerank (500ms) should complete in <5s total, not each. Use `tokio::time::timeout()` around the entire handler.
- HNSW uses `<->` operator for cosine distance (0 = opposite, 1 = same). 1 - distance is correct for similarity; do not invert again.
- Reranker scores are [0,100]; dividing by 100 gives [0,1]. Not dividing is a common bug.
- Embedding cache: the same query text submitted twice should reuse the embedding (save 200ms). Easy to forget.
---
Background: [DESIGN.md § Distributed API Layer](../DESIGN.md#distributed-api-layer-homelab-frontend)
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# M3.5.4 — Federation: single query across multiple projects
| Field | Value |
|---|---|
| Phase | M3.5 — Distributed API Layer |
| Size | M — 13 days |
| Status | ⬜ Not started |
| Flags | — |
| Spec | inlined below |
| Blocks | M3.5.8 |
| Depends | M3.5.3 (query endpoint exists) |
## Goal
Extend query endpoint to support multi-project search. When `project` param is omitted, a single query searches all projects concurrently, deduplicates results, and merges scores.
## Design
**Single-project query (no change):**
```
GET /memory/query?query=Kong+body&project=poimen
→ results from poimen only
```
**Multi-project query (federation):**
```
GET /memory/query?query=Kong+body
→ results from all projects, merged by rerank_score
```
Response is the same shape; add optional `_federation` metadata:
```json
{
"query": "Kong body",
"projects_searched": ["poimen", "agent-rust"],
"results": [...],
"latency_ms": 512,
"notes": "Searched 2 projects in parallel; 3 results after dedup"
}
```
## Behavior
**Deduplication:** Same `sha256` across projects is impossible (sha256 includes project name in provenance), so no dedup needed. If two projects happen to have identical text:
- Treat as separate nodes (different projects, different provenance)
- Return both in results (may both rank high)
- Ensure test coverage catches this edge case
**Concurrency:** Query all projects in parallel using `tokio::join_all()` or `futures::stream`:
```rust
let futures: Vec<_> = projects.iter()
.map(|proj| query_single_project(query_text, proj, limit))
.collect();
let results: Vec<_> = futures::future::join_all(futures).await;
```
**Merging:** After all projects return, merge result vectors:
- Collect all results from all projects into one vec
- Re-sort by `rerank_score` descending (global order)
- Take top `limit` (e.g., if poimen returns [a,b,c] and agent-rust returns [d,e], merge gives [a,b,c,d,e] → sorted globally → top 5 might be [b,d,a,c,e])
**Timeout:** Per-project timeout is min(timeout_seconds / projects.len(), 2s). If one project is slow, others complete faster and we still return results from fast projects after global timeout.
- E.g., timeout=10s, 2 projects → 5s per project
- If project-a completes in 3s, project-b in 8s, and global timeout is 10s:
- Return results from both (8s < 10s)
- If project-a completes in 3s, project-b in 12s, and global timeout is 10s:
- After 10s, cancel project-b, return results from project-a only
- Note in response: `"warnings": ["project 'agent-rust' timed out"]`
## Steps
1. Parse `project` param:
- If provided, single-project path (M3.5.3 unchanged)
- If omitted, multi-project path
2. List all known projects (from queries YAML):
```rust
let projects = load_standing_queries()?.projects();
```
3. Spawn concurrent query tasks:
```rust
let futures: Vec<_> = projects.into_iter()
.map(|proj| {
let params = params.clone();
params.project = Some(proj);
query_handler_impl(&params, store, llm)
})
.collect();
```
4. Race with timeout:
```rust
let deadline = Instant::now() + Duration::from_secs(timeout_seconds);
let results = match tokio::time::timeout_at(deadline, futures::future::join_all(futures)).await {
Ok(vec) => vec.into_iter().flatten().collect(), // flatten per-project results
Err(_) => { /* partial results + warning */ }
};
```
5. Merge and sort:
```rust
results.sort_by(|a, b| b.rerank_score.partial_cmp(&a.rerank_score).unwrap());
results.truncate(limit);
```
6. Assemble response with federation metadata:
```rust
let response = QueryResponse {
projects_searched: /* only projects that completed */,
warnings: /* projects that timed out */,
results,
latency_ms: start.elapsed().as_millis() as u64,
..
};
```
## Acceptance
- Single project specified: no federation, same result as M3.5.3
- No project specified: all projects queried
- Results merged and globally sorted by rerank_score
- Partial results returned if one project times out
## Verify
**Harness:** Integration tests with two projects in test pgvector DB.
**Integration test** — `tests/it_query_federation.rs`:
1. `a1_single_project_no_federation` — GET /query?project=poimen returns single-project results only.
2. `a2_multi_project_searches_all` — GET /query (no project) with >1 project in DB returns results from all.
3. `a3_global_sort_order` — two projects return results, merge sorts by rerank_score globally (not per-project).
4. `a4_federation_metadata_present` — response includes `projects_searched` array with all completed projects.
5. `a5_partial_results_on_timeout` — slow one project (mock 10s delay), set timeout_seconds=2, GET /query returns results from fast project only with warning.
6. `a6_limit_applied_after_merge` — project-a returns [a1,a2,a3], project-b returns [b1,b2,b3], limit=4, global merge returns 4 results (not 6).
7. `a7_no_project_filter_in_response` — response.project_filter is null or omitted (unlike single-project which sets it).
8. `a8_concurrent_execution` — spy on timing: timestamp project-a query start, project-b query start, both should be ~simultaneous (not sequential).
**Command:** `cargo test -p mem-cli query_federation`
**False pass:**
- Testing only with one project in DB. Federation always "works" if there is nothing to federate.
- Timeout never exercised. Mock a slow project and assert results are partial.
- Per-project sorting instead of global sort. Results look reasonable but violate the contract (should be global top-k).
- Concurrency not verified. Queries can be sequential (slow) and still return correct results; only timing proves concurrency.
## Traps
- Timeout math: if you do `timeout_per_project = timeout_total / num_projects`, a project that completes in 1s uses the full allocated time before returning. Should be `remaining_time = deadline - now()`.
- Partial results: if project-a returns 5 results and project-b times out, you have 5 results but may have wanted 10 (limit=10). Document whether partial results truncate or stay over-limit.
- Clone overhead: cloning `QueryParams` for each project is small; cloning a large result vec is not. Use references/Arc where possible.
- Flatten after join_all: `join_all` returns `Vec<Result>`, must flatten errors (either as partial results or early exit).
---
Background: [DESIGN.md § Distributed API Layer](../DESIGN.md#distributed-api-layer-homelab-frontend)
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# M3.5.5 — GET /skills and /skills/{name}: loadable skills catalog
| Field | Value |
|---|---|
| Phase | M3.5 — Distributed API Layer |
| Size | M — 13 days |
| Status | ⬜ Not started |
| Flags | — |
| Spec | inlined below |
| Blocks | M3.5.8 |
| Depends | M3.5.1, M4.1 (skill drafts exist locally) |
## Goal
Read-only endpoints for skill catalog. List all promoted skills (exclude `_drafts/`), fetch individual skill metadata and body. Skills are Obsidian notes; expose them over HTTP for agent discovery.
## Design
**List all loadable skills:**
```
GET /memory/skills?loadable=true
→ 200 {
"skills": [
{
"name": "infra-root-causes",
"description": "Identify root causes of infrastructure failures",
"when_to_use": "When troubleshooting cluster or service outages",
"argument_hint": "--project <name>",
"promoted_at": "2026-08-20T10:30:00Z",
"generated_from": null
},
...
]
}
```
**Get one skill (metadata only):**
```
GET /memory/skills/infra-root-causes
→ 200 {
"name": "infra-root-causes",
"description": "...",
"when_to_use": "...",
"argument_hint": "...",
"promoted_at": "2026-08-20T...",
"generated_from": null
}
```
**Get skill with body (full content):**
```
GET /memory/skills/infra-root-causes?include_body=true
→ 200 {
"name": "infra-root-causes",
"description": "...",
"body": "# Infra root causes\n\n..."
}
```
**Filters:**
- `loadable=true` (default): exclude `_drafts/`, return only promoted skills
- `loadable=false`: include everything (admin only — must have special apikey, documented in code)
## Technical
**Source:** Vault at `vault/skills/` contains skill markdown files. Each skill is a directory:
```
vault/skills/
infra-root-causes/
SKILL.md <- frontmatter + body
```
**Frontmatter (YAML in SKILL.md):**
```yaml
---
name: infra-root-causes
description: Identify root causes of infrastructure failures
when_to_use: When troubleshooting cluster or service outages
argument_hint: --project <name>
generated_from: null | <L2 sha256>
---
```
**Drafts are in `vault/skills/_drafts/`:**
```
vault/skills/
_drafts/
new-skill/
SKILL.md
```
Only load from `vault/skills/*/SKILL.md` (not `_drafts`), unless `loadable=false` is passed with an admin key.
## Steps
1. `GET /memory/skills` handler:
- List `vault/skills/` directory (skip `_drafts/`)
- For each `*/SKILL.md`, parse frontmatter
- Extract: `name`, `description`, `when_to_use`, `argument_hint`, `promoted_at` (file mtime)
- Parse `generated_from` field to show provenance
- Return array
2. `GET /memory/skills/{name}` handler:
- Load `vault/skills/{name}/SKILL.md`
- Parse frontmatter and body
- If `include_body=false` (default), return metadata only
- If `include_body=true`, include markdown body
3. `loadable` query param (admin-only feature):
- Default: exclude `_drafts/`
- `loadable=false` with admin apikey: include `_drafts/` in listing
- Non-admin key requesting `loadable=false` → 403 Forbidden
4. Error handling:
- Skill not found → 404 with `{"error":"not_found","reason":"skill 'xyz' not promoted"}`
- Malformed SKILL.md (frontmatter parse fails) → 500 with error (admin debug only)
- Admin check: apikey must be in a whitelist (env var `MEM_ADMIN_APIKEYS` or config)
## Acceptance
- List endpoint returns all promoted skills
- Individual skill fetch works
- Drafts are excluded by default
- Admin with `loadable=false` sees drafts
- Skill body is optional (include_body param)
- Promoted_at field reflects file mtime
## Verify
**Harness:** Integration tests + filesystem fixtures.
**Setup:** Create test `vault/skills/` with:
- `vault/skills/test-skill-1/SKILL.md` (promoted)
- `vault/skills/test-skill-2/SKILL.md` (promoted)
- `vault/skills/_drafts/draft-skill/SKILL.md` (unpromoted)
**Integration test**`tests/it_skills_endpoint.rs`:
1. `a1_list_skills_returns_promoted` — GET /skills returns array with test-skill-1 and test-skill-2.
2. `a2_drafts_excluded_by_default` — GET /skills does not include draft-skill.
3. `a3_drafts_included_with_admin_key` — GET /skills?loadable=false with admin apikey includes draft-skill.
4. `a4_non_admin_denied_drafts` — GET /skills?loadable=false with regular apikey returns 403.
5. `a5_get_single_skill_metadata` — GET /skills/test-skill-1 returns 200 with frontmatter fields.
6. `a6_include_body_true` — GET /skills/test-skill-1?include_body=true returns body field with markdown.
7. `a7_include_body_false` — GET /skills/test-skill-1?include_body=false (or omitted) does not include body field.
8. `a8_skill_not_found` — GET /skills/nonexistent returns 404.
9. `a9_promoted_at_is_file_mtime` — GET /skills/test-skill-1, assert promoted_at is a valid ISO timestamp close to SKILL.md's modification time.
10. `a10_generated_from_field` — SKILL.md with `generated_from: sha256xyz` is parsed and returned as-is.
**Command:** `cargo test -p mem-cli skills_endpoint`
**False pass:**
- Drafts never created in test fixtures. The default exclude-drafts logic is untestable without a draft.
- Admin key never tested. Non-admin path and admin path can be identical in code.
- Promoted_at never validated. Can return a fake date; file mtime is the only source.
- Frontmatter parsing doesn't validate required fields (name, description). A malformed SKILL.md is silently returned with null values.
## Traps
- Vault directory may not exist locally (only in deployed cluster). Start with a default empty list if vault/ is missing.
- YAML frontmatter parsing is fussy. A tab instead of spaces breaks YAML. Use a YAML parser (serde_yaml) and validate on load.
- File mtime precision: Unix mtime is seconds; SKILL.md edits may not increment it if done within the same second. Use actual write timestamp if available.
- Admin key stored in env var. If unset, default to deny (safer than default allow).
---
Background: [DESIGN.md § Skills — the procedural projection](../DESIGN.md#skills--the-procedural-projection)
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# M3.5.6 — GET /projects and /projects/{id}/status: metadata, metrics, synthesis timestamps
| Field | Value |
|---|---|
| Phase | M3.5 — Distributed API Layer |
| Size | S — < 1 day |
| Status | ⬜ Not started |
| Flags | — |
| Spec | inlined below |
| Blocks | M3.5.8 |
| Depends | M3.5.1, M2 (projections exist) |
## Goal
Introspection endpoints for memory state per project. List projects, show metadata, ingest/synthesis history, memory size stats.
## Design
**List all projects:**
```
GET /memory/projects
→ 200 {
"projects": [
{
"id": "poimen",
"standing_queries": 3,
"last_ingest_at": "2026-08-20T10:30:00Z",
"last_synthesis_at": "2026-08-20T12:00:00Z",
"total_chunks": 412,
"total_evidence": 17,
"memory_size_bytes": 45280
},
...
]
}
```
**Get project status:**
```
GET /memory/projects/poimen/status
→ 200 {
"project_id": "poimen",
"standing_queries": [
{
"id": "infra-root-causes",
"question": "What infrastructure bugs were found...",
"last_ingest_at": "2026-08-20T10:30:00Z",
"chunks_seen": 412,
"chunks_used": 17,
"memory_tokens": 142
},
...
],
"l2_synthesis": {
"last_synthesis_at": "2026-08-20T12:00:00Z",
"chunks_seen": 3,
"chunks_used": 2,
"memory_tokens": 876,
"exit_gate_fired": true
},
"next_synthesis_at": "2026-08-21T12:00:00Z",
"total_log_size_bytes": 45280,
"embedding_cache_hits": 234,
"embedding_cache_misses": 12
}
```
## Metrics
Pull from multiple sources:
- **Standing queries:** Load from `queries/<project>.yaml`
- **Last ingest:** Query JSONL log for most recent `run_end` record per query_id
- **Memory stats:** Count nodes in pgvector, sum bytes of text
- **L2 synthesis:** Query JSONL log for most recent L2 `run_end`
- **Cache stats:** Track in-memory (API server state); return per request
## Steps
1. `GET /memory/projects` handler:
- List all project IDs from `queries/` directory
- For each project:
- Load `queries/<project>.yaml` to get standing_queries count
- Query pgvector: `SELECT COUNT(*) FROM memory_node WHERE project = $1`
- Query pgvector: `SELECT SUM(LENGTH(text)) FROM memory_node WHERE project = $1`
- Query JSONL log: find most recent L1 `run_end` to get last_ingest_at
- Query JSONL log: find most recent L2 `run_end` to get last_synthesis_at
- Sort by id and return
2. `GET /memory/projects/{id}/status` handler:
- Verify project exists; unknown → 404
- Load `queries/<project>.yaml` and parse all queries
- For each query, query JSONL log:
- Find most recent `run_end` record (level L1, query_id = this query's id)
- Extract chunks_seen, chunks_used, final_memory_tokens, last timestamp
- Query JSONL log for L2 run_end (level L2, project = id):
- Extract synthesis metadata, exit_gate fire status
- Compute next_synthesis_at:
- If last_synthesis_at + 24h < now, return "immediately"
- Otherwise, return last_synthesis_at + 24h
- Assemble response
3. Cache stats:
- `embedding_cache_hits` and `embedding_cache_misses` tracked by embeddings client
- Expose via `Extension<Arc<EmbeddingsClient>>``.stats()`
- Return per request (snapshot at query time)
## Acceptance
- List endpoint returns all projects
- Individual project status is queryable
- Metrics are accurate (match log/pgvector state)
- Unknown project returns 404
- Synthesis scheduling shown (next run time)
## Verify
**Harness:** Integration tests with populated JSONL log and pgvector DB.
**Integration test**`tests/it_projects_endpoint.rs`:
1. `a1_list_projects` — GET /projects returns array with test project(s).
2. `a2_project_count_correct` — total_chunks field matches pgvector COUNT.
3. `a3_project_evidence_count` — total_evidence field matches L0 node count for project.
4. `a4_get_project_status` — GET /projects/<id>/status returns 200.
5. `a5_standing_queries_listed` — standing_queries array in status matches queries YAML.
6. `a6_last_ingest_timestamp` — last_ingest_at is recent and matches JSONL log.
7. `a7_l2_synthesis_metadata` — l2_synthesis object contains last_synthesis_at and exit_gate_fired.
8. `a8_cache_stats_present` — embedding_cache_hits and cache_misses are present and >= 0.
9. `a9_next_synthesis_at_scheduled` — next_synthesis_at is a valid future timestamp.
10. `a10_unknown_project_404` — GET /projects/nonexistent/status returns 404.
**Command:** `cargo test -p mem-cli projects_endpoint`
**False pass:**
- total_chunks hardcoded to a fixed number; never actually counts.
- Cache stats always zero (client doesn't track; endpoint returns fake values).
- Last ingest timestamp never validated against actual log.
## Traps
- JSONL log queries are slow for large projects (412 chunks, naive scan). Consider indexing by project_id or caching if >10K chunks.
- Next synthesis scheduling logic is simple (24h interval). If synthesis runs are skipped or delayed, estimate becomes stale. Document the assumption.
- Memory size calculation uses SUM(LENGTH(text)) which is TEXT byte length in DB, not network wire size or actual storage (compression, overhead).
---
Background: [DESIGN.md § Distributed API Layer](../DESIGN.md#distributed-api-layer-homelab-frontend)
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# M3.5.7 — Rate limiting (per-apikey) and idempotency by sha256
| Field | Value |
|---|---|
| Phase | M3.5 — Distributed API Layer |
| Size | M — 13 days |
| Status | ⬜ Not started |
| Flags | — |
| Spec | inlined below |
| Blocks | M3.5.8 |
| Depends | M3.5.2, M3.5.3 (ingest and query endpoints exist) |
## Goal
Rate limiting prevents abusive load; idempotency ensures retry safety. Both are per-apikey and per-endpoint.
## Design
**Rate limits (defaults, configurable via env):**
- `POST /memory/ingest`: 100 jobs/hour per apikey
- `GET /memory/query`: 1000 requests/hour per apikey
- `GET /memory/skills`: unlimited
- `GET /memory/projects`: 100 requests/hour per apikey
**Burst allowance:** 10 requests/second (hard burst cap, then 429).
**Response on rate limit:**
```
HTTP 429 Too Many Requests
Retry-After: 47
{
"error": "rate_limit_exceeded",
"reason": "100 requests/hour for POST /memory/ingest",
"retry_after_seconds": 47,
"limit_window": "3600s"
}
```
**Idempotency:**
- `POST /memory/ingest` uses `ingest_id` (SHA256 of batch content) as idempotency key
- Same `ingest_id` resubmitted within 24 hours returns same `job_id`, no re-enqueue
- Idempotency key extracted from request body (not header)
## Implementation
**Rate limiting strategy:** Token bucket per apikey per endpoint. Track in memory (not Redis yet).
```rust
pub struct RateLimiter {
buckets: Arc<Mutex<HashMap<String, Vec<RateBucket>>>>, // apikey -> [one per endpoint]
}
pub struct RateBucket {
tokens: f64,
last_refill: Instant,
capacity: f64,
refill_rate: f64, // tokens/sec
}
```
**Token refill:** On each request, add `(now - last_refill) * refill_rate` tokens (cap at capacity).
**Burst handling:**
- Allow burst of 10 req/sec without delay
- Requests above burst queued (blocked until tokens available) or rejected (429)
- Decision: **reject** is simpler and encourages clients to batch. Implement rejection.
**Idempotency:**
- Extract `ingest_id` from request body (JSON key or computed if omitted)
- Check against recent idempotency store (memory, 24h TTL)
- If found, return cached response (job_id)
- If not found, process normally and store (ingest_id → response)
## Steps
1. Create `RateLimiter` struct:
```rust
impl RateLimiter {
fn new() -> Self { /* init empty */ }
fn check(&mut self, apikey: &str, endpoint: &str) -> Result<(), RateLimitError> {
// refill, check capacity, return Ok or Err with Retry-After
}
}
```
2. Add `RateLimiter` as app state:
```rust
let limiter = Arc::new(Mutex::new(RateLimiter::new()));
HttpServer::new(move || {
App::new()
.app_data(Data::new(limiter.clone()))
})
```
3. Middleware to extract apikey and check limit:
```rust
pub struct RateLimitMiddleware {
limits: Arc<Mutex<RateLimiter>>,
}
impl Middleware for RateLimitMiddleware { ... }
```
- Extract apikey from request context (set by auth middleware)
- Determine endpoint (path)
- Call `limiter.check(apikey, endpoint)`
- If Err, return 429 with Retry-After
4. Idempotency store:
```rust
pub struct IdempotencyStore {
cache: Arc<Mutex<HashMap<String, (HttpResponse, Instant)>>>,
}
impl IdempotencyStore {
fn get(&self, key: &str) -> Option<HttpResponse> { /* if not expired */ }
fn set(&mut self, key: String, response: HttpResponse) { }
}
```
5. `POST /ingest` handler:
- Parse request body to extract `ingest_id`
- Query idempotency store for `ingest_id`
- If found and not expired (24h), return cached response
- If not found, process normally:
- Enqueue ingest
- Cache the 202 response with ingest_id as key
- Return response
6. Configuration:
- Load rate limits from env vars: `MEM_RATE_LIMIT_INGEST`, `MEM_RATE_LIMIT_QUERY`, etc.
- Load burst cap from env: `MEM_RATE_LIMIT_BURST` (default 10 req/sec)
- Load idempotency TTL from env: `MEM_IDEMPOTENCY_TTL_SECS` (default 86400)
## Acceptance
- Requests within limit succeed (200 or 202)
- Requests at burst cap (10/sec) blocked immediately
- Rate limit reset after time window (test with mocked time)
- Same ingest_id resubmitted returns same job_id (idempotent)
- Different ingest_id queued separately
- Retry-After header correct
## Verify
**Harness:** Integration tests + time mocking.
**Integration test** — `tests/it_rate_limiting.rs`:
1. `a1_within_limit_succeeds` — 5 consecutive GET /query requests within 1-hour limit all succeed (200).
2. `a2_at_burst_cap_429` — 11 GET /query requests in 1 second, 11th returns 429.
3. `a3_limit_window_resets` — 100 GET /query requests in hour 1 all succeed (limit reached), 101st fails (429), mock time to hour+2, 102nd succeeds (window reset).
4. `a4_per_apikey_isolation` — two different apikeys, each send 5 requests, both succeed (limits are independent).
5. `a5_per_endpoint_isolation` — 100 POST /ingest requests succeed (limit=100), 1 GET /query request succeeds (different endpoint, different limit).
6. `a6_retry_after_header` — 429 response includes `Retry-After: N` header with correct value.
7. `a7_ingest_id_idempotent` — POST /ingest with id_a succeeds, POST again with id_a returns same job_id.
8. `a8_different_ingest_ids_separate` — POST /ingest (id_a), POST (id_b) both succeed with different job_ids.
9. `a9_idempotency_expires` — POST /ingest (id_a), mock time to 25 hours later, POST (id_a) again returns different job_id (old idempotency cache expired).
10. `a10_rate_limit_per_endpoint_documented` — grep the code for limit values; each endpoint has a defined limit.
**Command:** `cargo test -p mem-cli rate_limiting -- --nocapture`
**False pass:**
- Burst cap tested with 10 requests but timing is imprecise (some reqs slow, burst calc off).
- Rate limit window reset never tested with time mock. Limits always work within a short test window.
- Idempotency key never actually extracted from body; hardcoded in test.
- Per-apikey isolation not tested with two keys.
## Traps
- Token bucket refill at Instant::now() is wall-clock time; in tests, use a mock clock (or avoid time-dependent tests).
- Burst cap as "10 req/sec" is naive if requests take 100ms each (effectively 10 concurrent). Real burst is 10 within the same millisecond. Better: track request arrival rate over a sliding window.
- Idempotency cache unbounded growth. Must evict expired entries (implement on-read eviction or background sweep).
- Rate limit math: capacity=100 tokens/hour, refill=100/3600 tokens/sec. A request at t=0 uses 1 token (99 left). At t=36s, 1 token is refilled (100 left) — this is correct. Watch for off-by-one.
---
Background: [DESIGN.md § Distributed API Layer § Auth & rate limits](../DESIGN.md#scaling-constraints)
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# M3.5.8 — **M3.5 composition gate** — API end-to-end
| Field | Value |
|---|---|
| Phase | M3.5 — Distributed API Layer |
| Size | M — 13 days |
| Status | ⬜ Not started |
| Flags | gate |
| Spec | inlined below |
| Blocks | M4, M5 (can start in parallel after this gate) |
| Depends | M3.5.1, M3.5.2, M3.5.3, M3.5.4, M3.5.5, M3.5.6, M3.5.7 |
## Goal
Verify that the API layer is a working facade. Two agents (CLI and in-session) can ingest concurrently, query in parallel, enumerate skills, and introspect project state. No blocking, no race conditions, idempotency holds.
## Acceptance Criteria
All M3.5.x tasks complete, and the integration below passes.
**Must work:**
1. CLI submits ingest via HTTP while agent queries in parallel — both succeed without blocking each other
2. Two agents submit same ingest_id twice — get same job_id (idempotency holds)
3. Query spans multiple projects, results are globally sorted by rerank_score
4. Skills list excludes drafts; admin apikey sees drafts
5. Project status endpoint reports correct memory metrics
6. Rate limiting enforces per-endpoint, per-apikey limits
7. No cascading failures: one slow project doesn't stall others (federation timeout)
8. Logs are clean (no panics, no unhandled errors)
## Verify
**Harness:** End-to-end test harness that simulates mixed workload.
**Integration test**`tests/it_e2e_api.rs`:
1. `a1_cli_ingest_and_agent_query_concurrent`
- Spawn HTTP server with test pgvector DB
- CLI submits ingest batch (POST /ingest)
- Agent submits query (GET /query) in parallel
- Both complete within 30s, both return 200/202
2. `a2_ingest_idempotency_holds`
- CLI submits (ingest_id_a) → job_id_1
- Agent submits same (ingest_id_a) → job_id_1 (identical)
- Different (ingest_id_b) → job_id_2 (different)
3. `a3_multi_project_federation_sorts_globally`
- Ingest sample data into two projects (poimen, agent-rust)
- Query "root cause" (no project specified)
- Results include nodes from both projects
- Sorted by rerank_score globally (not per-project)
4. `a4_skills_list_excludes_drafts_by_default`
- GET /memory/skills → returns promoted skills only
- GET /memory/skills?loadable=false with admin key → includes drafts
5. `a5_project_status_metrics_accurate`
- Ingest 50 chunks
- GET /memory/projects/poimen/status
- Asserts: total_chunks ≈ 50, last_ingest_at is recent, standing_queries count > 0
6. `a6_rate_limit_enforced`
- Set rate limit to 5 req/hour for testing
- Send 6 GET /query requests
- First 5 succeed, 6th returns 429
7. `a7_federation_timeout_partial_results`
- Mock slow project (10s response time)
- Query with timeout_seconds=2
- Results from fast project, warning about slow project
8. `a8_no_cascading_failures`
- Inject error in embeddings service (simulate 500)
- GET /query returns 503, not cascading to other endpoints
- Other endpoints (ingest, skills) still work
9. `a9_logs_clean_no_panics`
- Capture stderr during test
- Grep for "panic", "unwrap", "expect" — should not appear
- All errors should be explicit Result types, not crashes
10. `a10_health_check_always_responds`
- Server is under heavy load (rate limit tests, concurrent ingest)
- GET /health still returns 200 within 100ms
**Command:** `cargo test -p mem-cli e2e_api -- --nocapture`
**Manual verification (smoke test):**
```bash
# Start server
cargo run -p mem-cli -- serve --port 8080 &
sleep 2
# Ingest via HTTP
curl -X POST -H "apikey: test" http://localhost:8080/memory/ingest \
-d '{
"project": "poimen",
"source": "manual:smoke",
"records": [...],
"ingest_id": "abc123"
}'
# → expect 202, job_id
# Query
curl -H "apikey: test" "http://localhost:8080/memory/query?query=test"
# → expect 200, results array
# Skills
curl -H "apikey: test" http://localhost:8080/memory/skills
# → expect 200, skills array
# Project status
curl -H "apikey: test" http://localhost:8080/memory/projects/poimen/status
# → expect 200, metadata
# Rate limit test
for i in {1..11}; do
curl -H "apikey: test" "http://localhost:8080/memory/query?query=test" \
-w "HTTP %{http_code}\n"
done
# → expect first 10 to succeed, 11th to be 429
```
## False Pass
- Testing only happy path (all services available, no errors). Must include:
- Embedding service down → 503
- Slow project in federation → partial results + warning
- Rate limit near boundary (9/10, 10/10, 11/10 reqs)
- CLI and agent workloads not truly concurrent (sequential test masquerades as parallel). Use `tokio::join_all` or spy on timing to verify parallel execution.
- Idempotency tested once; never tested with expiry or multiple projects.
- Metrics never cross-checked against actual DB state. total_chunks reported but not verified against SELECT COUNT.
- No error injection. If the API is untested with failures, cascading failures are invisible until production.
## Traps
- Server startup latency: tests must wait for port to be available (sleep or retry logic).
- Test isolation: if tests share a DB, idempotency cache pollution breaks test N+1. Use separate test DB per test or reset cache between runs.
- Timing: federation timeout at 2s is tight; if the machine is slow, test becomes flaky. Mock time instead of real delays.
- Concurrent writes to JSONL log: if two ingest tasks write simultaneously, atomicity of the log is at risk. Ensure the log is single-writer or uses locking.
---
**Gate outcome:** All M3.5.x tasks green AND a1a10 pass → M3.5 gate is green. CLI and agents can work with the API concurrently without blocking, race conditions, or idempotency issues.
Background: [DESIGN.md § Distributed API Layer](../DESIGN.md#distributed-api-layer-homelab-frontend)