# Aether Platform Integration — Cortex Tool Layer

> Last updated: 2026-04-30
> Status: Journal toolset complete — broader AE integration planned

This doc covers how Cortex/Inara integrates with the Aether Platform API, what's
implemented, what the data model looks like, and what's planned next.

---

## Overview

Cortex connects to the Aether Platform V3 API to give the orchestrator read/write
access to the user's knowledge base (Journals) and task data. Auth uses the same
`x-aether-api-key` + `x-account-id` headers as every other Aether client.

Config lives in `.env`:
```
AE_API_URL=https://dev-api.oneskyit.com
AE_API_KEY=...
AE_ACCOUNT_ID=...
AE_API_TIMEOUT=15
```

Tool implementation: `cortex/tools/ae_knowledge.py`
Tool registrations: `cortex/tools/__init__.py`

---

## V3 Search Engine

### Endpoint
```
POST /v3/crud/{obj_type}/search
```
For nested objects (journal_entry scoped to a journal):
```
POST /v3/crud/journal_entry/search
  ?for_obj_type=journal&for_obj_id={journal_id}
```

### Search body
```json
{
  "query_string": "fulltext search term",
  "and": [
    { "field": "tags",       "op": "icontains", "value": "networking" },
    { "field": "created_on", "op": "gte",        "value": "2026-01-01" }
  ],
  "or": [...],
  "page_size": 20,
  "page": 1,
  "order_by": "-updated_on"
}
```

**`query_string` vs `and` filters on `default_qry_str`:**
- `query_string` → triggers `MATCH(default_qry_str) AGAINST(... IN BOOLEAN MODE)` — uses the
  FULLTEXT index. Faster and supports boolean operators (`+word`, `-word`, `"phrase"`).
- `and` with `icontains` on `default_qry_str` → plain `LIKE '%term%'`. Slower, no index.

**Important:** `query_string` must be present for `and`/`or` filters to apply. When using
filters without a keyword query, pass `query_string: "%"` as a wildcard to activate the
filter path without restricting by keyword.

### Supported operators
| Operator | SQL | Notes |
|---|---|---|
| `eq` | `=` | exact match |
| `ne` | `!=` | not equal |
| `gt` / `gte` | `>` / `>=` | numeric, dates |
| `lt` / `lte` | `<` / `<=` | numeric, dates |
| `contains` / `icontains` | `LIKE '%v%'` | substring; both case-insensitive on MariaDB |
| `startswith` / `istartswith` | `LIKE 'v%'` | |
| `endswith` / `iendswith` | `LIKE '%v'` | |
| `like` | `LIKE` | raw LIKE pattern |
| `in` | `IN (...)` | value is a list |
| `is_null` / `is_not_null` | `IS NULL` / `IS NOT NULL` | no value needed |

### Sorting
`order_by` accepts any indexed field name. Prefix with `-` for descending:
- `-updated_on` (default for listing)
- `-created_on`
- `name`
- `-priority`

### Pagination
`page_size` (default 10, max ~100) + `page` (1-based).
Total count is in `response["meta"]["data_list_count"]` — not a top-level key.

---

## journal_entry Schema

Full table schema from `ae_describe journal_entry --detailed`:

| Field | Type | Indexed | Notes |
|---|---|---|---|
| `id_random` | varchar(22) | UNI | DB public ID field — but API responses return this as `journal_entry_id` (the Vision ID convention: `{obj_type}_id`). `id_random` key is `None` in responses. |
| `journal_id` | int | MUL | FK — use `for_obj_id` param in search |
| `name` | varchar(250) | MUL | Entry title |
| `short_name` | varchar(25) | | |
| `summary` | text | | Short summary (1–2 sentences) |
| `content` | text | | Full markdown content |
| `content_html` | text | | HTML version |
| `content_json` | longtext | | Structured content (editor format) |
| `content_encrypted` | longtext | | Optional encrypted content |
| `tags` | varchar(255) | MUL | Comma-separated string — filter with `icontains` |
| `type` / `type_code` | varchar | | Classification: type |
| `topic` / `topic_code` | varchar | | Classification: topic |
| `activity` / `activity_code` | varchar | | Classification: activity |
| `category_code` | varchar(25) | | Classification: category |
| `code` | varchar(20) | | Short entry code |
| `start_datetime` | datetime | MUL | Optional event start |
| `end_datetime` | datetime | | Optional event end |
| `seconds` / `hours` | int/decimal | | Duration |
| `priority` | tinyint | MUL | 1=low → 5=high |
| `status` | int | MUL | Status code (domain-specific) |
| `private` / `public` / `personal` / `professional` | tinyint | MUL | Visibility flags |
| `billable` | tinyint | | Billing flag |
| `enable` | tinyint NOT NULL | MUL | Soft-delete flag (default 1) |
| `hide` | tinyint | MUL | UI hide flag |
| `archive` | tinyint | MUL | Archived flag |
| `default_qry_str` | text | FULLTEXT | Auto-generated search target (name + content) |
| `data_json` | longtext | | Arbitrary structured data |
| `notes` | text | | Internal notes |
| `created_on` | timestamp NOT NULL | MUL | Auto-set on create |
| `updated_on` | timestamp | MUL | Auto-updated on change |

### journal Schema (top-level)

| Field | Type | Notes |
|---|---|---|
| `id_random` | varchar(22) | DB field — returned in API as `journal_id` |
| `name` | varchar(250) | Journal name |
| `summary` / `description` | text | |
| `type_code` | varchar(25) | Journal type |
| `enable` | tinyint | |
| `created_on` / `updated_on` | timestamp | |

---

## Current Tool Inventory

| Tool | Status | Notes |
|---|---|---|
| `ae_journal_list` | ✅ | Lists journals with id + name |
| `ae_journal_search` | ✅ | Fulltext + tag/date/type/status/priority filters; paginated |
| `ae_journal_entry_read` | ✅ | Full content by entry_id; configurable truncation |
| `ae_journal_entries_list` | ✅ | Browse a journal newest-first; paginated |
| `ae_journal_entry_create` | ✅ | Create with title, content, tags, summary |
| `ae_journal_entry_update` | ✅ | Patch any fields (title, content, tags, summary, enable) |
| `ae_journal_entry_disable` | ✅ | Soft-delete (enable=false) |
| `ae_journal_entry_append` | ✅ | Timestamped append to bottom |
| `ae_journal_entry_prepend` | ✅ | Timestamped prepend to top |
| `ae_task_list` | ✅ | agents_sync Kanban (admin only) |

---

## ae_journal_search — Current Signature

All filters are optional and combine with AND. At least one should be provided.

```python
ae_journal_search(
    query: str = "",          # fulltext via query_string (MATCH/AGAINST)
    journal_id: str = "",     # scope to a specific journal
    tags: str = "",           # icontains on tags field
    type_code: str = "",      # eq on type_code
    topic_code: str = "",     # eq on topic_code
    date_from: str = "",      # created_on gte  (YYYY-MM-DD)
    date_to: str = "",        # created_on lte  (YYYY-MM-DD, exclusive of time — use next day to include full day)
    sort_by: str = "updated", # updated | created | name | priority
    sort_order: str = "desc",
    status: int | None = None,
    priority: int | None = None,
    max_results: int = 10,
    page: int = 1,
)
```

**date_to boundary note:** `date_to='2026-01-17'` means `<= 2026-01-17 00:00:00`, which
excludes entries created later that day. Use `date_to='2026-01-18'` to include all of Jan 17.

---

## Planned: Broader AE Platform Integration

### Phase 1 — Journal Toolset (current)
Complete read/write/search for Journals and Journal Entries.

### Phase 2 — Tasks & Projects
- `ae_task_create` / `ae_task_update` / `ae_task_complete` on Aether tasks (not just agents_sync Kanban)
- Read project/task hierarchy

### Phase 3 — Knowledge Import Pipeline
- Script to walk markdown dirs, chunk by H2, create Journal entries
- Dedup via search-before-create pattern
- Tag and classify entries automatically via orchestrator

### Phase 4 — People & Contacts
- Read contact records (person, organization)
- Link journal entries to contacts

### Phase 5 — Calendar / Events
- `start_datetime` / `end_datetime` already on journal_entry
- Could expose time-scoped journal queries as a calendar view

---

## Notes on `tags` field

`tags` is stored as a raw comma-separated varchar(255), not a JSON array.
The API accepts a Python list on write (the `tags` PATCH key takes a list and the backend joins it).
On read, it comes back as a **string** (e.g. `"shelterluv, api"`), not a list — normalize before
displaying: `[t.strip() for t in tags_str.split(",") if t.strip()]`.
For filtering: use `icontains` on `tags` inside the `"and"` list, e.g.:
`{"field": "tags", "op": "icontains", "value": "networking"}`.
A tag search for "net" matches "networking" AND "subnet" — acceptable for now.
True per-tag filtering would require a tags junction table.

## Notes on `default_qry_str`

Auto-populated by the backend from `name` + content fields. Do not write to it directly.
FULLTEXT index supports boolean mode: `+required -excluded "exact phrase"`.
The `query_string` key in the search body triggers this path automatically.