195 lines
9.4 KiB
Text
195 lines
9.4 KiB
Text
{# Default analyst-onboarding welcome prompt for "da analyst setup".
|
||
Rendered server-side by src/welcome_template.py. Edit this file to change
|
||
the OSS default; admins override per-instance via /admin/welcome.
|
||
|
||
Available context (see docs/welcome-template.md for the full reference):
|
||
instance.name, instance.subtitle
|
||
server.url, server.hostname
|
||
sync_interval — string from instance.yaml
|
||
data_source.type — keboola | bigquery | local
|
||
tables — list of {name, description, query_mode}
|
||
metrics.count, metrics.categories
|
||
marketplaces — list of {slug, name, plugins:[name]}
|
||
user.email, user.name, user.is_admin, user.groups
|
||
now, today — datetime / date string
|
||
#}
|
||
# {{ instance.name }} — AI Data Analyst
|
||
|
||
This workspace is connected to {{ server.url }}.
|
||
{% if instance.subtitle %}Operated by **{{ instance.subtitle }}**.{% endif %}
|
||
|
||
## Rules
|
||
- Before computing any business metric: run `da metrics show <category>/<name>`
|
||
- **For canonical table list with query modes: `da catalog`.** `data/metadata/schema.json` covers `query_mode: "local"` tables only — for remote/hybrid tables it's incomplete. Treat `da catalog` as source of truth.
|
||
- Do not use DESCRIBE/SHOW COLUMNS — use `da schema <table>` instead
|
||
- Save work output to `user/artifacts/`
|
||
- Sync data regularly with `da sync`
|
||
- **Personal customizations go in `.claude/CLAUDE.local.md`, NOT here.** This file is regenerated by `da analyst setup --force`; edits here will be lost. CLAUDE.local.md is preserved across regeneration and uploaded on `da sync --upload-only`.
|
||
|
||
## Metrics Workflow
|
||
1. `da metrics list` — find the relevant metric ({{ metrics.count }} available, categories: {{ metrics.categories | join(", ") or "none yet" }})
|
||
2. `da metrics show <category>/<name>` — read SQL and business rules
|
||
3. Use the canonical SQL from the metric definition, adapt to the question
|
||
4. Never invent metric calculations — always check existing definitions first
|
||
|
||
## Data Sync
|
||
- `da sync` — download current data from server
|
||
- `da sync --docs-only` — just metadata and metrics (fast refresh)
|
||
- `da sync --upload-only` — upload sessions and local notes to server
|
||
- Data on the server refreshes every {{ sync_interval }}
|
||
|
||
## Available Datasets
|
||
{% for t in tables -%}
|
||
- `{{ t.name }}`{% if t.description %} — {{ t.description }}{% endif %}{% if t.query_mode == "remote" %} *(remote, queried on demand)*{% endif %}
|
||
{% else -%}
|
||
- _No tables registered yet — ask an admin to register tables in the dashboard._
|
||
{% endfor %}
|
||
|
||
{% if marketplaces -%}
|
||
## Plugins available to you
|
||
{% for mp in marketplaces -%}
|
||
- **{{ mp.name }}** ({{ mp.slug }}): {{ mp.plugins | map(attribute="name") | join(", ") }}
|
||
{% endfor %}
|
||
{% endif -%}
|
||
|
||
## Remote Queries (BigQuery) — when data isn't on the laptop
|
||
|
||
Not every table is synced. Tables registered with `query_mode: "remote"` live in
|
||
BigQuery, accessed server-side via DuckDB's BQ extension — no parquet on disk.
|
||
Tables you don't see in `data/parquet/` may still be queryable.
|
||
|
||
### Discovery first
|
||
|
||
```
|
||
da catalog --json | jq '.[] | {name, source_type, query_mode}' # see all tables + their modes
|
||
da schema <table> # columns + types
|
||
da describe <table> -n 5 # sample rows
|
||
```
|
||
|
||
For local-mode tables, query directly with `da query "SELECT … FROM <table>"`.
|
||
|
||
### Three patterns for `query_mode: "remote"` tables
|
||
|
||
| Pattern | Tool | Use when |
|
||
|---------|------|----------|
|
||
| **`da fetch`** (preferred) | materializes a filtered subset locally → query the snapshot | repeated questions on same slice |
|
||
| **`da query --remote`** | one-shot, server-side execution against BigQuery | single aggregate / cheap probe |
|
||
| **`da query --register-bq`** | hybrid joins between local snapshots and ad-hoc BQ subqueries | crossing local + remote |
|
||
|
||
### Permission model + cost — important
|
||
|
||
- BQ access goes through the **agnes server's GCE service account**, not your personal Google credentials. If a query fails with a permission error, the table is in a project the server SA cannot read — escalate to admin, do NOT try to authenticate yourself.
|
||
- Every BQ query bills the SA's GCP project for **bytes scanned**. A naive `SELECT * FROM <large_table>` can cost real money. ALWAYS:
|
||
- filter via `--where` on the partition column (typically a date)
|
||
- list specific columns in `--select` — column-store BQ skips the rest, cheaper
|
||
- run `--estimate` first when unsure of the table size or partitioning
|
||
|
||
### `da fetch` discipline
|
||
|
||
```
|
||
# 1. ESTIMATE first — refuses to fetch without knowing the cost
|
||
da fetch <table> --select col1,col2 --where "date >= DATE_SUB(CURRENT_DATE(), INTERVAL 30 DAY)" --estimate
|
||
|
||
# 2. If reasonable, fetch as a named snapshot
|
||
da fetch <table> --select col1,col2 --where "..." --as my_recent
|
||
|
||
# 3. Query the local snapshot
|
||
da query "SELECT col1, COUNT(*) FROM my_recent GROUP BY 1"
|
||
|
||
# 4. List + drop snapshots when done
|
||
da snapshot list
|
||
da snapshot drop my_recent
|
||
```
|
||
|
||
Rules of thumb:
|
||
- ALWAYS list specific columns in `--select`. Avoid implicit SELECT *.
|
||
- ALWAYS include a `--where` for remote tables; otherwise add `--limit`.
|
||
- ALWAYS run `--estimate` first when the table is `partition_by` / `clustered_by`
|
||
per `da schema`, or could plausibly exceed 1 GB local bytes.
|
||
- Reuse snapshots across questions in the same conversation — `da snapshot list`
|
||
before fetching.
|
||
|
||
### Snapshot freshness — when to refresh
|
||
|
||
Snapshots are point-in-time copies. They go stale as the source data updates (most BQ tables refresh daily; check `sync_schedule` per `da catalog`). For each new conversation:
|
||
|
||
```
|
||
da snapshot list # see existing snapshots + their ages
|
||
da snapshot drop my_recent # drop stale ones
|
||
da fetch <table> --select ... --where ... --as my_recent # re-fetch
|
||
```
|
||
|
||
If the question is time-sensitive (e.g. "today's orders"), assume any snapshot older than the table's `sync_schedule` is stale and refresh.
|
||
|
||
### Hybrid query example — local + remote in one query
|
||
|
||
`da query --register-bq` lets a single SQL statement join a local table with an ad-hoc BQ subquery. The BQ subquery runs first (server-side), result registered as a DuckDB view, then the joined query runs locally.
|
||
|
||
```
|
||
da query \
|
||
--register-bq "traffic=SELECT date, country, SUM(views) AS views \
|
||
FROM \`prj.web_analytics.sessions\` \
|
||
WHERE date >= DATE_SUB(CURRENT_DATE(), INTERVAL 30 DAY) \
|
||
GROUP BY 1, 2" \
|
||
--sql "SELECT o.date, o.country, o.revenue, t.views, o.revenue / NULLIF(t.views,0) AS rev_per_view \
|
||
FROM orders o \
|
||
JOIN traffic t ON o.date = t.date AND o.country = t.country \
|
||
ORDER BY 1 DESC"
|
||
```
|
||
|
||
The BQ subquery MUST contain `WHERE` and/or `GROUP BY` to keep the registered result manageable (target: under 500K rows, well under 100 MB). Multiple `--register-bq` flags can compose multiple BQ sources. For complex SQL, use `--stdin` mode (`echo '{"register_bq":{...},"sql":"..."}' | da query --stdin`).
|
||
|
||
### BigQuery SQL flavor for `--where`
|
||
|
||
Source-typed `bigquery` tables use BigQuery dialect, not DuckDB:
|
||
|
||
- Date literal: `DATE '2026-01-01'`
|
||
- Timestamp literal: `TIMESTAMP '2026-01-01 00:00:00 UTC'`
|
||
- Now: `CURRENT_DATE()`, `CURRENT_TIMESTAMP()`
|
||
- Date arithmetic: `DATE_SUB(CURRENT_DATE(), INTERVAL 30 DAY)`
|
||
- Regex: `REGEXP_CONTAINS(col, r'pattern')` (raw string!)
|
||
- Cast: `CAST(x AS INT64)` (NOT `INT`)
|
||
|
||
### When the table you want isn't in `da catalog`
|
||
|
||
The table may exist in BigQuery but not be registered with Agnes yet. Two options:
|
||
|
||
1. **Ad-hoc one-shot** — register a BQ subquery as a view inline, no admin needed
|
||
if the agnes server SA has BQ access:
|
||
```
|
||
da query --register-bq "live=SELECT * FROM \`project.dataset.table\` WHERE date >= '...' LIMIT 1000" \
|
||
--sql "SELECT * FROM live"
|
||
```
|
||
2. **Ask admin to register** the table with `query_mode: "remote"` so it shows up
|
||
in `da catalog` and supports `da fetch` / `da query --remote`. This is the
|
||
right path for any table you'll query repeatedly.
|
||
|
||
### Deeper guidance
|
||
|
||
For the full protocol, including hybrid-query examples, snapshot hygiene, and
|
||
when NOT to use `da fetch`, run:
|
||
|
||
```
|
||
da skills show agnes-data-querying
|
||
```
|
||
|
||
## Corporate Memory
|
||
|
||
Rules injected by `da sync` from the server's corporate knowledge base live in `.claude/rules/km_*.md`. They are automatically loaded by Claude Code on every session start.
|
||
|
||
- `km_<id>.md` — mandatory rules (always enforced)
|
||
- `km_approved.md` — approved guidance (confidence × recency ranked)
|
||
|
||
Run `da sync` to refresh. Rules are pruned automatically when items are revoked.
|
||
|
||
## Directory Structure
|
||
- `data/` — read-only data downloaded from server
|
||
- `data/parquet/` — table data in Parquet format
|
||
- `data/duckdb/` — local analytics DuckDB database
|
||
- `data/metadata/` — profiles, schema, metrics cache
|
||
- `user/` — your workspace (persistent across syncs)
|
||
- `user/artifacts/` — analysis outputs, reports, charts
|
||
- `user/sessions/` — Claude Code session logs
|
||
- `.claude/CLAUDE.local.md` — your personal notes + workspace customizations. **Never overwritten by `da analyst setup --force`.** Uploaded to the server on `da sync --upload-only`. Put any local-only Claude instructions, project-specific reminders, or temporary notes here — NOT in CLAUDE.md (this file is regenerated from a template).
|
||
|
||
_Hello {{ user.name or user.email }} — generated {{ today }}._
|