alva

仓库: alva-ai/skills
安装量: 76
排名: #10325

安装

npx skills add https://github.com/alva-ai/skills --skill alva
Alva
What is Alva
Alva is an agentic finance platform. It provides unified access to 250+
financial data sources spanning crypto, equities, ETFs, macroeconomic
indicators, on-chain analytics, and social sentiment -- including spot and
futures OHLCV, funding rates, company fundamentals, price targets, insider and
senator trades, earnings estimates, CPI, GDP, Treasury rates, exchange flows,
DeFi metrics, news feeds, social media and more!
What Alva Skills Enables
The Alva skill connects any AI agent or IDE to the full Alva platform. With
it you can:
Access financial data
-- query any of Alva's 250+ data SDKs
programmatically, or bring your own data via HTTP API or direct upload.
Run cloud-side analytics
-- write JavaScript that executes on Alva Cloud
in a secure runtime. No local compute, no dependencies, no infrastructure to
manage.
Build agentic playbooks
-- create data pipelines, trading strategies, and
scheduled automations that run continuously on Alva Cloud.
Deploy trading strategies
-- backtest with the Altra trading engine and
run continuous live paper trading.
Release and share
-- turn your work into a hosted playbook web app at
https://yourusername.playbook.alva.ai/playbook-name/version/index.html
, and share it with the world.
In short: turn your ideas into a forever-running finance agent that gets things
done for you.
Capabilities & Common Workflows
1. ALFS (Alva FileSystem)
The foundation of the platform. ALFS is a globally shared filesystem with
built-in authorization. Every user has a home directory; permissions control who
can read and write each path. Scripts, data feeds, playbook assets, and shared
libraries all live on ALFS.
Key operations: read, write, mkdir, stat, readdir, remove, rename, copy,
symlink, chmod, grant, revoke.
2. JS Runtime
Run JavaScript on Alva Cloud in a secure V8 isolate. The runtime has access to
ALFS, all 250+ SDKs, HTTP networking, LLM access, and the Feed SDK. Everything
executes server-side -- nothing runs on your local machine.
3. SDKHub
250+ built-in financial data SDKs. To find the right SDK for a task, use the
two-step retrieval flow:
Pick a partition
from the index below.
Call
GET /api/v1/sdk/partitions/:partition/summary
to see module
summaries, then load the full doc for the chosen module.
SDK Partition Index
Partition
Description
spot_market_price_and_volume
Spot OHLCV for crypto and equities. Price bars, volume, historical candles.
crypto_futures_data
Perpetual futures: OHLCV, funding rates, open interest, long/short ratio.
crypto_technical_metrics
Crypto technical & on-chain indicators: MA, EMA, RSI, MACD, Bollinger, MVRV, SOPR, NUPL, whale ratio, market cap, FDV, etc. (20 modules)
crypto_exchange_flow
Exchange inflow/outflow data for crypto assets.
crypto_fundamentals
Crypto market fundamentals: circulating supply, max supply, market dominance.
crypto_screener
Screen crypto assets by technical metrics over custom time ranges.
company_crypto_holdings
Public companies' crypto token holdings (e.g. MicroStrategy BTC).
equity_fundamentals
Stock fundamentals: income statements, balance sheets, cash flow, margins, PE, PB, ROE, ROA, EPS, market cap, dividend yield, enterprise value, etc. (31 modules)
equity_estimates_and_targets
Analyst price targets, consensus estimates, earnings guidance.
equity_events_calendar
Dividend calendar, stock split calendar.
equity_ownership_and_flow
Institutional holdings, insider trades, senator trading activity.
stock_screener
Screen stocks by sector, industry, country, exchange, IPO date, earnings date, financial & technical metrics. (9 modules)
stock_technical_metrics
Stock technical indicators: beta, volatility, Bollinger, EMA, MA, MACD, RSI-14, VWAP, avg daily dollar volume.
etf_fundamentals
ETF holdings breakdown.
macro_and_economics_data
CPI, GDP, unemployment, federal funds rate, Treasury rates, PPI, consumer sentiment, VIX, TIPS, nonfarm payroll, retail sales, recession probability, etc. (20 modules)
technical_indicator_calculation_helpers
50+ pure calculation helpers: RSI, MACD, Bollinger Bands, ATR, VWAP, Ichimoku, Parabolic SAR, KDJ, OBV, etc. Input your own price arrays.
feed_widgets
Social & news data feeds: news, Twitter/X, YouTube, Reddit, podcasts, web search (Brave, Grok).
ask
General news and market articles.
You can also bring your own data by uploading files to ALFS or fetching from
external HTTP APIs within the runtime.
4. Altra (Alva Trading Engine)
A feed-based event-driven backtesting engine for quantitative trading
strategies. A trading strategy IS a feed: all output data (targets, portfolio,
orders, equity, metrics) lives under a single feed's ALFS path. Altra supports
historical backtesting and continuous live paper trading, with custom
indicators, portfolio simulation, and performance analytics.
5. Deploy on Alva Cloud
Once your data analytics scripts and feeds are ready, deploy them as scheduled
cronjobs on Alva Cloud. They run continuously on your chosen schedule (e.g.
every hour, every day). Grant public access so anyone -- or any playbook page --
can read the data.
6. Build the Playbook Web App
After your data pipelines are deployed and producing data, build the playbook's
web interface. Create HTML5 pages that read from Alva's data gateway and
visualize the results. Follow the Alva Design System for styling, layout, and
component guidelines.
7. Release
Three phases:
Write HTML to ALFS
:
POST /api/v1/fs/write
the playbook HTML to
~/playbooks/{name}/index.html
.
Call release API
:
POST /api/v1/release/playbook
— creates DB records
and uploads HTML to CDN. Returns
playbook_id
(numeric).
Write ALFS files
Using the returned numeric playbook_id , write release files, draft files, and playbook.json to ALFS. See api-reference.md for details. The playbook.json must include a type field ( "dashboard" or "strategy" ) and a draft object. Omitting type causes wrong frontend routing; omitting draft causes the dashboard iframe to never load. Once released, the playbook is accessible at https://yourusername.playbook.alva.ai/playbook-name/version/index.html . -- ready to share with the world. Detailed sub-documents (read these for in-depth reference): Document Contents api-reference.md Full REST API reference (filesystem, run, deploy, user info, time series paths) jagent-runtime.md Writing jagent scripts: module system, built-in modules, async model, constraints feed-sdk.md Feed SDK guide: creating data feeds, time series, upstreams, state management altra-trading.md Altra backtesting engine: strategies, features, signals, testing, debugging deployment.md Deploying scripts as cronjobs for scheduled execution design-system.md Alva Design System: design tokens, colors, typography, font rules design-widgets.md Widget design: chart cards, KPI cards, table cards, feed cards, layout grid design-components.md Base component templates: dropdown, button, switch, modal, select, markdown design-playbook-trading-strategy.md Trading strategy playbook guideline adk.md Agent Development Kit: adk.agent() API, tool calling, ReAct loop, examples Setup All configuration is done via environment variables. Variable Required Description ALVA_API_KEY yes Your API key (create and manage at alva.ai ) ALVA_ENDPOINT no Alva API base URL. Defaults to https://api-llm.prd.alva.ai if not set Making API Requests All API examples in this skill use HTTP notation ( METHOD /path ). Every request requires the X-Alva-Api-Key header unless marked (public, no auth) . Curl templates for reference:

Authenticated

curl -s -H "X-Alva-Api-Key: $ALVA_API_KEY " " $ALVA_ENDPOINT {path}"

Authenticated + JSON body

curl -s -H "X-Alva-Api-Key: $ALVA_API_KEY " -H "Content-Type: application/json" \ " $ALVA_ENDPOINT {path}" -d '{body}'

Public read (no API key, absolute path)

curl
-s
"
$ALVA_ENDPOINT
{path}"
Discovering User Info
Retrieve your
user_id
and
username
:
GET /api/v1/me
→
Quick API Reference
See
api-reference.md
for full details.
Filesystem (
/api/v1/fs/
)
Method
Endpoint
Description
GET
/api/v1/fs/read?path={path}
Read file content (raw bytes) or time series data
POST
/api/v1/fs/write
Write file (raw body or JSON with
data
field)
GET
/api/v1/fs/stat?path={path}
Get file/directory metadata
GET
/api/v1/fs/readdir?path={path}
List directory entries
POST
/api/v1/fs/mkdir
Create directory (recursive)
DELETE
/api/v1/fs/remove?path={path}
Remove file or directory
POST
/api/v1/fs/rename
Rename / move
POST
/api/v1/fs/copy
Copy file
POST
/api/v1/fs/symlink
Create symlink
GET
/api/v1/fs/readlink?path={path}
Read symlink target
POST
/api/v1/fs/chmod
Change permissions
POST
/api/v1/fs/grant
Grant read/write access to a path
POST
/api/v1/fs/revoke
Revoke access
Paths:
~/data/file.json
(home-relative) or
/alva/home//...
(absolute).
Public reads use absolute paths without API key.
Run (
/api/v1/run
)
Method
Endpoint
Description
POST
/api/v1/run
Execute JavaScript (inline
code
or
entry_path
to a script on filesystem)
Deploy (
/api/v1/deploy/
)
Method
Endpoint
Description
POST
/api/v1/deploy/cronjob
Create a cronjob
GET
/api/v1/deploy/cronjobs
List cronjobs (paginated)
GET
/api/v1/deploy/cronjob/:id
Get cronjob details
PATCH
/api/v1/deploy/cronjob/:id
Update cronjob (name, cron, args)
DELETE
/api/v1/deploy/cronjob/:id
Delete cronjob
POST
/api/v1/deploy/cronjob/:id/pause
Pause cronjob
POST
/api/v1/deploy/cronjob/:id/resume
Resume cronjob
Release (
/api/v1/release/
)
Method
Endpoint
Description
POST
/api/v1/release/feed
Register feed (DB + link to cronjob task). Call after deploying cronjob.
POST
/api/v1/release/playbook
Release playbook for public hosting. Call after writing playbook HTML.
Name uniqueness
Both
name
in releaseFeed and releasePlaybook must be
unique within your user space. Use
GET /api/v1/fs/readdir?path=~/feeds
or
GET /api/v1/fs/readdir?path=~/playbooks
to check existing names before
releasing.
SDK Documentation (
/api/v1/sdk/
)
Method
Endpoint
Description
GET
/api/v1/sdk/doc?name={module_name}
Get full doc for a specific SDK module
GET
/api/v1/sdk/partitions
List all SDK partitions
GET
/api/v1/sdk/partitions/:partition/summary
Get one-line summaries of all modules in a partition
SDK retrieval flow
pick a partition from the index above → call
/partitions/:partition/summary
to see module summaries → call
/sdk/doc?name=...
to load the full doc for the chosen module.
Trading Pair Search (
/api/v1/trading-pairs/
)
Method
Endpoint
Description
GET
/api/v1/trading-pairs/search?q={q}
Search trading pairs by base asset (fuzzy match)
Search before writing code to check which symbols/exchanges Alva supports.
Supports exact match + prefix fuzzy search by base asset or alias.
Comma-separated queries for multiple searches.
GET /api/v1/trading-pairs/search?q=BTC,ETH
→ {"trading_pairs":[{"base":"BTC","quote":"USDT","symbol":"BINANCE_PERP_BTC_USDT","exchange":"binance","type":"crypto-perp","fee_rate":0.001,...},...]}
User Info
Method
Endpoint
Description
GET
/api/v1/me
Get authenticated user's id and username
Runtime Modules Quick Reference
Scripts executed via
/api/v1/run
run in a V8 isolate. See
jagent-runtime.md
for full details.
Module
require()
Description
alfs
require("alfs")
Filesystem (uses absolute paths
/alva/home//...
)
env
require("env")
userId
,
username
,
args
from request
net/http
require("net/http")
fetch(url, init)
for async HTTP requests
@alva/algorithm
require("@alva/algorithm")
Statistics
@alva/feed
require("@alva/feed")
Feed SDK for persistent data pipelines + FeedAltra trading engine
@alva/adk
require("@alva/adk")
Agent SDK for LLM requests —
agent()
for LLM agents with tool calling
@test/suite
require("@test/suite")
Jest-style test framework (
describe
,
it
,
expect
,
runTests
)
SDKHub
250+ data modules available via
require("@arrays/crypto/ohlcv:v1.0.0")
etc. Version suffix is optional
(defaults to
v1.0.0
). To discover function signatures and response shapes,
use the SDK doc API (
GET /api/v1/sdk/doc?name=...
).
Key constraints
No top-level
await
(wrap script in
(async () => { ... })();
). No Node.js builtins (
fs
,
path
,
http
). Module
exports are frozen.
Feed SDK Quick Reference
See
feed-sdk.md
for full details.
Feeds are persistent data pipelines that store time series data, readable via
filesystem paths.
const
{
Feed
,
feedPath
,
makeDoc
,
num
}
=
require
(
"@alva/feed"
)
;
const
{
getCryptoKline
}
=
require
(
"@arrays/crypto/ohlcv:v1.0.0"
)
;
const
{
indicators
}
=
require
(
"@alva/algorithm"
)
;
const
feed
=
new
Feed
(
{
path
:
feedPath
(
"btc-ema"
)
}
)
;
feed
.
def
(
"metrics"
,
{
prices
:
makeDoc
(
"BTC Prices"
,
"Close + EMA10"
,
[
num
(
"close"
)
,
num
(
"ema10"
)
]
)
,
}
)
;
(
async
(
)
=>
{
await
feed
.
run
(
async
(
ctx
)
=>
{
const
raw
=
await
ctx
.
kv
.
load
(
"lastDate"
)
;
const
lastDateMs
=
raw
?
Number
(
raw
)
:
0
;
const
now
=
Math
.
floor
(
Date
.
now
(
)
/
1000
)
;
const
start
=
lastDateMs
>
0
?
Math
.
floor
(
lastDateMs
/
1000
)
:
now
-
30
*
86400
;
const
bars
=
getCryptoKline
(
{
symbol
:
"BTCUSDT"
,
start_time
:
start
,
end_time
:
now
,
interval
:
"1h"
,
}
)
.
response
.
data
.
slice
(
)
.
reverse
(
)
;
const
closes
=
bars
.
map
(
(
b
)
=>
b
.
close
)
;
const
ema10
=
indicators
.
ema
(
closes
,
{
period
:
10
}
)
;
const
records
=
bars
.
map
(
(
b
,
i
)
=>
(
{
date
:
b
.
date
,
close
:
b
.
close
,
ema10
:
ema10
[
i
]
||
null
,
}
)
)
.
filter
(
(
r
)
=>
r
.
date
>
lastDateMs
)
;
if
(
records
.
length
>
0
)
{
await
ctx
.
self
.
ts
(
"metrics"
,
"prices"
)
.
append
(
records
)
;
await
ctx
.
kv
.
put
(
"lastDate"
,
String
(
records
[
records
.
length
-
1
]
.
date
)
)
;
}
}
)
;
}
)
(
)
;
Feed output is readable at:
~/feeds/btc-ema/v1/data/metrics/prices/@last/100
Data Modeling Patterns
All data produced by a feed should use
feed.def()
+
ctx.self.ts().append()
.
Do not use
alfs.writeFile()
for feed output data.
Pattern A -- Snapshot (latest-wins)
For data that represents current state
(company detail, ratings, price target consensus). Use start-of-day as the date
so re-runs overwrite.
const
today
=
new
Date
(
)
;
today
.
setHours
(
0
,
0
,
0
,
0
)
;
await
ctx
.
self
.
ts
(
"info"
,
"company"
)
.
append
(
[
{
date
:
today
.
getTime
(
)
,
name
:
company
.
name
,
sector
:
company
.
sector
}
,
]
)
;
Read
@last/1
for current snapshot,
@last/30
for 30-day history.
Pattern B -- Event log
For timestamped events (insider trades, news,
senator trades). Each event uses its natural date. Same-date records are
auto-grouped.
const
records
=
trades
.
map
(
(
t
)
=>
(
{
date
:
new
Date
(
t
.
transactionDate
)
.
getTime
(
)
,
name
:
t
.
name
,
type
:
t
.
type
,
shares
:
t
.
shares
,
}
)
)
;
await
ctx
.
self
.
ts
(
"activity"
,
"insiderTrades"
)
.
append
(
records
)
;
Pattern C -- Tabular (versioned batch)
For data where the whole set refreshes each run (top holders, EPS estimates). Stamp all records with the same run timestamp; same-date grouping stores them as a batch. const now = Date . now ( ) ; const records = holdings . map ( ( h , i ) => ( { date : now , rank : i + 1 , name : h . name , marketValue : h . value , } ) ) ; await ctx . self . ts ( "research" , "institutions" ) . append ( records ) ; Data Type Pattern Date Strategy Read Query OHLCV, indicators Time series (standard) Bar timestamp @last/252 Company detail, ratings Snapshot (A) Start of day @last/1 Insider trades, news Event log (B) Event timestamp @last/50 Holdings, estimates Tabular (C) Run timestamp @last/N See feed-sdk.md for detailed data modeling examples and deduplication behavior. Deploying Feeds Every feed follows a 6-step lifecycle: Write -- define schema + incremental logic with ctx.kv Upload -- write script to ~/feeds//v1/src/index.js Test -- POST /api/v1/run with entry_path to verify output Grant -- make feed public via POST /api/v1/fs/grant Deploy -- POST /api/v1/deploy/cronjob for scheduled execution Release -- POST /api/v1/release/feed to register the feed in the database (requires the task_id from the deploy step) Data Type Recommended Schedule Rationale Stock OHLCV + technicals 0 */4 * * * (every 4h) Markets update during trading hours Company detail, price targets 0 8 * * * (daily 8am) Changes infrequently Insider/senator trades 0 8 * * * (daily 8am) SEC filings are daily Earnings estimates 0 8 * * * (daily 8am) Updated periodically See deployment.md for the full deployment guide and API reference. Debugging Feeds Resetting Feed Data (development only) During development, use the REST API to clear stale or incorrect data. Do not use this in production.

Clear a specific time series output

DELETE /api/v1/fs/remove?path=~/feeds/my-feed/v1/data/market/ohlcv&recursive=true

Clear an entire group (all outputs under "market")

DELETE /api/v1/fs/remove?path=~/feeds/my-feed/v1/data/market&recursive=true

Full reset: clear ALL data + KV state (removes the data mount, re-created on next run)

DELETE /api/v1/fs/remove?path=~/feeds/my-feed/v1/data&recursive=true
Inline Debug Snippets
Test SDK shapes before building a full feed:
POST /api/v1/run
{"code":"const { getCryptoKline } = require(\"@arrays/crypto/ohlcv:v1.0.0\"); JSON.stringify(Object.keys(getCryptoKline({ symbol: \"BTCUSDT\", start_time: 0, end_time: 0, interval: \"1h\" })));"}
Altra Trading Engine Quick Reference
See
altra-trading.md
for full details.
Altra is a feed-based event-driven backtesting engine. A trading strategy IS a
feed: all output data lives under a single ALFS path. Decisions execute at bar
CLOSE.
const
{
createOHLCVProvider
}
=
require
(
"@arrays/data/ohlcv-provider:v1.0.0"
)
;
const
{
FeedAltraModule
}
=
require
(
"@alva/feed"
)
;
const
{
FeedAltra
,
e
,
Amount
}
=
FeedAltraModule
;
const
altra
=
new
FeedAltra
(
{
path
:
"~/feeds/my-strategy/v1"
,
startDate
:
Date
.
parse
(
"2025-01-01T00:00:00Z"
)
,
portfolioOptions
:
{
initialCash
:
1_000_000
}
,
simOptions
:
{
simTick
:
"1min"
,
feeRate
:
0.001
}
,
perfOptions
:
{
timezone
:
"UTC"
,
marketType
:
"crypto"
}
,
}
,
createOHLCVProvider
(
)
,
)
;
const
dg
=
altra
.
getDataGraph
(
)
;
dg
.
registerOhlcv
(
"BINANCE_SPOT_BTC_USDT"
,
"1d"
)
;
dg
.
registerFeature
(
{
name
:
"rsi"
/ ... /
}
)
;
altra
.
setStrategy
(
strategyFn
,
{
trigger
:
{
type
:
"events"
,
expr
:
e
.
ohlcv
(
"BINANCE_SPOT_BTC_USDT"
,
"1d"
)
}
,
inputConfig
:
{
ohlcvs
:
[
{
id
:
{
pair
:
"BINANCE_SPOT_BTC_USDT"
,
interval
:
"1d"
}
}
]
,
features
:
[
{
id
:
"rsi"
}
]
,
}
,
initialState
:
{
}
,
}
)
;
(
async
(
)
=>
{
await
altra
.
run
(
Date
.
now
(
)
)
;
}
)
(
)
;
Deployment Quick Reference
See
deployment.md
for full details.
Deploy feed scripts or tasks as cronjobs for scheduled execution:
POST /api/v1/deploy/cronjob
{"path":"~/feeds/btc-ema/v1/src/index.js","cron_expression":"0 /4 * * ","name":"BTC EMA Update"}
Cronjobs execute the script via the same jagent runtime as
/api/v1/run
. Max 20
cronjobs per user. Min interval: 1 minute.
After deploying a cronjob, register the feed, create a playbook draft, then
release the playbook for public hosting. The playbook HTML must already be
written to ALFS at
~/playbooks/{name}/index.html
via
fs/write
before
releasing.
Important
Feed names and playbook names must be unique within your user space. Before creating a new feed or playbook, use GET /api/v1/fs/readdir?path=~/feeds or GET /api/v1/fs/readdir?path=~/playbooks to check for existing names and avoid conflicts.

1. Release feed (register in DB, link to cronjob)

POST /api/v1/release/feed {"name":"btc-ema","version":"1.0.0","task_id":42} → {"feed_id":100,"name":"btc-ema","feed_major":1}

2. Create playbook draft (creates DB record + ALFS draft files automatically)

POST /api/v1/draft/playbook {"name":"btc-dashboard","type":"dashboard","description":"BTC market dashboard","feeds":[{"feed_id":100}]} → {"playbook_id":99,"playbook_version_id":200}

3. Release playbook (reads HTML from ALFS, uploads to CDN, writes release files automatically)

POST /api/v1/release/playbook
{"name":"btc-dashboard","version":"v1.0.0","feeds":[{"feed_id":100}]}
→
The playbook will be accessible at
https://username.playbook.alva.ai/{name}/{version}/index.html
.
Alva Design System
All Alva playbook pages, dashboards, and widgets must follow the Alva Design
System. The system defines design tokens (colors, spacing, shadows), typography
rules, and component/widget templates.
Key rules:
Font
Delight (Regular 400, Medium 500). No Semibold/Bold. Font files: Delight-Regular.ttf , Delight-Medium.ttf Page background : --b0-page (

ffffff

)
Semantic colors
:
--main-m3
(bullish/green),
--main-m4
(bearish/red),
--main-m1
(Alva theme/teal)
Charts
Use ECharts. Select colors from the chart palette in
design-system.md
. Grey only when >= 3 series.
Widgets
No borders on widget cards. Chart cards use dotted background;
table card has no background; other cards use
--grey-g01
.
Grid
8-column grid (web), 4-column grid (mobile). Column spans must sum to 8 per row. Reference documents (read for detailed specs when building playbook web apps): When Read Design tokens, typography, font rules, general guidelines design-system.md Widget types, chart/KPI/table/feed cards, grid layout design-widgets.md Component templates (button, dropdown, modal, select, switch, markdown) design-components.md Trading strategy playbook layout, sections, and content guidelines design-playbook-trading-strategy.md Filesystem Layout Convention Path Purpose ~/tasks//src/ Task source code ~/feeds//v1/src/ Feed script source code ~/feeds//v1/data/ Feed synth mount (auto-created by Feed SDK) ~/playbooks// Playbook web app assets ~/data/ General data storage ~/library/ Shared code modules Prefer using the Feed SDK for all data organization , including point-in-time snapshots. Store snapshots as single-record time series rather than raw JSON files via alfs.writeFile() . This keeps all data queryable through a single consistent read pattern ( @last , @range , etc.). Common Pitfalls @last returns chronological (oldest-first) order , consistent with @first and @range . No manual sorting needed. Time series reads return flat JSON records. Paths with @last , @range , etc. return JSON arrays of flat records like [{"date":...,"close":...,"ema10":...}] . Regular paths return file content with Content-Type: application/octet-stream . last(N) limits unique timestamps, not records. When multiple records share a timestamp (grouped via append() ), auto-flatten may return more than N individual records. The data/ in feed paths is the synth mount. feedPath("my-feed") gives ~/feeds/my-feed/v1 , and the Feed SDK mounts storage at /data/ . Don't name your group "data" or you'll get data/data/... . Public reads require absolute paths. Unauthenticated reads must use /alva/home//... (not ~/... ). Discover your username via GET /api/v1/me . Top-level await is not supported. Wrap async code in (async () => { ... })(); . require("alfs") uses absolute paths. Inside the V8 runtime, alfs.readFile() needs full paths like /alva/home/alice/... . Get your username from require("env").username . No Node.js builtins. require("fs") , require("path") , require("http") do not exist. Use require("alfs") for files, require("net/http") for HTTP. Altra run() is async. FeedAltra.run() returns a Promise . Always await it: const result = await altra.run(endDate); Altra decisions happen at bar CLOSE. Feature timestamps must use bar.endTime , not bar.date . Using bar.date introduces look-ahead bias. Altra lookback: feature vs strategy. Feature lookback controls how many bars the feature computation sees. Strategy lookback controls how many feature outputs the strategy function sees. They are independent. Cronjob path must point to an existing script. The deploy API validates the entry_path exists via filesystem stat before creating the cronjob. Always create a draft before releasing. POST /api/v1/release/playbook requires the playbook to already exist (created via POST /api/v1/draft/playbook ). Resource Limits Resource Limit V8 heap per execution 2 GB Write payload 10 MB max per request HTTP response body 128 MB max Max cronjobs per user 20 Min cron interval 1 minute Error Responses All errors return: {"error":{"code":"...","message":"..."}} HTTP Status Code Meaning 400 INVALID_ARGUMENT Bad request or invalid path 401 UNAUTHENTICATED Missing or invalid API key 403 PERMISSION_DENIED Access denied 404 NOT_FOUND File/directory not found 429 RATE_LIMITED Rate limit / runner pool exhausted 500 INTERNAL Server error
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