> ## Documentation Index
> Fetch the complete documentation index at: https://docs.doomberg.me/llms.txt
> Use this file to discover all available pages before exploring further.

# Sentiment & Macro Skills

> Reference for sentiment.get, macro.dashboard, universe.list, economic.calendar, fda.calendar, commodity.prices, forex.rates, crypto.prices, and vix.term_structure — the archive-backed sentiment and macro skills exposed to AI agents.

Sentiment and macro skills surface news/social sentiment, macro indicators, calendars, and cross-asset prices from the Ithaca archive. Macro indicators come from **FRED**; the rest come from the **community archive**.

<Callout type="info">
  Every result includes the [provenance envelope](/skills/overview#the-provenance-envelope). Calendar skills return *upcoming* events; price skills return the latest archive snapshot.
</Callout>

## Skill summary

| Skill ID             | Tool name            | Source            | Runtime     | Description                                          |
| -------------------- | -------------------- | ----------------- | ----------- | ---------------------------------------------------- |
| `sentiment.get`      | `sentiment_get`      | archive-community | interactive | News/social sentiment score for a ticker             |
| `macro.dashboard`    | `macro_dashboard`    | fred              | interactive | Macro indicator dashboard (CPI, rates, unemployment) |
| `universe.list`      | `universe_list`      | archive-community | interactive | Predefined universes (S\&P 500, Russell 2000, etc.)  |
| `economic.calendar`  | `economic_calendar`  | archive-community | interactive | Upcoming economic releases                           |
| `fda.calendar`       | `fda_calendar`       | archive-community | interactive | FDA approval dates (biotech catalysts)               |
| `commodity.prices`   | `commodity_prices`   | archive-community | interactive | Spot + futures for commodities                       |
| `forex.rates`        | `forex_rates`        | archive-community | interactive | FX spot rates                                        |
| `crypto.prices`      | `crypto_prices`      | archive-community | interactive | Crypto spot + 24h volume                             |
| `vix.term_structure` | `vix_term_structure` | archive-community | interactive | VIX futures curve by maturity                        |

***

## sentiment.get

Aggregate news + social sentiment score for a ticker, with a time series.

**Arguments**

| Name          | Type      | Required | Default             | Description                 |
| ------------- | --------- | -------- | ------------------- | --------------------------- |
| `symbol`      | string    | yes      | —                   | Ticker symbol               |
| `sources`     | string\[] | no       | `["news","social"]` | `news`, `social`, `analyst` |
| `from`        | ISO date  | no       | `now - 30d`         | Range start                 |
| `to`          | ISO date  | no       | `now`               | Range end                   |
| `granularity` | string    | no       | `daily`             | `daily` or `weekly`         |

**Source**: `archive-community`

**Example**

```json theme={null}
sentiment_get({ "symbol": "GME", "from": "2025-06-01" })
```

```json theme={null}
{
  "skill_id": "sentiment.get",
  "data": {
    "symbol": "GME",
    "current_score": 0.42, "score_7d_avg": 0.18, "score_30d_avg": -0.05,
    "series": [
      { "date": "2025-06-24", "score": 0.51, "n_mentions": 8200 },
      { "date": "2025-06-25", "score": 0.38, "n_mentions": 6100 }
    ]
  },
  "provenance": { "source": "archive-community", "freshness": { "as_of": "2025-06-27T18:00:00Z", "lag_seconds": 3600 }, "cost": { "credits": 2, "tier": "free" }, "warnings": [] }
}
```

***

## macro.dashboard

Macro indicator dashboard — CPI, Fed funds, unemployment, GDP, 10Y yield, etc.

**Arguments**

| Name              | Type      | Required | Default  | Description                                                       |
| ----------------- | --------- | -------- | -------- | ----------------------------------------------------------------- |
| `indicators`      | string\[] | no       | core set | FRED series IDs (e.g. `["CPIAUCSL","FEDFUNDS","UNRATE","DGS10"]`) |
| `as_of`           | ISO date  | no       | latest   | Snapshot date                                                     |
| `lookback_months` | int       | no       | `12`     | History to include                                                |

**Source**: `fred`

**Example**

```json theme={null}
macro_dashboard({ "indicators": ["CPIAUCSL","FEDFUNDS","UNRATE","DGS10"] })
```

```json theme={null}
{
  "skill_id": "macro.dashboard",
  "data": {
    "as_of": "2025-06-27",
    "indicators": [
      { "id": "CPIAUCSL", "name": "CPI All Urban", "value": 318.4, "yoy_pct": 0.032, "release": "2025-06-12" },
      { "id": "FEDFUNDS", "name": "Fed Funds Rate", "value": 0.0525, "yoy_pct": 0.0, "release": "2025-06-18" },
      { "id": "UNRATE", "name": "Unemployment", "value": 0.041, "yoy_pct": 0.004, "release": "2025-06-06" },
      { "id": "DGS10", "name": "10Y Treasury", "value": 0.0432, "yoy_pct": 0.0018, "release": "2025-06-27" }
    ]
  },
  "provenance": { "source": "fred", "freshness": { "as_of": "2025-06-27T20:00:00Z", "lag_seconds": 3600 }, "cost": { "credits": 2, "tier": "free" }, "warnings": [] }
}
```

***

## universe.list

Predefined universes — S\&P 500, Russell 2000, Nasdaq 100, sector ETFs, etc.

**Arguments**

| Name       | Type     | Required | Default | Description                          |
| ---------- | -------- | -------- | ------- | ------------------------------------ |
| `universe` | string   | no       | —       | Specific universe (omit to list all) |
| `as_of`    | ISO date | no       | latest  | Snapshot date                        |
| `limit`    | int      | no       | `500`   | Max constituents                     |

**Source**: `archive-community`

**Example**

```json theme={null}
universe_list({ "universe": "sp500", "limit": 10 })
```

```json theme={null}
{
  "skill_id": "universe.list",
  "data": {
    "universe": "sp500",
    "as_of": "2025-06-01",
    "constituents": ["AAPL","MSFT","NVDA","AMZN","META","GOOGL","BRK.B","LLY","AVGO","TSLA"],
    "total": 503
  },
  "provenance": { "source": "archive-community", "freshness": { "as_of": "2025-06-01T00:00:00Z", "lag_seconds": 2592000 }, "cost": { "credits": 1, "tier": "free" }, "warnings": [] }
}
```

***

## economic.calendar

Upcoming economic releases — date, time, indicator, consensus, prior.

**Arguments**

| Name         | Type     | Required | Default     | Description             |
| ------------ | -------- | -------- | ----------- | ----------------------- |
| `from`       | ISO date | no       | `now`       | Range start             |
| `to`         | ISO date | no       | `now + 14d` | Range end               |
| `country`    | string   | no       | `US`        | ISO country code        |
| `importance` | string   | no       | —           | `low`, `medium`, `high` |
| `limit`      | int      | no       | `50`        | Max events              |

**Source**: `archive-community`

**Example**

```json theme={null}
economic_calendar({ "to": "2025-07-04", "importance": "high" })
```

```json theme={null}
{
  "skill_id": "economic.calendar",
  "data": {
    "events": [
      { "date": "2025-07-03", "time": "08:30 ET", "country": "US", "indicator": "Nonfarm Payrolls", "consensus": 190000, "prior": 206000, "importance": "high" },
      { "date": "2025-07-03", "time": "08:30 ET", "country": "US", "indicator": "Unemployment Rate", "consensus": 0.041, "prior": 0.041, "importance": "high" }
    ]
  },
  "provenance": { "source": "archive-community", "freshness": { "as_of": "2025-06-27T20:00:00Z", "lag_seconds": 3600 }, "cost": { "credits": 1, "tier": "free" }, "warnings": [] }
}
```

***

## fda.calendar

FDA approval dates and advisory committee meetings — biotech catalysts.

**Arguments**

| Name     | Type     | Required | Default     | Description      |
| -------- | -------- | -------- | ----------- | ---------------- |
| `from`   | ISO date | no       | `now`       | Range start      |
| `to`     | ISO date | no       | `now + 90d` | Range end        |
| `symbol` | string   | no       | —           | Filter by ticker |
| `limit`  | int      | no       | `50`        | Max events       |

**Source**: `archive-community`

**Example**

```json theme={null}
fda_calendar({ "to": "2025-09-30" })
```

```json theme={null}
{
  "skill_id": "fda.calendar",
  "data": {
    "events": [
      { "date": "2025-07-22", "symbol": "MRNA", "event": "PDUFA", "drug": "mRNA-1273.214", "indication": "COVID booster" },
      { "date": "2025-08-15", "symbol": "BIIB", "event": "Advisory Committee", "drug": "lecanemab", "indication": "Alzheimer's" }
    ]
  },
  "provenance": { "source": "archive-community", "freshness": { "as_of": "2025-06-27T18:00:00Z", "lag_seconds": 86400 }, "cost": { "credits": 2, "tier": "basic" }, "warnings": [] }
}
```

***

## commodity.prices

Spot and front-month futures for commodities.

**Arguments**

| Name            | Type      | Required | Default | Description                                      |
| --------------- | --------- | -------- | ------- | ------------------------------------------------ |
| `symbols`       | string\[] | no       | all     | Commodity tickers (e.g. `["CL","GC","SI","NG"]`) |
| `as_of`         | ISO date  | no       | latest  | Snapshot date                                    |
| `include_curve` | bool      | no       | `false` | Include full futures curve                       |

**Source**: `archive-community`

**Example**

```json theme={null}
commodity_prices({ "symbols": ["CL","GC"], "include_curve": true })
```

```json theme={null}
{
  "skill_id": "commodity.prices",
  "data": {
    "as_of": "2025-06-27",
    "commodities": [
      { "symbol": "CL", "name": "WTI Crude", "spot": 78.42, "front_month": 78.15, "curve": [{ "expiry": "2025-07", "price": 78.15 }, { "expiry": "2025-08", "price": 77.90 }] },
      { "symbol": "GC", "name": "Gold", "spot": 2310.50, "front_month": 2312.00, "curve": [{ "expiry": "2025-08", "price": 2312.00 }] }
    ]
  },
  "provenance": { "source": "archive-community", "freshness": { "as_of": "2025-06-27T20:00:00Z", "lag_seconds": 900 }, "cost": { "credits": 1, "tier": "free" }, "warnings": [] }
}
```

***

## forex.rates

FX spot rates.

**Arguments**

| Name    | Type      | Required | Default | Description                                    |
| ------- | --------- | -------- | ------- | ---------------------------------------------- |
| `pairs` | string\[] | no       | majors  | FX pairs (e.g. `["EURUSD","GBPUSD","USDJPY"]`) |
| `as_of` | ISO date  | no       | latest  | Snapshot date                                  |

**Source**: `archive-community`

**Example**

```json theme={null}
forex_rates({ "pairs": ["EURUSD","USDJPY"] })
```

```json theme={null}
{
  "skill_id": "forex.rates",
  "data": {
    "as_of": "2025-06-27",
    "rates": [
      { "pair": "EURUSD", "rate": 1.0712, "change_pct": 0.18 },
      { "pair": "USDJPY", "rate": 160.84, "change_pct": -0.32 }
    ]
  },
  "provenance": { "source": "archive-community", "freshness": { "as_of": "2025-06-27T20:00:00Z", "lag_seconds": 60 }, "cost": { "credits": 1, "tier": "free" }, "warnings": [] }
}
```

***

## crypto.prices

Crypto spot prices with 24h volume.

**Arguments**

| Name                | Type      | Required | Default | Description                                 |
| ------------------- | --------- | -------- | ------- | ------------------------------------------- |
| `symbols`           | string\[] | no       | top 10  | Crypto symbols (e.g. `["BTC","ETH","SOL"]`) |
| `as_of`             | ISO date  | no       | latest  | Snapshot date                               |
| `include_24h_stats` | bool      | no       | `true`  | Include high/low/volume                     |

**Source**: `archive-community`

**Example**

```json theme={null}
crypto_prices({ "symbols": ["BTC","ETH"] })
```

```json theme={null}
{
  "skill_id": "crypto.prices",
  "data": {
    "as_of": "2025-06-27T20:00:00Z",
    "prices": [
      { "symbol": "BTC", "price": 61200.0, "change_24h_pct": 1.8, "high_24h": 61800, "low_24h": 60100, "volume_24h_usd": 28000000000 },
      { "symbol": "ETH", "price": 3420.0, "change_24h_pct": 2.4, "high_24h": 3450, "low_24h": 3380, "volume_24h_usd": 14000000000 }
    ]
  },
  "provenance": { "source": "archive-community", "freshness": { "as_of": "2025-06-27T20:00:00Z", "lag_seconds": 120 }, "cost": { "credits": 1, "tier": "free" }, "warnings": [] }
}
```

***

## vix.term\_structure

VIX futures curve by maturity — useful for reading vol regimes and roll yield.

**Arguments**

| Name              | Type     | Required | Default | Description                          |
| ----------------- | -------- | -------- | ------- | ------------------------------------ |
| `as_of`           | ISO date | no       | latest  | Snapshot date                        |
| `include_history` | bool     | no       | `false` | Include N days of curve history      |
| `history_days`    | int      | no       | `30`    | Days of history if `include_history` |

**Source**: `archive-community`

**Example**

```json theme={null}
vix_term_structure({ "as_of": "2025-06-27" })
```

```json theme={null}
{
  "skill_id": "vix.term_structure",
  "data": {
    "as_of": "2025-06-27",
    "vix_spot": 13.82,
    "curve": [
      { "expiry": "2025-07-16", "days": 19, "price": 14.20 },
      { "expiry": "2025-08-20", "days": 54, "price": 14.85 },
      { "expiry": "2025-09-17", "days": 82, "price": 15.40 },
      { "expiry": "2025-10-22", "days": 117, "price": 15.95 }
    ],
    "contango": true,
    "front_back_spread": 1.75
  },
  "provenance": { "source": "archive-community", "freshness": { "as_of": "2025-06-27T20:00:00Z", "lag_seconds": 900 }, "cost": { "credits": 1, "tier": "free" }, "warnings": [] }
}
```

## Next steps

<Card title="Volatility Skills" icon="wave-square" href="/skills/volatility">
  Realized vol, IV rank, variance risk premium, and regime classification — computed from archive closes.
</Card>

<Card title="Computed Analytics Skills" icon="calculator" href="/skills/computed">
  Correlations, factor exposures, DCF, portfolio optimization, Monte Carlo, and tearsheets.
</Card>