Is oraclaw-forecast safe to install?

SaferSkills independently audited oraclaw-forecast (Agent Skill) and scored it 100/100 (green). The audit ran 55 deterministic rules across Security, Supply Chain, Maintenance, Transparency, and Community; it found 0 high-severity and 0 lower-severity findings. The full rule-by-rule trace and per-finding evidence are below. Free, methodology-open.

CategoryWeightCategory scoreContribution

Securityprompt, exec, net, exfil, eval

35%

100

35.0 pts

Supply chainhash, typosquat, maintainer, lockfile

20%

100

20.0 pts

Maintenancestaleness, pinning, CI

15%

100

15.0 pts

TransparencySKILL.md, perms, README

15%

100

15.0 pts

Communityinstalls, verify, response

15%

100

15.0 pts

Findings & checks · 0 flagged

Securityscore 100 · 0 findings

✓—All security checks passedNo findings in this category for the latest scan.pass

Supply chainscore 100 · 0 findings

✓—All supply chain checks passedNo findings in this category for the latest scan.pass

Maintenancescore 100 · 0 findings

✓—All maintenance checks passedNo findings in this category for the latest scan.pass

Transparencyscore 100 · 0 findings

✓—All transparency checks passedNo findings in this category for the latest scan.pass

Communityscore 100 · 0 findings

✓—All community checks passedNo findings in this category for the latest scan.pass

The primary manifest — the file an agent reads to learn what this artifact does.

mission-control/packages/clawhub-skills/oraclaw-forecast/SKILL.md · 1 file

mission-control/packages/clawhub-skills/oraclaw-forecast/SKILL.md2.1 KB · Markdown

name: oraclaw-forecast

description: Time series forecasting for AI agents. ARIMA and Holt-Winters predictions with confidence intervals. Predict revenue, traffic, prices, or any sequential data. Sub-5ms inference.

version: 1.0.0

metadata:

openclaw:

requires:

env:

- ORACLAW_API_KEY

primaryEnv: ORACLAW_API_KEY

emoji: "📈"

homepage: https://web-olive-one-89.vercel.app/forecast

tags:

- forecasting

- time-series

- arima

- prediction

- revenue

- analytics

- holt-winters

price: 0.05

currency: USDC

OraClaw Forecast — Time Series Prediction for Agents

You are a forecasting agent that predicts future values from historical time series using ARIMA and Holt-Winters exponential smoothing.

When to Use This Skill

Use when the user or agent needs to:

Predict next N values from a data sequence (revenue, traffic, temperature, stock prices)
Get confidence intervals on forecasts ("between $80K and $120K with 95% confidence")
Detect trends, seasonality, and level shifts
Compare ARIMA (auto-fit) vs Holt-Winters (seasonal) approaches

Tools

`predict_forecast`

{
  "data": [100, 121, 133, 142, 155, 163, 178, 185, 192, 205, 218, 231],
  "steps": 6,
  "method": "arima"
}

Returns: forecast values + 95% confidence interval (lower/upper bounds).

For seasonal data, use Holt-Winters:

{
  "data": [362, 385, 432, 341, 382, 409, 498, 387, 473, 513, 582, 474],
  "steps": 4,
  "method": "holt-winters",
  "seasonLength": 4
}

Rules

ARIMA auto-detects the best (p,d,q) parameters. Use for non-seasonal or weakly seasonal data.
Holt-Winters requires seasonLength (e.g., 12 for monthly data with yearly seasonality, 7 for daily with weekly).
Minimum 10 data points for ARIMA, 2× seasonLength for Holt-Winters.
Confidence intervals widen the further you forecast — don't trust 30-step forecasts.
Best for: revenue forecasting, traffic prediction, demand planning, price trends.

Pricing

$0.05 per forecast. USDC on Base via x402. Free tier: 3,000 calls/month.

oraclaw-forecast— agent skill

Is oraclaw-forecast safe to install?

OraClaw Forecast — Time Series Prediction for Agents

When to Use This Skill

Tools

`predict_forecast`

Rules

Pricing

Audit the pieces. Scan the whole. Decide.