Home / ai-analyst-lab / ai-analyst · .claude/skills/forecast/SKILL.md · GitHub

forecast skillA

forecast is agent-read markdown (skill) from ai-analyst-lab/ai-analyst: Generate time-series forecasts and projections for metrics over future time periods. Use this skill whenever the user asks about future values, predictions, or projections — phrases like "what will X look like next month?", "forecast DAU for Q2", "project revenue", "estimate future growth", "what should we expect?", "predict next quarter", "where are we headed?", "extrapolate this trend", or explicitly invokes "/forecast". This skill is essential after trend analysis when you need to quantify wh.

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What the file says

# Skill: Forecast

## Purpose
Generate time-series forecasts for key metrics using the forecast_helpers
library. Supports naive baselines, seasonality detection, and exponential
smoothing — enough to answer "what should we expect next?" without complex
modeling.

## When to Use
- User asks "what will revenue look like next month?" or "forecast DAU"
- After trend analysis reveals a pattern worth projecting
- When sizing an opportunity that depends on future values
- Invoked as `/forecast`

## Invocation
`/forecast {metric}` — forecast the named metric
`/forecast {metric} periods=30` — specify forecast horizon
`/forecast {metric} method=holt_winters` — specify method

## Instructions

### Step 0: Understand the Business Context
Before diving into the forecast, ask clarifying questions if the user hasn't specified:
- **What decision depends on this forecast?** (e.g., capacity planning, budgeting, staffing, resource allocation)
- **Who will use it?** (exec summary vs technical deep-dive)
- **What's the forecast horizon?** (7 days, 30 days, 90 days, a quarter?)
…

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How to install

Latest version
mdr add ai-analyst-lab/ai-analyst/forecast@git:20260827.7ff2e25
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mdr add ai-analyst-lab/ai-analyst/forecast@sha256:43e061a0317b134b

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Versions

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git:20260827.7ff2e25 latest2026-08-27 7ff2e25 7,300 BA view

Audit of the latest version

A  17 of 17 checks passed. Deterministic, no model, same answer every run.
  • pass: Frontmatter block present
  • pass: Frontmatter declares a name
  • pass: Frontmatter declares a description
  • pass: Size between 200 bytes and 200 KB (7300 bytes)
  • pass: No zero-width or bidi control characters
  • pass: No instruction hidden inside an HTML comment
  • pass: No link to an exfiltration or paste host
  • pass: No credential-shaped string
  • pass: No instruction to send local credentials anywhere
  • pass: No text hidden with inline styles
  • pass: No prompt-injection phrasing
  • pass: No curl or wget piped into a shell
  • pass: No recursive delete of root, home or parent
  • pass: No instruction to read or print local credentials
  • pass: No base64 blob over 200 characters
  • pass: No link to a raw IP address
  • pass: No script tag

Source

GitHub

ai-analyst-lab/ai-analyst · 302 stars · license MIT · pushed 2026-09-22 · branch main

API

GET https://markdownregistry.com/api/v1/artifacts/art_wsilrf4f2cpabm6e
GET https://markdownregistry.com/api/v1/resolve?ref=ai-analyst-lab/ai-analyst/forecast
GET https://markdownregistry.com/api/v1/blob/43e061a0317b134b531feefece1f6cbf40f62cd2f758a3e7bfaf34f398c9ba4a

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