demand-forecasting SKILL.md skillA
demand-forecasting from tinh2/skills-hub-registry is an agent skill: a SKILL.md folder an AI agent loads when a task calls for it.
mdr add tinh2/skills-hub-registry/demand-forecasting@v2.0.1Pins v2.0.1 in mdr.lock. Pin the fingerprint instead.
- Audit grade
- A, 17 of 17 checks passed
- Kind
- SKILL.md skill
- Repository
- tinh2/skills-hub-registry
- Path
analysis/demand-forecasting/SKILL.md- Versions recorded
- 4
- Latest version
- v2.0.1, committed Sep 2, 2026
- First version recorded
- Mar 1, 2026
- Size
- 12,206 bytes
- Repository stars
- 22
- License
- none declared
Analyze demand forecasting systems — time-series decomposition (ARIMA, Prophet, ETS), seasonal and event-driven demand modeling, booking curve and pickup analysis, cancellation prediction, forecast accuracy metrics (MAPE, bias), and model retraining pipelines.
Collected from public GitHub. Every version is saved exactly as it was and never changes. Install it at an exact version with the mdr tool, and every file is checked before it reaches your agent. The main file is checked against the SHA-256 fingerprint recorded here, and the others against the fingerprints GitHub keeps for its source commit. The automatic checks below grade the latest version, and the same checks always give the same file the same grade.
What the file says
You are an autonomous demand forecasting analyst for travel, hospitality, and commerce businesses. Do NOT ask the user questions. Analyze forecasting models, data pipelines, feature engineering, and accuracy metrics, then produce a comprehensive demand forecasting analysis. TARGET: $ARGUMENTS If arguments are provided, use them to focus the analysis (e.g., "booking curves", "seasonal decomposition", "cancellation model", specific product or market). If no arguments, perform a full forecasting system audit. ============================================================ PHASE 1: FORECASTING SYSTEM DISCOVERY ============================================================ Step 1.1 -- Model Architecture Scan for forecasting infrastructure: - Statistical models: ARIMA/SARIMA, exponential smoothing (ETS), Holt-Winters - ML models: Prophet, XGBoost, LightGBM, neural networks (LSTM, Transformer) - Ensemble methods: model stacking, weighted averaging, selection by horizon - Hierarchical forecasting: top-down, bottom-up, middle-out, reconciliation - Model serving: batch predictions, real-time inference, scheduled retraining …
Read the whole file at its exact version.
How to install
mdr add tinh2/skills-hub-registry/demand-forecasting@sha256:6113dcf60f147c4aThe line at the top of this page pins the label v2.0.1, which is what most people want. This one pins the sha256 fingerprint of the contents instead, so it survives a label being moved. Either way the exact version is written to mdr.lock, and mdr install downloads and checks those contents again, so it installs them exactly or stops with an error.
[](https://markdownregistry.com/a/art_ijmizwehuffy4w2v)
4 badge image fetches in 30 days. What the badge shows.
Versions
The registry has recorded 4 versions of this file, between Mar 1, 2026 and Sep 2, 2026, about one every 62 days.
| version | committed | commit | size | audit | |
|---|---|---|---|---|---|
| v2.0.1 latest | 2026-09-02 | 5713ecc | 12,206 B | A | view · diff |
| v2.0.0 | 2026-03-18 | 851800b | 12,309 B | A | view · diff |
| v1.0.0 | 2026-03-13 | 0aafe73 | 10,556 B | A | view · diff |
| v1.0.0 | 2026-03-01 | 38b2b87 | 10,819 B | A | view |
Audit of the latest version
- pass: Frontmatter block present
- pass: Frontmatter declares a name
- pass: Frontmatter declares a description
- pass: Size between 200 bytes and 200 KB (12206 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
tinh2/skills-hub-registry · 22 stars · license none declared · pushed 2026-10-28 · branch main
API
GET https://markdownregistry.com/api/v1/artifacts/art_ijmizwehuffy4w2v GET https://markdownregistry.com/api/v1/resolve?ref=tinh2/skills-hub-registry/demand-forecasting GET https://markdownregistry.com/api/v1/blob/6113dcf60f147c4ae558c978d3ba94c3c90e7f4bb5202ddaff67fe7b1661ae66
Your AI assistant does the legwork. You hear about the deals worth your word. Hand yours the standing instructions at modelranch.com and it joins the network that reads files like this one.
Guides: the SKILL.md format and its required fields · what to check before you install a skill · how to pin a skill to an exact version · where to find agent skills · keeping a team on the same skills · which agent file does what.