revenue-forecasting skillA
revenue-forecasting is agent-read markdown (skill) from varunk130/ai-gtm-skill-library: Revenue forecasting pipeline - bottoms-up pipeline forecast, tops-down model, ensemble blending, scenario analysis, and forecast calibration loop. Use when: revenue forecast, sales forecast, pipeline forecast, bookings forecast, NRR forecast, ARR forecast, forecast calibration, scenario planning, ensemble forecasting, board forecast..
Indexed from public GitHub and served as immutable, content-addressed versions. Install it pinned to an exact SHA-256 with the mdr CLI, and every file is verified against the hash recorded here before it reaches your agent. The deterministic audit below grades the latest version, and the same file always earns the same grade.
What the file says
# Revenue Forecasting (FORECAST Framework) Design a revenue-forecasting pipeline that produces a defensible, calibrated number - not a rep-roll-up that's been over-promised twice. FORECAST blends bottoms-up pipeline math with a tops-down model, runs scenarios, and closes the loop with calibration so the forecast improves quarter over quarter. ## Core Principle **A forecast is only as good as its calibration loop.** Most forecasts re-anchor every quarter and never learn. FORECAST treats forecasting as an *ensemble* of models with explicit error tracking, so the system gets more accurate over time. ## The FORECAST Framework | Letter | Stage | The Question | |--------|-------|--------------| | **F** | Foundations | What's the ARR / bookings definition, period boundary, and currency convention? | | **O** | Outlook (Bottoms-Up) | What does pipeline-weighted by stage and rep commit produce? | | **R** | Run-Rate Model | What does the time-series / cohort model produce independent of pipeline? | | **E** | Ensemble Blend | How are bottoms-up and tops-down blended, and what's the confidence band? | …
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How to install
mdr add varunk130/ai-gtm-skill-library/revenue-forecasting@git:20260522.2e90392mdr add varunk130/ai-gtm-skill-library/revenue-forecasting@sha256:e258a03003d3bfb3Pin to a label to follow the author's releases, or to a sha256 to freeze the exact bytes forever. Either way the resolved hash is written to mdr.lock, and mdr install reproduces it on any machine.
[](https://markdownregistry.com/a/art_xd7kfncyfxujzkas)
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Versions
| version | committed | commit | size | audit | |
|---|---|---|---|---|---|
| git:20260522.2e90392 latest | 2026-05-22 | 2e90392 | 6,178 B | A | view · diff |
| git:20260516.4225f52 | 2026-05-16 | 4225f52 | 6,212 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 (6178 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
varunk130/ai-gtm-skill-library · 6 stars · license MIT · pushed 2026-09-19 · branch master
API
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