okhp3-outcome-modeling-core SKILL.md skillA
okhp3-outcome-modeling-core from okhp3/skillz is an agent skill: a SKILL.md folder an AI agent loads when a task calls for it.
mdr add okhp3/skillz/okhp3-outcome-modeling-core@v1.1.0Pins v1.1.0 in mdr.lock. Pin the fingerprint instead.
- Audit grade
- A, 17 of 17 checks passed
- Kind
- SKILL.md skill
- Repository
- okhp3/skillz
- Path
.agents/skills/okhp3-outcome-modeling-core/SKILL.md- Versions recorded
- 1
- Latest version
- v1.1.0, committed Aug 26, 2026
- Size
- 9,376 bytes
- Repository stars
- 3
- License
- MIT
Design and operationalize outcome models that compress noisy event histories into calibrated forecasts and constrained decisions. Use when a user asks about feature reduction, probability, expected value, aggregation, or moving a prediction method between sports, business, sales, advertising, finance, or prediction markets. Load a domain adapter when one fits.
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
# okhp3-outcome-modeling-core **OverKill Hill P³** · [overkillhill.com](https://overkillhill.com) · [github.com/OKHP3](https://github.com/OKHP3) Build a defensible model for systems where many noisy events contribute to a measurable outcome. The core separates the shared world model from the decision objective, so the same evidence can support forecasting, ranking, budgeting, or market comparison without confusing prediction with optimization. --- ## Scope | In scope | Out of scope | |----------|-------------| | Repeated event histories, state vectors, and aggregate outcomes | A universal algorithm that fits every dataset | | Feature reduction and diminishing-returns testing | Claims that a fixed feature count always explains 95% of outcomes | | Calibrated forecasts and decision-ready uncertainty | Presenting a forecast as certainty or advice without constraints | | Domain-adapter routing and handoff contracts | Live trading, betting, or political targeting | --- ## Core mental model Treat a complex system as a noisy, time-indexed process: ```text events -> entity state -> outcome estimate -> objective and constraints -> decision ``` …
Read the whole file at its exact version.
How to install
mdr add okhp3/skillz/okhp3-outcome-modeling-core@sha256:41a1e9992784257bThe line at the top of this page pins the label v1.1.0, 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_nq3dcnimw2q6yxzp)
5 badge image fetches in 30 days. What the badge shows.
Versions
The registry has recorded 1 version of this file, committed on Aug 26, 2026.
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 (9376 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
okhp3/skillz · 3 stars · license MIT · pushed 2026-11-06 · branch main
API
GET https://markdownregistry.com/api/v1/artifacts/art_nq3dcnimw2q6yxzp GET https://markdownregistry.com/api/v1/resolve?ref=okhp3/skillz/okhp3-outcome-modeling-core GET https://markdownregistry.com/api/v1/blob/41a1e9992784257bab60151720aae7e68ca50ebc4c8179a3cecb6e3d995ee448
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.