calibrate SKILL.md skillA

calibrate from skymanbp/sci-paper is an agent skill: a SKILL.md folder an AI agent loads when a task calls for it.

Install it, pinned
mdr add skymanbp/sci-paper/calibrate@git:20261002.7e38af6

Pins git:20261002.7e38af6 in mdr.lock. Pin the fingerprint instead.

Audit grade
A, 17 of 17 checks passed
Kind
SKILL.md skill
Repository
skymanbp/sci-paper
Path
skills/calibrate/SKILL.md
Versions recorded
6
Latest version
git:20261002.7e38af6, committed Oct 2, 2026
First version recorded
Aug 26, 2026
Size
15,590 bytes
Repository stars
6
License
a license file GitHub does not identify

Make the plugin yours. Walks the whole calibration chain for one field — corpus intake, profile extraction, per-axis calibration, optional model training, a held-out provenance measurement, and finding-level labelling against your own standard, style and target journal — then verifies the result. Every axis reports `measured`, `degraded` or `unmeasured` from its own floor; a stratum that cannot support a rate stays `unmeasured` rather than being given one. Produces evidence only: no threshold…

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

> **Not a policy source.** `docs/SCIPAPER_STANDARD.md` decides what good
> scientific prose is; nothing produced here can change that. Calibration
> supplies the *reference distributions* the advisory axes compare against, and
> `docs/architecture/EVALUATION.md` records what each one is worth. A corpus
> statistic cannot redefine a consequence class, create an authorship verdict,
> or turn an advisory into a blocker.

# calibrate — 校准:make the axes speak your field

## 0. What this skill does, and what it refuses

A fresh clone ships **no** corpus and **no** profile. Every `measured` axis in
this plugin is measured *against a reference distribution built from papers you
supply*, so out of the box the field-referenced axes are honestly `unmeasured`.
This skill is the path from that state to a calibrated one, for one field.

It refuses three things, and will say so rather than do them:

1. **It will not lower a floor to make a number appear.** If a section bucket
   holds fewer than 30 reference passages, or a labelling cell fewer than 20
   labels, the result is `unmeasured`. A rate computed from four observations is
   worse than no rate, because it reads like the others.
…

Read the whole file at its exact version.

How to install

The exact contents, by fingerprint
mdr add skymanbp/sci-paper/calibrate@sha256:57988415d9ba9271

The line at the top of this page pins the label git:20261002.7e38af6, 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.

Badge

mdr badge

[![mdr](https://markdownregistry.com/badge/art_xn7seavs6bukbw67.svg)](https://markdownregistry.com/a/art_xn7seavs6bukbw67)

5 badge image fetches in 30 days. What the badge shows.

Versions

The registry has recorded 6 versions of this file, between Aug 26, 2026 and Oct 2, 2026, about one every 7 days.

versioncommittedcommitsizeaudit
git:20261002.7e38af6 latest2026-10-02 7e38af6 15,590 BA view · diff
git:20260927.2c700542026-09-27 2c70054 15,080 BA view · diff
git:20260927.b25f4cd2026-09-27 b25f4cd 15,021 BA view · diff
git:20260927.de925a92026-09-27 de925a9 14,593 BA view · diff
git:20260827.b2a4a9b2026-08-27 b2a4a9b 14,656 BA view · diff
git:20260826.23e80b02026-08-26 23e80b0 13,645 BA view

Audit of the latest version

A  17 of 17 checks passed. Fixed automatic checks with no AI involved, so the same checks give the 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 (15590 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

skymanbp/sci-paper · 6 stars · license a license file GitHub does not identify · pushed 2026-10-17 · branch main

API

GET https://markdownregistry.com/api/v1/artifacts/art_xn7seavs6bukbw67
GET https://markdownregistry.com/api/v1/resolve?ref=skymanbp/sci-paper/calibrate
GET https://markdownregistry.com/api/v1/blob/57988415d9ba927106de6b32b6dc41642398746c86ba8da85fbce07c8e2eaf31

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.

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mainline SKILL.md skill
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paper SKILL.md skill
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skymanbp/sci-paper · skills/physics/SKILL.md · 物理第一原则核查(测量原件,只产 finding,不改稿):量纲一致性、渐近极限、对称性/宇称/守恒律、信息论与统计不等式的前提、代数再推导、数值溯源、基础引用真实性、编译与交叉引用完整性。findings 走…
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Every file in skymanbp/sci-paper

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