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bootloops-ai/skills

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26 stars 品質 66 トレンド 19MIT

BootLoops skills: working protocols and research skills for trustworthy quantitative work with AI agents, as plain-markdown Agent Skills and Claude Code / Codex plugins. MIT (scripts), CC BY 4.

概要

BootLoops 1.0 is a harness for large language models doing precision quantitative science. It has two halves. The computing packages, ports and engine upgrades are the toolkit, which lives in its own repository, bootloops, published beside this one by the same organization. This repository, skills, is the other half: the working protocols of the program, written as standalone instruction files an LLM agent can load and follow, plus their packaging as Claude Code and Codex plugins. The protocols are as much a part of the harness as the packages: the code supplies capability, these supply the discipline that makes its output trustworthy. The skills are plain markdown in the Agent Skills format (a SKILL.md with frontmatter: name, when to use, and a self-contained body), the format that Claude Code and a number of other agent tools read. None depends on any private infrastructure, and they are written so that any capable agent can follow them.

README

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BootLoops skills

BootLoops 1.0 is a harness for large language models doing precision quantitative science. It has two halves. The computing packages, ports and engine upgrades are the toolkit, which lives in its own repository, bootloops, published beside this one by the same organization. This repository, skills, is the other half: the working protocols of the program, written as standalone instruction files an LLM agent can load and follow, plus their packaging as Claude Code and Codex plugins. The protocols are as much a part of the harness as the packages: the code supplies capability, these supply the discipline that makes its output trustworthy.

The skills are plain markdown in the Agent Skills format (a SKILL.md with frontmatter: name, when to use, and a self-contained body), the format that Claude Code and a number of other agent tools read. None depends on any private infrastructure, and they are written so that any capable agent can follow them. They encode what “done” means: a result reproduces an independent route at points no fit ever saw, with a positive control proving the check can fail; integer-relation discipline with the constant ring declared before the search and refusal over invention when no relation is found; planted-truth controls that recover a known answer before any real data is touched; provenance bookkeeping so no oracle that fed a fit ever certifies the result; timing discipline (measure a small run before a big one); and the heavier protocols for proving with agents, simulating referees, auditing the literature behind a novelty claim, verifying bibliographies, and linting scientific prose for hype and honesty failures.

The roster

Twelve skills in two groups; skills/README.md has one line per skill on what each governs.

  • The protocol layer (general purpose; load these for any quantitative work): acceptance-gate, constant-recognition, planted-truth, independence-bookkeeping, timing-discipline, reading-contract, tool-stewardship.
  • The research skills (heavier machinery for specific kinds of work): prove-protocol, referee-sim, lit-review, ref-check, prose-lint.

The two groups are also the two plugins, bootloops-protocols and bootloops-research.

Scope and responsibility

These protocols make agent-produced results checkable; they do not replace review by a qualified person. The verdict labels used in the skills (CLOSED, VERIFIED-CLOSED) are internal grades; every BootLoops result was reviewed by the author before release.

Repository map

  • skills/: the library, one directory per skill. This is the single source of truth; every other copy in the repository is generated from it.
  • .claude/skills/bootloops-setup/: the installer skill, the only skill that is active when you open Claude Code
GitHub で README 全文を見る

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インストール

npx skillfish add bootloops-ai/skills
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