bootloops-ai/skills

bootloops-setup

Set up the BootLoops protocol skills for this user.

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원본 Skill 문서

원본 저장소의 제목, 예시, 코드, 표, 링크, 이미지를 유지해 표시합니다.

bootloops-setup

BootLoops ships twelve working protocols in skills/ at the repository root. They are a library, not an installation: nothing in skills/ is active until the user chooses to activate it. This skill is the installer. Never activate anything without an explicit choice.

Procedure

  1. Show the roster. Present the two groups below (one line each). The

protocol layer is discipline for any quantitative work; the research skills are heavier machinery for specific tasks.

The protocol layer:

  • acceptance-gate — what "done" means: never-fit digits against an independent route
  • constant-recognition — integer-relation discipline: declared rings, height bounds, refusal over invention
  • planted-truth — synthetic-truth controls before real data
  • independence-bookkeeping — provenance of reference values; no oracle that fed a fit certifies the result
  • timing-discipline — measure a small run first; a multi-hour projection means restructure
  • reading-contract — sources-only assertion for document-reading instruments
  • tool-stewardship — consult the toolkit first, write code last, document for the next agent

The research skills:

  • prove-protocol — proving with agents: adversary-first pipelines, skeptic loops
  • referee-sim — pre-circulation audit: the strongest standard objection from every audience
  • lit-review — the literature audit behind a novelty claim: papers actually read, citation chains both directions
  • ref-check — bibliography verification against authoritative sources
  • prose-lint — scientific-prose linter: hype vocabulary, empty structures, agentless prose, honesty and number checks
  1. Ask what to activate. Offer: all twelve, the protocol layer only, the

research skills only, an individual selection, or none. Use the host's question/multi-select interface if it has one (in Claude Code, grouped multi-select questions fit within the four-option limit); otherwise ask in plain text. "None" is a fine answer — the library stays available to read or load ad hoc either way.

  1. Ask the scope. Project-level (.claude/skills/ in the user's project —

active only there) or user-level (~/.claude/skills/ — active in every project). Default to project-level if the user has no preference.

  1. Install. Copy each chosen skill's directory from skills/<name>/ in

this repository into the chosen location, keeping the directory name. Nothing else: no edits to the files, no extra registration step.

  1. Confirm. List what is now active and where. Note that an activated

skill still only engages when its work actually comes up; activation makes it discoverable, not mandatory. To deactivate one later, delete its directory from the install location. Re-run this setup any time to add or change the selection.

같은 저장소의 Skills

더 많은 Skills

모든 Skills
bootloops-ai
커뮤니티

acceptance-gate

The standard a computed result must meet before it may be called done. Use whenever an agent claims an integral is solved, a fit has closed, a formula is identified, or any quantitative answer is ready — the claim is not done until it passes this gate.

설치 수
4
GitHub Stars
6
업데이트
10월 1일
bootloops-ai
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constant-recognition

Discipline for integer-relation searches (PSLQ, LLL) that turn high-precision digits into exact constants. Use whenever recognizing a numerical value as a closed form, fitting boundary constants, or reporting that no closed form exists.

설치 수
4
GitHub Stars
6
업데이트
10월 1일
bootloops-ai
커뮤니티

independence-bookkeeping

Provenance rules that keep checks independent. Use when setting up any comparison, oracle, or reference value — and whenever tempted to certify a result with machinery that helped produce it.

설치 수
4
GitHub Stars
6
업데이트
10월 1일
bootloops-ai
커뮤니티

lit-review

Deep literature review behind a research project's novelty claims — a protocol whose one job is to prevent shortcuts. It demands the papers be actually read (nothing from memory), makes thoroughness falsifiable (read ledgers, search receipts, gap statements), tracks citation chains in both directions, and lists the places to look. Use before any novelty claim ships, when writing or reviewing a related-work section, and when refereeing.

설치 수
4
GitHub Stars
6
업데이트
10월 1일