vincenzoimp/academic-research-skills

develop-contribution

Use when creating a new contribution (analysis, experiment, dataset, software, reproduction) or regularizing a draft folder into badge compliance with its LaTeX report.

소스 보기

사용 방법

  1. 설치 명령을 복사하고 자신의 에이전트 환경에 설치하기 전에 소스 패키지를 확인하세요.
  2. 필요한 도구, 인증 정보, 지원 환경은 원본 문서에서 확인하세요.
  3. 입력과 원하는 산출물을 설명하고 출처와 결과를 대조하세요.
npx skills add https://github.com/vincenzoimp/academic-research-skills --skill develop-contribution

시작 전 확인

  • 설치에는 모델 구독, API 한도, 파일 접근 권한이 포함되지 않습니다.
  • 별점 수와 설치 수는 활동 지표이며 독립적인 품질·보안 검증이 아닙니다.
원본 Skill 문서

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

Develop Contribution

Create or regularize one contributions/<slug>/ folder: badge-general compliant, self-contained, with a report/report.tex detailed enough that paper writing never needs to re-read the code.

Read First

  • contributions/README.md — the badge-general contract
  • survey/survey.pdf, gaps section — when positioning a new contribution
  • references/methodology.md — evaluation, statistics, figure discipline
  • references/experiments.md — run logs and autonomous campaigns
  • references/reproduction.md — reproducing external work
  • references/ethics.md — data red flags
  • references/data.md — data placement and inter-contribution data

dependencies (when the contribution has shared/large data or consumes another contribution's output)

Before Building (both modes)

Fill the Positioning section of the contribution README:

  • the claim this contribution will support
  • the delta vs the nearest prior work (cite survey/SOTA citekeys)
  • the evidence plan: what will be measured or collected, and how
  • the falsifiability condition: what outcome would refute the claim

If the claim has no evidence path, stop and discuss with the user.

Create Mode

  1. Copy contributions/_template/ to contributions/<slug>/ (kebab-case

slug).

  1. Python code? Write the contribution's own pyproject.toml (name,

requires-python, dependencies), add "contributions/<slug>" to [tool.uv.workspace] members in the root pyproject.toml, run uv sync --all-packages from the root (plain uv sync prunes the members' dependencies on a package = false root). Genuinely conflicting dependencies → move the path to exclude, create a local venv, document it in the README.

  1. Develop inside the folder — free-form structure (src/, data/,

figures/, outputs/, notebooks). Follow references/methodology.md for any evaluation; keep a run log per references/experiments.md for every run that supports a claim, including autonomous campaigns. For reproductions of external work, follow references/reproduction.md.

  1. Fill the README badge checklist truthfully — every checked box has

evidence inside the folder. Check data against references/ethics.md.

  1. Write report/report.tex: motivation, positioning vs the SOTA (cite the

root .bib), method, setup, results with figures/tables, limitations. Build it: make contribution C=<slug>.

  1. Run make check.

Regularize Mode

  1. Inventory the draft folder: what exists, what it claims, what is missing

against the badge checklist.

  1. Reorganize in place — keep provenance (note original filenames when

renaming), capture the environment, verify the run path works end-to-end, record data provenance and ethics flags.

  1. Continue with Create Mode steps 4–6.

Rules

  • Self-contained: no imports from other contributions; tooling worth

sharing becomes its own contribution referenced in the README. If the input is another contribution's output, declare it and read it in place — never copy (see references/data.md).

  • Exploratory results never masquerade as confirmed evidence — label them.
  • Negative results are results: report them in report.tex.

Done When

  • Badge checklist fully and truthfully checked, report.pdf built,

workspace coherent, make check passes

관련 작업

같은 저장소의 Skills

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모든 Skills