d-laub/dlaub-togo

scientific-writing-story

Use when starting a scientific manuscript from a code+results repo and you need to separate the real paper from the "research cloud" of parallel/abandoned experiments. Stage 1 of scientific-writing — produces story.md.

First seen Jun 17, 2026

Installation

$ npx skills add d-laub/dlaub-togo --skill scientific-writing-story

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More details

Agent compatibility

Declared targets from SKILL.md / docs. Unmarked agents are not listed — the skill may still install via the CLI.

Claude Code Declared
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Windsurf Not declared
Gemini CLI Not declared
Cline Not declared
OpenCode Not declared

Repository health

Default branch main
Open issues 0
Status Active

Skill metadata

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Declared agents claude-code
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type
technique

Package contents

Files included with this skill beyond the listing page.

  • skill md SKILL.md 3,232 B
  • docs SUMMARY.md 252 B

History

  1. First seen on skills.sh
  2. First recorded snapshot · 19 installs

SKILL.md

Scientific Writing — Stage 1: Find the Story

Overview

A research repo accumulates parallel and abandoned experiments. Before any outline or prose, establish ONE linear story: the thesis, the experiments that support it, and an explicit record of what was dropped. Output: docs/writing/<story-slug>/story.md in the consuming repo.

Do not write the story from your own assumptions. Map the repo, then converge with the user.

Method backbone — Steps 1–2

This stage is Steps 1–2 of the fifteen steps (detail: scientific-writing/fifteen-steps.md):

  • Step 1 — main point. The thesis is one short declarative sentence (subject + verb) that scopes the phenomenon and gives focus. Every later paragraph must illuminate it. It need not become the final title.
  • Step 2 — narrative arc. The arc answers what did we want to learn, why, what did we do, what do we know now, and follows the key transitions (question→answer, theory→evidence, data→interpretation). Prefer a two-part structure — the most memorable and publishable shape. Confirm which two-part scheme fits when you converge with the user (e.g. experiment 1 + experiment 2; simple model + complicated model; experiment + model to explain it; model + experiment to test it; observed pattern + model to explain it).

Process

  1. Map the research cloud. Dispatch Explore subagents (read-only) to inventory:

experiments/scripts, results/, figures/, notebooks, git log, and CLAUDE.md. Use superpowers:dispatching-parallel-agents if there are independent areas. Goal: a list of every experiment/result thread, each tagged candidate-main vs possibly-dropped.

  1. Converge with the user, ONE question at a time. Confirm: the working title, the single thesis, which threads are IN, which are DROPPED. Prefer multiple-choice. Do not proceed to writing until the user confirms the thesis and the in/out split.
  2. Write story.md (template below).

story.md template

# <Working title>
slug: <kebab-case-slug>

## Thesis
<one or two sentences — the single claim the paper makes>

## Narrative arc (linear)
Two-part scheme: <which Step-2 scheme, e.g. "experiment + model to explain it">
1. <beat> 2. <beat> 3. <beat> …  (the logical order the paper will argue in)

## Beat → artifacts
| Beat | Supporting artifacts (scripts / results / plots / notebooks) |
|------|------|
| <beat> | `path/to/script.py`, `results/x.csv`, `figures/y.svg` |

## Dropped / out of scope
- <thread> — why dropped (user-confirmed)

Red flags — STOP

  • Writing story.md before mapping the repo → map first.
  • Asserting a thesis the user hasn't confirmed → ask.
  • A beat with no backing artifact → either find it or it's not a beat.
  • An abandoned experiment silently included → it goes in Dropped.

Next stage

Once the user approves story.md, invoke scientific-writing-outline.