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DeadpoolmineDeadpoolmine/systematic-research-skills/skills/paper-writing/SKILL.md

paper-writing

Skill14 starsChanged 4 months agoMITView on GitHub

Use when writing or polishing academic papers. Use when the user mentions writing a paper, system paper, AI paper, polishing a draft, academic writing, or needs hierarchical logic flow for consistency.

36 other projects use a version of this.

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Projects with it also use ml-training-recipe, replication and 9 more.

Other files people use alongside this one.

Files found in the same public projects as a version of this one, more often than they turn up anywhere else. Each project counts once, large collections count for less, and this file's own repository is left out.
  • getcompanion-aiSkill

    ml-training-recipe

    Find implementable ML training recipes from papers, datasets, docs, and code. Use when the user wants to fine-tune, train, reproduce, or choose a practical ML method, dataset, hyperparameter setup, or benchmark recipe.

    Also in 3 projects that use this

  • getcompanion-aiSkill

    replication

    Plan a replication of a paper, claim, or benchmark, and execute only after an explicit environment choice. Use when the user asks to replicate results, reproduce an experiment, verify a claim empirically, or build a replication package.

    Also in 3 projects that use this

  • brainbytes-devSkill

    alpha-research

    Also in 3 projects that use this

  • JaimeParkerSkill

    paper-code-audit

    Perform three-way cross-validation of a research paper by comparing the original paper text (via Zotero), official code implementation (via Git), and personal Obsidian notes. Use this skill whenever the user wants to "audit a paper", "verify paper claims against code", "cross-check notes with implementation", "triangulate paper + code + notes", "find discrepancies between paper and code", or mentions wanting a deep, structured comparison of a paper's claims against its implementation and their own notes. Also trigger when the user asks to "analyze this paper thoroughly" with code available, or when they want to systematically reconcile what the paper says, what the code does, and what their notes claim.

    Also in 3 projects that use this

  • JimLiuSkill

    pdf-explore

    Use this skill when the user has attached a PDF, paper, report, or other document and the answer needs content from more than one place in it: summarize the methods or any other section, compare sections, find where a topic is discussed, read a value or label off a figure or chart, or find/list/extract every instance of something across the whole document (datasets, benchmarks, citations, figures, table rows, accession numbers — including appendices). Skip it only for a single lookup of 1–4 pages quoted in your very next response — `read_file(pages=[...])` attaches pages as images that are dropped from context after one turn, so multi-section answers end up re-reading the same ranges repeatedly. Parses the PDF once in the Python kernel: `pdf_pages` (pages as persistent text), `pdf_outline` (TOC), `pdf_scan` (rank pages by relevance), `pdf_map`/`pdf_extract` (per-page summary / structured fields via parallel haiku calls). For PDF creation/manipulation, use reportlab/pypdf directly.

    Also in 4 projects that use this

  • Yusong-EnceladusSkill

    research-review

    Get a deep critical review of research from GPT via Codex MCP. Use when user says "review my research", "help me review", "get external review", or wants critical feedback on research ideas, papers, or experimental results.

    Also in 6 projects that use this

  • +1 more from getcompanion-ai

The file

We split this skill into the rules it gives an agent

9 rules. 0 are common, 7 are distinctive, and 2 are very specific to this project.

  • 0

    Common

    Most of the 26 edited versions we read keep these.

  • 7

    Distinctive

    This author's own choices. Worth a look.

  • 2

    Very specific

    Tied to their project's names, files or tools. Probably skip.

  • Common
  • Distinctive
  • Very specific
  1. Distinctive:

    Core principle: Write mode builds from ideas.

    line 17
  2. Distinctive:

    Every level commits to git.

    line 32
  3. Distinctive:

    When polishing an existing draft, HLS documents MUST be generated — not just discussed verbally.

    line 52
  4. Very specific:

    Do NOT proceed to L1 until: target venue determined, 6 core points written to docs/systematic-research/plans/stream-L0.md, each point …

    line 68
  5. Distinctive:

    Do NOT batch all 6 points into a single message.

    line 69
  6. Distinctive:

    Do NOT proceed to L2 until: each Section proposed ONE AT A TIME, name confirmed, A→B→C flow chain defined and confirmed, figures placed, L1 …

    line 74
  7. Distinctive:

    Do NOT present all Sections at once.

    line 75
  8. Very specific:

    Do NOT proceed to L3 until: skeleton copied to paper/, every Section drafted by its OWN parallel agent (all dispatched simultaneously, one …

    line 79
  9. Distinctive:

    Do NOT write Sections sequentially.

    line 80

“Common” is measured: kept by at least 6 in 10 of the 26 edited versions of this file we could read. “Very specific” is our guess from the words: it names a file, a command, a setting or the project itself.

Keep what fits and drop the rest. Your version, ready for your agents.
Files
SKILL.md

Paper Writing — Hierarchical Logic Stream (HLS)

When to Use

ScenarioModePath
Starting a paper from scratchWriteFull HLS: L0 → L1 → L2 → L3
Polishing an existing draft (no HLS)PolishExtract L0/L1 from draft → critical review → L2/L3
Polishing an existing draft (HLS exists)PolishCritical review L0/L1 → L2/L3
Language polish only (draft is structurally sound)Polish-liteSkip L0/L1. Use existing structure, run L2/L3 for prose

Core principle: Write mode builds from ideas. Polish mode extracts structure from a draft. Both use the same HLS levels — only the starting point differs.

Overview

4-level refinement. Each level validates before descending. No skipping. No merging.

LevelRoleReference
L0Judge — pressure-test thesis, determine venuel0-core-idea.md
L1Architect — design custom Section flow chainsl1-chapter-structure.md
L2Builder — draft/revise Sectionsl2-parallel-writing.md
L3Auditor — cross-validate L0↔L1↔L2l3-consistency-check.md

Venue-driven discovery: Target venue determined at L0. All resources (skeleton, blueprint, writing guide) auto-discovered by exploring templates/ — never hardcoded.

Every level commits to git.

Universal Interaction Protocol

All L0/L1 confirmations use clickable options — never free-text. The user clicks, does not type.

InteractionOption Pattern
Venue selectionList discovered venues as clickable options (e.g., "NeurIPS (9pg)", "ICML (8pg)", "AAAI (7pg)", "OSDI (12pg)"), mark recommendation
Point judgment"PASS — [reason]" / "WEAK — [what's missing]" / "REJECT — [why]" as selectable options
Section name2-3 name options with purpose, mark recommendation
Flow chainAccept / Reorder / Add step / Remove step / Revise
Figure placementAccept / Move X to step Y / Add at step Z
Polish issue"Accept suggestion" / "Revise — [counter-proposal]" / "Skip — not relevant"
Proceed"Confirmed → next" / "Let me revise this"

Every prompt to the user MUST end with a set of clickable options. L0 and L1 each specify which options apply at which step.

Polish Mode

When polishing an existing draft, HLS documents MUST be generated — not just discussed verbally.

  1. If no L0/L1 exists — read draft → extract implicit HLS → critical think silently (identify issues, form 2-3 suggestions) → present to user → discuss → write docs/systematic-research/plans/stream-L0.md and stream-L1.md → commit
  2. If L0/L1 exist — critical review: points still valid? chains match draft? → critical think (2-3 issues + suggestions) → present → discuss → update L0/L1
  3. Invoke L2 — parallel revision following (revised) flow chains + writing guide
  4. Invoke L3 — consistency check (7 structural + prose checks). Polish complete when all checks pass.

Polish-lite (language only): User says "just polish the language" → use writing guide for voice/pitfalls → L2 revise prose → L3 consistency. Do NOT restructure.

Write Mode (Full HLS)

Standard flow: L0 → L1 → L2 → L3. Start from ideas, end with paper.

Hard Gates

<HARD-GATE-L0> Do NOT proceed to L1 until: target venue determined, 6 core points written to `docs/systematic-research/plans/stream-L0.md`, each point discussed ONE AT A TIME and judged PASS, NOT rejected, user confirmed each point individually. Do NOT batch all 6 points into a single message. Ask one → judge → user confirms → next. **Every challenge MUST pass the causal test:** "would solving the root cause eliminate this?" Weak links = reject or remove the challenge. </HARD-GATE-L0><HARD-GATE-L1> Do NOT proceed to L2 until: each Section proposed ONE AT A TIME, name confirmed, A→B→C flow chain defined and confirmed, figures placed, L1 document accumulated incrementally and user approved. Do NOT present all Sections at once. Propose Section N → discuss → confirm name → define chain → confirm chain → next Section. </HARD-GATE-L1><HARD-GATE-L2> Do NOT proceed to L3 until: skeleton copied to `paper/`, every Section drafted by its OWN parallel agent (all dispatched simultaneously, one per Section), each Section follows its L1 flow chain, abstract written (5-sentence formula, consistent with all Sections), user reviewed each Section. Do NOT write Sections sequentially. Dispatch all Section agents at once. </HARD-GATE-L2><HARD-GATE-L3> Paper NOT complete until: all 7 consistency checks pass (6 structural + 1 fine-grained line-by-line prose polish), report shows zero issues. </HARD-GATE-L3>

Process Flow

digraph hls {
    rankdir=TB;
    "Start" [shape=oval];
    "L0: Judge + Venue\n[l0-core-idea.md]" [shape=box];
    "User OK?" [shape=diamond];
    "Commit L0" [shape=box];
    "L1: Architect\n[l1-chapter-structure.md]" [shape=box];
    "User OK?" [shape=diamond];
    "Commit L1" [shape=box];
    "L2: Build\n[l2-parallel-writing.md]" [shape=box];
    "User OK?" [shape=diamond];
    "Commit L2" [shape=box];
    "L3: Audit\n[l3-consistency-check.md]" [shape=box];
    "7 checks pass?" [shape=diamond];
    "Commit final" [shape=box];
    "Done" [shape=oval];

    "Start" -> "L0: Judge + Venue\n[l0-core-idea.md]";
    "L0: Judge + Venue\n[l0-core-idea.md]" -> "User OK?"; "User OK?" -> "L0: Judge + Venue\n[l0-core-idea.md]" [label="no"];
    "User OK?" -> "Commit L0" [label="yes"]; "Commit L0" -> "L1: Architect\n[l1-chapter-structure.md]";
    "L1: Architect\n[l1-chapter-structure.md]" -> "User OK?"; "User OK?" -> "L1: Architect\n[l1-chapter-structure.md]" [label="no"];
    "User OK?" -> "Commit L1" [label="yes"]; "Commit L1" -> "L2: Build\n[l2-parallel-writing.md]";
    "L2: Build\n[l2-parallel-writing.md]" -> "User OK?"; "User OK?" -> "L2: Build\n[l2-parallel-writing.md]" [label="no"];
    "User OK?" -> "Commit L2" [label="yes"]; "Commit L2" -> "L3: Audit\n[l3-consistency-check.md]";
    "L3: Audit\n[l3-consistency-check.md]" -> "7 checks pass?"; "7 checks pass?" -> "L2: Build\n[l2-parallel-writing.md]" [label="no"];
    "7 checks pass?" -> "Commit final" [label="yes"]; "Commit final" -> "Done";
}

Quick Reference

LevelOutputKey ActionRef
L0docs/systematic-research/plans/stream-L0.mdVenue + judge 6 points, reject until clearl0
L1docs/systematic-research/plans/stream-L1.mdPropose 2-3 custom structures, define A→B→C chainsl1
L2paper/ dirWrite: draft Sections + abstract. Polish: revise Sections + abstract following writing guidel2
L3Consistency reportRun 7 checks (6 structural + 1 prose), fix root causes. Polish-lite also runs L3l3

Git

git commit -m "L0: core idea for <topic>"   # docs/systematic-research/plans/stream-L0.md
git commit -m "L1: structure for <topic>"   # docs/systematic-research/plans/stream-L1.md
git commit -m "L2: draft for <topic>"       # paper/
git commit -m "L3: final for <topic>"       # paper/

Red Flags

  • "The core idea is clear enough, let's start writing" → return to L0
  • "We can figure out the details while writing" → return to L0
  • "This point is obvious, no need to write it down" → return to L0
  • "We can't write anything until experiments are finished" → return to L0 (draft mode exists)
  • "We can just make up placeholder numbers without marking them" → stop
  • "One commit at the end is fine" → return to current level
  • "I'll check consistency after the paper is accepted" → return to L3
  • "We need three challenges to match three designs" → return to L0 (challenges are determined by evidence, not symmetry)
  • "This challenge is related to the root cause somehow" → return to L0 (causal link must be direct, strong, and testable)

Anti-Patterns

  • Writing before clarifying → L0 must be committed before any prose
  • Soft judgement → use rejection criteria mechanically
  • Editing skeleton in-place → copy to paper/ first; templates are read-only
  • Big bang commit → four commits, one per level
  • Hardcoding paths → discover from venue, never assume skeleton location

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