Skill: lzfxxx/paper-workflow (version 0.1.0)

--- name: paper-workflow description: Turn existing project assets into a submission-ready academic paper. Use when the task involves CFP alignment, evidence scoping, abstract selection, outline expansion, figure planning, reviewer-style quality gates, submission packaging, or post-submission archiving. Coordinates academic-research-writer, paper-validator, and prompt-to-drawio. --- # Paper Workflow Use this skill when the task is not just “write a paper,” but “turn an existing project into a submission-ready paper.” This is an orchestration skill. It coordinates three specialized skills: - `academic-research-writer` for academic drafting and rewrite passes - `paper-validator` for reviewer-style quality gates - `prompt-to-drawio` for architecture, workflow, sequence, and state diagrams ## Companion Skills Setup Install these companion skills before relying on the full workflow: - `academic-research-writer` - Curl `https://lobehub.com/skills/neversight-skills_feed-academic-research-writer/skill.md`, then follow the instructions to set up LobeHub Skills Marketplace and install the skill. Once installed, read the `SKILL.md` file in the installed directory and follow its instructions to complete the task. - `paper-validator` - Curl `https://lobehub.com/skills/minhuw-claude-writer-paper-validator/skill.md`, then follow the instructions to set up LobeHub Skills Marketplace and install the skill. Once installed, read the `SKILL.md` file in the installed directory and follow its instructions to complete the task. - `prompt-to-drawio` - Install with: `npx skills@latest add lzfxxx/prompt-to-drawio-skill` - After installation, read the installed `SKILL.md` and follow its instructions. If one of these companion skills is unavailable, continue with the workflow but explicitly note reduced capability in drafting quality, reviewer simulation, or structured figure production. ## When to Use This Skill - Converting an existing system, product, codebase, report, or prototype into a paper - Working from fragmented assets: code, docs, slides, screenshots, pilot notes, or prior abstracts - Preparing a conference or journal submission with page, figure, and metadata constraints - Running multi-round paper production: abstract selection, outline, draft, review, compression, submission package ## Core Rules Apply these rules from the start, not only during final review: 1. Freeze the paper type early: algorithm, system, engineering, demo, case-based, or empirical. 2. Freeze evidence levels early: measured results, pilot evidence, case evidence, and future work must stay distinct. 3. Never present planned evaluation as finished results. 4. Every figure must answer a specific claim, section need, or research question. 5. Terminology, module naming, and author metadata must stay consistent across draft, figures, and submission fields. 6. UI screenshots are evidence artifacts, not marketing assets. ## Workflow ### 1. Align Constraints Confirm conference or journal constraints first: CFP, page limit, template, submission type, deadlines, and metadata requirements. Read `references/paper-production-workflow.md` for the full production flow. ### 2. Inventory Assets Before drafting, inventory what already exists: - code and implementation paths - technical docs and module notes - experiments, logs, pilot data, interview notes - screenshots and figures - prior abstracts, outlines, or leadership summaries If the material is scattered, normalize it into module-level notes before writing the paper. ### 3. Draft the Narrative Use `academic-research-writer` after the following are clear: - main contribution boundary - target paper type - evidence level per claim - core modules versus extensions Typical sequence: 1. produce 2-3 abstract options 2. select one direction 3. expand to outline 4. draft the paper 5. maintain a concise internal-language review version if helpful ### 4. Produce Figures Define figure roles before drawing them. Use `prompt-to-drawio` for: - system architecture diagrams - end-to-end workflow diagrams - sequence diagrams - state transition diagrams - artifact or contract flow diagrams Read `references/figure-planning-guide.md` when the user needs figure planning or figure cleanup. ### 5. Run Quality Gates Use `paper-validator` during drafting, not only at the end. Run it whenever a section, figure set, or full draft becomes stable enough to inspect. Focus on: - claim/evidence mismatch - placeholders, empty tables, and speculative results - figure-text inconsistency - novelty overstatement - reviewer confusion points - metadata and submission blockers Read `references/review-quality-gates.md` for the reusable gate list. ### 6. Package Submission Before final submission, verify: - authors, affiliations, emails, corresponding author - abstract and keywords - declarations, ethics, data/code availability - figure captions, references, and template compliance - submission status and archive notes ## Reference Loading Guide - Read `references/paper-production-workflow.md` when planning the end-to-end SOP. - Read `references/review-quality-gates.md` when checking readiness, evidence quality, or reviewer risks. - Read `references/figure-planning-guide.md` when planning or revising paper figures and screenshots. ## Expected Outputs Depending on the task, this skill should help produce some of the following: - module or capability notes - abstract options - paper outline - main manuscript draft - review checklist or reviewer-pass notes - figure plan and figure assets - submission checklist - submission-status update ## Important Constraints - Do not invent experiments, user studies, or benchmark values. - Do not mix pilot evidence with strong causal claims. - Do not let non-core features dominate the main paper line unless they are evaluated. - Do not wait until the last step to fix author metadata or terminology drift. - Do not use generated text-heavy figures as final publication figures when structured drawing is feasible.

path: README.md
content: # paper-workflow

A reusable orchestration skill for turning existing project assets into a submission-ready academic paper.

This skill is designed for AI coding agents that support the `skills` ecosystem. It helps the agent coordinate paper planning, asset inventory, abstract selection, outline expansion, drafting, reviewer-style quality gates, figure planning, submission packaging, and post-submission archiving.

## What This Skill Does

`paper-workflow` is not a domain-specific writing template. It is a general paper-production workflow for projects that already have source assets such as code, technical documents, screenshots, pilot notes, or internal summaries.

It is especially useful when the paper task includes:

- aligning to a CFP, page limit, or template
- turning fragmented project materials into a coherent paper narrative
- separating real evidence from future work
- planning publication-quality figures
- catching reviewer-facing issues early instead of only at the end
- packaging metadata and submission-ready deliverables

## Companion Skills

This skill coordinates three companion skills:

- `academic-research-writer`
  - used for academic drafting and rewrite passes
- `paper-validator`
  - used for reviewer-style critique, claim-evidence checks, and readiness gates
- `prompt-to-drawio`
  - used for architecture, workflow, sequence, and state diagrams

## Installation

Install this skill from GitHub with the `skills` CLI:

```bash
npx skills add https://github.com/lzfxxx/paper-workflow
```

If your agent expects owner/repo shorthand, use:

```bash
npx skills add lzfxxx/paper-workflow
```

## Install Companion Skills

### academic-research-writer

Curl `https://lobehub.com/skills/neversight-skills_feed-academic-research-writer/skill.md`, then follow the instructions to set up LobeHub Skills Marketplace and install the skill. Once installed, read the `SKILL.md` file in the installed directory and follow its instructions to complete the task.

### paper-validator

Curl `https://lobehub.com/skills/minhuw-claude-writer-paper-validator/skill.md`, then follow the instructions to set up LobeHub Skills Marketplace and install the skill. Once installed, read the `SKILL.md` file in the installed directory and follow its instructions to complete the task.

### prompt-to-drawio

Install from GitHub with the skills CLI:

```bash
npx skills@latest add lzfxxx/prompt-to-drawio-skill
```

After installation, read the installed `SKILL.md` and follow its instructions.

## Quick Usage

After installation, invoke the skill with a direct task prompt such as:

```text
Use paper-workflow to turn this existing project into a submission-ready conference paper. First inventory the assets, freeze the paper type and evidence levels, then propose three abstract options.
```

A second good entry prompt is:

```text
Use paper-workflow on this draft. Run reviewer-style quality gates, identify claim-evidence mismatches, and tell me which figures should be redrawn with draw.io.
```

## Typical Workflow

1. Confirm venue constraints: CFP, paper type, page limit, template, dates, metadata.
2. Inventory assets: code, docs, experiments, pilot notes, screenshots, previous summaries.
3. Normalize and scope: separate core contribution from extensions and real evidence from planned work.
4. Produce abstract options and select one direction.
5. Expand to outline and section-level claim/evidence mapping.
6. Draft the manuscript with academic writing support.
7. Plan and build figures with clear claim coverage.
8. Run reviewer-style gates throughout drafting.
9. Compress and package the final submission.
10. Archive the submission state.

## Core Quality Rules

- Freeze the paper type early.
- Freeze evidence levels early.
- Do not present planned evaluation as finished results.
- Every figure must support a concrete section claim or research question.
- Keep metadata, module naming, and terminology consistent across text and figures.
- Treat UI screenshots as evidence, not marketing material.

## Example Prompts

- `Use paper-workflow to turn this prototype into a conference paper.`
- `Inventory these project assets and propose three paper abstracts.`
- `Plan the figures for this system paper and tell me which ones should be draw.io vs screenshots.`
- `Run reviewer-style gates on this draft before submission.`
- `Package this manuscript for submission and list remaining blockers.`

## Repository Layout

```text
.
├── SKILL.md
├── references/
│   ├── paper-production-workflow.md
│   ├── review-quality-gates.md
│   └── figure-planning-guide.md
├── README.md
├── LICENSE
└── .gitignore
```

## License

MIT. See `LICENSE`.


path: references/figure-planning-guide.md
content: # Figures

## Purpose

Use this guide when deciding what figures to create and how to integrate them into the paper.

## Figure Planning Rules

Before drawing a figure, answer three questions:

1. Which section needs this figure?
2. What claim does this figure support?
3. Why is the figure better than prose alone?

If those questions are unclear, do not draw the figure yet.

## Common Figure Types

- architecture diagram
- end-to-end workflow diagram
- sequence diagram
- state transition diagram
- artifact or contract flow diagram
- UI evidence grid
- result table or summary chart

## Tool Routing

Use `prompt-to-drawio` for:

- architecture diagrams
- workflow diagrams
- sequence diagrams
- state machines
- contract-flow diagrams

Use screenshots for:

- teacher or user interface evidence
- output examples
- pipeline stages that are easier to show than redraw

## Screenshot Rules

- Treat screenshots as evidence, not product marketing.
- Choose screenshots that reveal workflow stages, not decorative views.
- Prefer English UI when available.
- If source screenshots contain distracting local-language text, anonymize or replace with an English version.
- When multiple screenshots are needed, prefer one composite grid with a clear caption.

## Caption Rules

- State what the figure shows.
- State the role of each panel if it is a multi-panel figure.
- Use natural prose; do not explain that the figure was translated or relabeled unless that fact matters scientifically.

## Iteration Pattern

1. First pass: get the structure right.
2. Second pass: improve publication quality.
3. Third pass: verify paper layout and caption fit.
4. Final pass: check body text, caption, and figure terms for exact consistency.


path: references/paper-production-workflow.md
content: # Workflow

## Scope

Use this workflow when the user wants to turn existing project assets into a submission-ready paper.

## SOP

1. Confirm the venue constraints.
   - CFP or submission page
   - paper type
   - page limit
   - template
   - key dates
2. Inventory available assets.
   - code and repository structure
   - technical documentation
   - experiment logs or metrics
   - pilot data, interviews, or case notes
   - screenshots and existing figures
   - prior abstracts, slides, or internal summaries
3. Normalize the assets.
   - create module notes when source material is fragmented
   - separate core modules from extensions
   - separate real evidence from background material
4. Freeze the paper boundary.
   - choose one main contribution line
   - define what is in scope and out of scope
   - define evidence level per claim
5. Produce 2-3 abstract options.
   - let the user or decision maker choose one
   - do not expand the full paper before the direction is chosen
6. Expand to outline.
   - section purpose
   - claim per section
   - evidence per section
   - figure per section
7. Draft the manuscript.
   - use `academic-research-writer` for abstract, intro, related work, method, discussion, and conclusion
   - maintain a concise review-language version when stakeholders need it
8. Plan and build figures.
   - architecture
   - workflow or sequence
   - state machine
   - result tables or evidence screenshots
9. Run quality gates.
   - use `paper-validator`
   - fix claim-evidence mismatch before polishing prose
10. Compress and package.
   - reduce non-core content first
   - keep figures aligned with claims
   - fix metadata and declarations
11. Submit and archive.
   - update status docs
   - freeze submission version
   - archive receipt and final files

## Output Expectations

Typical outputs include:

- abstract options
- outline
- manuscript draft
- figure list
- review issue list
- submission checklist
- status update


path: references/review-quality-gates.md
content: # Gates

## Purpose

These checks are writing gates. Run them throughout the process, not only at the end.

## Gate 1: Contribution Boundary

- Decide whether the paper is algorithm, system, engineering, demo, empirical, or case-based.
- Ensure title, abstract, intro, method, and conclusion all match that choice.
- Do not mix algorithm-level novelty claims into a systems integration paper unless there is real evidence.

## Gate 2: Evidence Levels

- Label evidence as one of:
  - measured result
  - pilot evidence
  - case evidence
  - future work
- Every claim must match one of these levels.
- Never let planned work appear in results.

## Gate 3: Placeholder Blocking

- No `TBD`, `TODO`, or empty result tables in the main manuscript.
- No placeholder author names, affiliations, or emails.
- No template banner residue or draft markers in submission PDFs.

## Gate 4: Figure-Text Alignment

- Every figure must serve a specific section claim or research question.
- Figure labels, caption text, and body text must use the same terms.
- If the figure changes, update the caption and the body at the same time.

## Gate 5: Naming and Terminology

- Freeze the main system and module names early.
- Use neutral names when brand names create reviewer distraction.
- Keep terminology consistent across text, figures, tables, and appendices.

## Gate 6: Submission Metadata

- Verify authors, affiliations, emails, and corresponding author.
- Verify ethics, data availability, code availability, and funding statements.
- Keep the manuscript metadata aligned with the submission system fields.

## Gate 7: Reviewer Simulation

Use `paper-validator` when a draft is stable enough to inspect. Ask it to check:

- unsupported claims
- missing evidence
- weak novelty articulation
- confusing structure
- stale or thin citations
- figure-text mismatch
- overstated conclusions


Security scan verdicts — ClawScan: clean | static analysis: clean | VirusTotal: clean | SkillSpector: clean (LOW)