ppw:caption

ppw:caption is a skill for Claude Code from Lylll9436/Paper-Polish-Workflow-skill. It costs 41 tokens per session (3,196 once invoked), scanned A, original, MIT.

A caption-writing aid for academic figures and tables that produces LaTeX captions and accounts for map details such as study area, data source, and coordinate reference system when needed.

In plain words
What is it for?
Use it to generate or improve captions, adapt them to a specified journal, and place them in the correct location in a .tex file.
Why use it?
It helps create concise, correctly formatted captions without asking irrelevant map-related questions for ordinary figures or tables.

Skill for Claude Code

Written for Claude Code: shipped in a Claude Code plugin. Also seen: names the AskUserQuestion tool.

Part of the paper-polish-workflow plugin — 16 skills shipped together

Good fit Use it to generate or improve captions, adapt them to a specified journal, and place them in the correct location in a .tex file.

Compare 6 skills from other repositories ↓
Install with agentmods
npx agentmods add skills/lylll9436/paper-polish-workflow-skill/ppw-caption
Install

Getting it into your agent

One page per mod, every tool's command on it. A separate URL per tool would split the same page into five that compete with each other.

Any agent
npx skills add Lylll9436/Paper-Polish-Workflow-skill --skill ppw-caption
Clone the repo
git clone --depth 1 https://github.com/Lylll9436/Paper-Polish-Workflow-skill

Made for: Claude Code.

Or install paper-polish-workflow, the plugin that ships this one along with the rest of its 16 skills.

Wrote this? Show the measurements

A badge with what this costs and how it scanned, read live from this page, so it follows the numbers instead of freezing them. Markdown for a README, HTML for a documentation site or a project page.

agentmods badge for ppw:caption

README.md
[![agentmods](https://agentmods.dev/badge/skills/lylll9436/paper-polish-workflow-skill/ppw-caption/github.svg)](https://agentmods.dev/skills/lylll9436/paper-polish-workflow-skill/ppw-caption)
Your own site
<a href="https://agentmods.dev/skills/lylll9436/paper-polish-workflow-skill/ppw-caption"><img src="https://agentmods.dev/badge/skills/lylll9436/paper-polish-workflow-skill/ppw-caption/github.svg" alt="Measured on agentmods" height="20"></a>

Or the 80×15 button, for a site that already has a row of RSS and ATOM ones. Only the verdict fits; the numbers stay here.

agentmods 80×15 button for ppw:caption

Your own site · 80×15
<a href="https://agentmods.dev/skills/lylll9436/paper-polish-workflow-skill/ppw-caption"><img src="https://agentmods.dev/badge/skills/lylll9436/paper-polish-workflow-skill/ppw-caption.svg" alt="Reviewed on agentmods" width="80" height="20"></a>
Per session 41 Skills are progressive disclosure: only the name and description are preloaded; the body loads when the skill is used.
When invoked 3,196 The whole file, excluding the scripts and references it only reads on demand.
Security scan A 0 findings. A grade says what 26 rules found in the file — not that it is safe.
Origin original No closer match found in the catalogue.
Token cost

What it costs to keep this loaded

Counted locally with the o200k_base tokenizer, which is exact for GPT models; Claude uses its own tokenizer and its counts differ. Treat this as one consistent yardstick across the catalogue rather than a bill. Prices are per million input tokens.

ModelPer sessionOnce invoked
Fable 5.1 $0.00041 $0.03196
Opus 5 $0.00020 $0.01598
Sonnet 5 $0.00008 $0.00639
Haiku 4.5 $0.00004 $0.00320

Measured 10d ago against content hash 4e883d5f8ba2, method: parsed. Prices are Anthropic first-party input rates as of 2026-09-09, from the pricing page.

Security

Grade A, and why

ppw:caption scanned grade A with 0 findings against 26 rules in 11 categories — prompt injection, anti-refusal, data exfiltration, privilege escalation, supply chain, agent snooping, system-prompt leakage, SSRF and excessive agency — measured 10d ago.

A static scan of the body, not an audit. Every finding is printed with the line that produced it so you can judge whether it matters here. A mod is markdown that instructs an agent; that is exactly why what it instructs is worth reading.

Nothing flagged

None of the 26 patterns this scan looks for appear in this file: no shell pipes, no recursive deletes, no credential paths, no hidden text, no instruction-override or anti-refusal phrasing, no agent-config snooping. That is not a guarantee, it is the absence of the things that are checkable.

skills/ppw-caption/SKILL.md · 285 lines

How it starts

The opening of the file, as written. The whole thing — 285 lines — stays where its author put it; the contents beside it link to each section on GitHub.

Purpose

This Skill generates or optimizes LaTeX figure and table captions for academic papers. For spatial figures (maps, GIS outputs, aerial photos), the Skill proactively collects study area, data source, and CRS metadata using a geography-aware Ask Strategy. For non-spatial figures and tables, geography questions are skipped entirely. Output is written directly to the user's .tex file at the correct \caption{} location using the Read-before-Write pattern. When a target journal is specified, caption length and style are adapted to the journal template.

Core Prompt

Source: awesome-ai-research-writing — 生成图的标题 + 生成表的标题

图标题 Prompt:

# Role
你是一位经验丰富的学术编辑,擅长撰写精准、规范的论文插图标题。

# Task
请将我提供的【中文描述】转化为符合顶级会议规范的【英文图标题】。

# Constraints
1. 格式规范:
   - 如果翻译结果是名词性短语:请使用 Title Case 格式,即所有实词的首字母大写,末尾不加句号。
   - 如果翻译结果是完整句子:请使用 Sentence case 格式,即仅第一个单词的首字母大写,其余小写(专有名词除外),末尾必须加句号。

2. 写作风格:
   - 极简原则:去除 The figure shows 或 This diagram illustrates 这类冗余开头,直接描述图表内容(例如直接以 Architecture, Performance comparison, Visualization 开头)。
   - 去 AI 味:尽量避免使用复杂的生僻词,保持用词平实准确。

3. 输出格式:
   - 只输出翻译后的英文标题文本。
   - 不要包含 Figure 1: 这样的前缀,只输出内容本身。
   - 必须对特殊字符进行转义(例如:`%`、`_`、`&`)。
   - 保持数学公式原样(保留 `$` 符号)。

表标题 Prompt:

# Role
你是一位经验丰富的学术编辑,擅长撰写精准、规范的论文表格标题。

# Task
请将我提供的【中文描述】转化为符合顶级会议规范的【英文表标题】。

# Constraints
1. 格式规范:
   - 如果翻译结果是名词性短语:请使用 Title Case 格式,即所有实词的首字母大写,末尾不加句号。
   - 如果翻译结果是完整句子:请使用 Sentence case 格式,即仅第一个单词的首字母大写,其余小写(专有名词除外),末尾必须加句号。

2. 写作风格:
   - 常用句式:对于表格,推荐使用 Comparison with, Ablation study on, Results on 等标准学术表达。
   - 去 AI 味:尽量避免使用 showcase, depict 等词,直接使用 show, compare, present。

3. 输出格式:
   - 只输出翻译后的英文标题文本。
   - 不要包含 Table 1: 这样的前缀,只输出内容本身。
   - 必须对特殊字符进行转义(例如:`%`、`_`、`&`)。
   - 保持数学公式原样(保留 `$` 符号)。

Trigger

Activates when the user asks to:

  • Write, generate, or create a caption for a figure or table
  • Optimize, improve, or rewrite an existing weak caption
  • 写图题、生成图表说明、优化标题、改写图表描述

Read the full file on GitHub · 285 lines

Changes

What this file has done since we first saw it

Hashed on every crawl. A supply-chain change to an agent config is a question of when, not whether, so the history is kept rather than the latest state alone.

  1. 10d ago First seen · 285 lines · 41 tokens per session scan A 4e883d5f8ba2

Subscribe to this mod's changes

ppw:caption is a skill published in the GitHub repository Lylll9436/Paper-Polish-Workflow-skill (386 stars, last pushed 5mo ago), licensed MIT. It adds 41 tokens to every session and 3,196 once invoked, about $0.0002 per session on Opus 5. A static security scan graded it A with 0 findings. No closer match exists in the catalogue, so it is treated as the original; first seen 2026-08-30.

Related

Other skills, from other repositories

instrument-data-to-allotrope

Convert laboratory instrument output files (PDF, CSV, Excel, TXT) to Allotrope Simple Model (ASM) JSON format or flattened 2D CSV. Use this skill when scientists need to standardize instrument data for LIMS systems, data lakes, or downstream analysis. Supports auto-detection of instrument types. Outputs include full…

anthropics/knowledge-work-plugins · 123 tokens

exploratory-data-analysis

Perform bounded, local exploratory analysis of explicitly supported scientific files. Use for redacted CSV/TSV/JSON profiles; optional NumPy, HDF5, FASTA/FASTQ, and basic image metadata inspection; missingness/leakage audits; outlier and transformation sensitivity; and rigorous EDA report scaffolds. Other domain…

K-Dense-AI/scientific-agent-skills · 83 tokens

matlab

Build, review, migrate, and safely plan MATLAB or GNU Octave numerical workflows, including arrays, tabular/time data, tests, projects, graphics, MAT files, and explicit Python interoperability.

K-Dense-AI/scientific-agent-skills · 42 tokens

phylogenetics

Build and analyze phylogenetic trees using MAFFT (multiple alignment), IQ-TREE 2 (maximum likelihood), and FastTree (fast NJ/ML). Visualize with ETE3 or FigTree. For evolutionary analysis, microbial genomics, viral phylodynamics, protein family analysis, and molecular clock studies.

K-Dense-AI/scientific-agent-skills · 68 tokens

research-engineer

An uncompromising Academic Research Engineer. Operates with absolute scientific rigor, objective criticism, and zero flair. Focuses on theoretical correctness, formal verification, and optimal implementation across any required technology.

davila7/claude-code-templates · 43 tokens

mapping-to-snomed

Maps clinical concept spans extracted by OpenMed to SNOMED CT concepts through a USER-SUPPLIED terminology server (the user's own Ontoserver, Snowstorm, or UMLS/UTS), never a bundled vocabulary. Use when the user wants to code findings, disorders, procedures, body structures, or substances to SNOMED CT, run an ECL…

maziyarpanahi/openmed · 205 tokens