A document-production workflow for creating, editing, comparing changes in, and commenting on Word files and documents intended for Google Docs. It also renders documents into images or PDFs so their layout can be checked.

Use it to create or modify .docx files, prepare Word-compatible documents for Google Docs, add redlines or comments, and visually verify the final pages.

It helps catch formatting and page-layout problems that may not be visible from the document's underlying text or code.

documents — Skill by zm1990s

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.

agentmods

npx agentmods add skills/zm1990s/kb-agent/documents

Any agent

npx skills add zm1990s/kb-agent --skill documents

Clone the repo

git clone --depth 1 https://github.com/zm1990s/kb-agent

Made for: Claude Code, Codex.

Per session 71 Skills are progressive disclosure: only the name and description are preloaded; the body loads when the skill is used.

When invoked 8,578 The whole file, excluding the scripts and references it only reads on demand.

Security scan A 0 findings. Scan, not verified.

Origin 88% copy Near-identical to another mod 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.

Model	Per session	Once invoked
Fable 5	$0.00071	$0.08578
Opus 5	$0.00036	$0.04289
Sonnet 5	$0.00014	$0.01716
Haiku 4.5	$0.00007	$0.00858

Measured 3d ago against content hash 8ed9ed302b57, method: parsed. Prices are Anthropic first-party input rates as of 2026-08-30, from the pricing page.

Security

Grade A, and why

documents 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 3d ago.

The scan reads SKILL.md. This mod also ships 37 executable files (render_docx.py, scripts/a11y_audit.py, scripts/accept_tracked_changes.py, …), listed below but not scanned — reading those needs a real analyzer, not pattern matching.

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.

Origin

This is a copy

88% identical to docx — 163 lines differ, which has more behind it and is treated as the original. This page carries a canonical link to it rather than competing with it.

backend/codex_skills/documents/SKILL.md · 465 lines

How it starts

The opening of the file, as written. The whole thing — 465 lines — stays where its author put it; the contents beside it link to each section on GitHub.

Documents Skill (Read • Create • Edit • Redline • Comment)

Use this skill when you need to create or modify .docx, Word, or Google Docs-targeted document artifacts in this container environment and verify them visually.

Tools + Contract

Use Codex workspace dependencies for docx artifact work: resolve them through the workspace dependency loader or runtime skill, then treat the returned Node/Python runtimes and package directory as authoritative. Do not use system node, system python, global npm packages, or repo-local installs.
For document creation and deterministic OOXML edits, it is still acceptable to use the bundled Python/OOXML helper scripts in this skill package when the JS surface is incomplete.
Run any builder or helper file from a writable workspace or temp directory, not from the managed dependency directory itself.
Final user-facing responses should describe only the requested document result. Do not link QA intermediates unless the user explicitly asks for them.

Google Docs-targeted output

For a net-new Google Docs request, create and visually verify a local .docx with this skill first. The native Google Docs deliverable must then be produced by the Google Drive plugin's document import action, mcp__codex_apps__google_drive_import_document, with upload_mode: "native_google_docs".

Before rendering or importing any Google Docs-targeted DOCX, run the deterministic title sanitizer:

python scripts/google_docs_title_sanitize.py input.docx --out sanitized.docx
python scripts/google_docs_title_sanitize.py sanitized.docx --check

Use the sanitized DOCX for render QA and native Google Docs import. This is not a style preference or prose reminder: the sanitizer removes Word Title paragraph-style border residue, direct title-paragraph borders, and leading title-block paragraph borders from the OOXML so Word's built-in blue title rule cannot survive into the imported Google Doc.

Do not use Computer Use, Browser Use, blank-Google-Doc creation plus Google Docs write APIs, or another direct-to-Docs construction path for net-new Google Docs unless the user explicitly asks for that alternate workflow. If they do, mention first that output quality is expected to be best when a local .docx is imported through the Google Drive plugin.

Read the full file on GitHub · 465 lines

Files

What ships with it

60 files beside SKILL.md in the same directory: the scripts, references and assets a skill reads on demand. Not counted in the per-session cost; read them before you install if any of them is executable.

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.

3d ago First seen · 465 lines · 71 tokens per session scan A 8ed9ed302b57

Subscribe to this mod's changes

documents is a skill published in the GitHub repository zm1990s/kb-agent (5 stars, last pushed 13d ago), licensed MIT. It adds 71 tokens to every session and 8,578 once invoked, about $0.0004 per session on Opus 5. A static security scan graded it A with 0 findings. It is 88% identical to docx, differing in 163 lines, and is treated as a copy.

Documents

notion

Notion API for creating and managing pages, databases, and blocks. Use when the user wants to create a Notion page, query a Notion database, update Notion properties, search Notion, add content to Notion, manage Notion blocks, or interact with Notion data sources and workspaces via the API.

elizaOS/eliza · 69 tokens

feishu

Work with Feishu or Lark bots, docs, sheets, bitables, approval flows, and OpenAPI/MCP setup without hardcoding credentials.

Hmbown/CodeWhale · 33 tokens

sn-da-large-file-analysis

万行以上 Excel 数据集的高性能分析引擎。提供 openpyxl readonly 流式读取（iterrows 支持 10 万行以上）、Parquet 转换加速、内存优化、分块处理和大文件写入模式。遇到以下任一情况就主动使用本 skill：①数据行数 ≥ 10k（由 sn-da-excel-workflow 的行数评估步骤触发）；②用户出现触发词：大文件 / 大数据量 / 性能优化 / 内存不足 / OOM / 百万行 / 十万行 / 流式读取 / Parquet / 分块处理 / large file / big data / streaming read / chunked processing；③直接使用…

OpenSenseNova/SenseNova-Skills · 218 tokens

resilient-document-pipeline

Unified document generation with tool failure detection, domain knowledge fallback, progressive conversion, and Unicode safety.

HKUDS/OpenSpace · 25 tokens

category-filtering-and-difficulty-analysis

对Excel数据进行自定义分类统计、交叉分析与可视化，并基于多维度指标（如文本长度、术语密度、正则匹配等）进行综合评分与分级，适用于多类别数据分布统计及文本内容难度/质量评估场景。.

OpenSenseNova/SenseNova-Skills · 74 tokens

summarize-document

Summarize a long PDF, scan, office file, text file, or markdown file through the connected Superlinked MCP edge instead of reading the whole source into model context. Use when the user asks for a summary, overview, digest, or "what does this document say" about a large file.

superlinked/sie · 66 tokens