docx-reader

A document converter that reads Microsoft Word DOCX files and produces clean Markdown, a plain-text format commonly used for documentation. It can also extract images into a companion folder.

In plain words
What is it for?
Use it to convert DOCX documents, create kebab-case Markdown filenames, extract embedded images, and add the required tags.
Why use it?
It removes the need to copy and reformat Word content manually. The output is easier to store, search, and edit alongside technical files.

Agent

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 agents/datacore-one/datacore/docx-reader
Clone the repo
git clone --depth 1 https://github.com/datacore-one/datacore
Per session 25 Only the description is in the session, so the agent can decide to use it. The body loads when it is invoked.
When invoked 1,946 The whole file, excluding the scripts and references it only reads on demand.
Security scan A 0 findings. Scan, not verified.
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 $0.00025 $0.01946
Opus 5 $0.00013 $0.00973
Sonnet 5 $0.00005 $0.00389
Haiku 4.5 $0.00003 $0.00195

Measured yesterday against content hash e790ea2a3ff7, method: parsed. Prices are Anthropic first-party input rates as of 2026-08-30, from the pricing page.

Security

Grade A, and why

docx-reader 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 yesterday.

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.

.datacore/agents/docx-reader.md · 301 lines

How it starts

The opening of the file, as written. The whole thing — 301 lines — stays where its author put it; the contents beside it link to each section on GitHub.

DOCX Reader Agent

Engram Injection

Before starting work, load relevant learned patterns:

  1. Preferred: Call plur_admin MCP tool with action = "plur_inject_hybrid", prompt = your task description, scope = agent:docx-reader
  2. Fallback: If MCP is unavailable, read .datacore/state/agent-engrams/docx-reader.md for compiled engrams

Engrams encode learned behavioral patterns that improve task quality.

Agent Context

When to Reference DIP-0014

Always reference when:

  • Adding tags to converted documents
  • Formatting inline tags
  • Using proper tag capitalization
  • Placing tags at end of content

Key decisions this DIP informs:

  • Tags at end of content, not frontmatter
  • Inline #Tag format, space-separated
  • Use proper capitalization from registry
  • Check .datacore/config/tags.yaml for valid tags

Quick Reference

Question Answer
Output format? Kebab-case markdown filename
Where to place tags? End of document, inline
Image extraction? word/media/* to companion folder
Who calls me? file-reader

Related DIPs

Related Agents

Agent Relationship
file-reader Spawns me for DOCX files

Integration Points

  • DIP-0014 - Tag format and placement
  • Unzip - Extracts DOCX content
  • Frontmatter - Uses proper YAML metadata

You are a document conversion specialist that reads Microsoft Word DOCX files and produces clean, well-structured Markdown.

Your Role

You read DOCX files (which are ZIP archives containing XML) and convert them to readable Markdown, preserving:

  • Document structure (headings, paragraphs)
  • Text formatting (bold, italic)
  • Lists (bulleted and numbered)
  • Basic tables
  • Meaningful content

Technical Approach

DOCX files are ZIP archives. The main content is in word/document.xml.

Read the full file on GitHub · 301 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. yesterday First seen · 301 lines · 25 tokens per session scan A e790ea2a3ff7

Subscribe to this mod's changes

docx-reader is an agent published in the GitHub repository datacore-one/datacore (4 stars, last pushed 2d ago), licensed MIT. It adds 25 tokens to every session and 1,946 once invoked, about $0.0001 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 2026-08-31.

Related

Other agents, from other repositories

01-crm-pull

Fetch contacts, actions, pipeline data from CRM (Notion or local markdown).

assafkip/kipi-system · 22 tokens

01-calendar-pull

Fetch calendar events for the next 7 days via Google Calendar MCP.

assafkip/kipi-system · 18 tokens

verification-gate

Evidence-before-claims gate. Use before declaring work complete, fixed, or passing — before committing or creating PRs. Requires running verification commands, driving the affected flow end-to-end to observe real behaviour, and confirming output before any success claims. Adapted from Superpowers'…

sliamh11/Deus · 111 tokens

keystone

Structured end-to-end trace to find the FIRST broken link in a specific claim's dependency chain. Single-claim depth probe — NOT a breadth reviewer. Use when a consequential claim ("X is enforced", "Y has a fallback", "Z reaches the main agent") needs primary-evidence verification across its full chain. Advisory…

sliamh11/Deus · 87 tokens

brainstormer

Creative research and solution design agent. Takes a problem statement, surveys prior art (vault memory, web, papers), generates 3-5 ranked solution ideas with effort/impact/risk estimates, and identifies non-obvious connections. Use when stuck on a challenge, exploring design alternatives, or wanting creative input…

sliamh11/Deus · 210 tokens

code-reviewer

Post-implementation, pre-commit review of actual code changes against Deus-specific rules stored in a versioned rules file. Runs on the working-tree + staged diff like a PR reviewer tuned to this repo's standards (CI gates, cross-platform, token efficiency, security basics, cleanup, type safety, comment discipline…

sliamh11/Deus · 222 tokens