word-digest

word-digest is an agent for Claude Code from gonzalezpazmonica/pm-workspace. It costs 83 tokens per session (1,351 once invoked), scanned A, a copy of word-digest, MIT.

A document-processing agent for Word files (.docx). It extracts text, tables, embedded images, and document details into a structured summary while using project context to resolve unclear terms.

In plain words
What is it for?
It helps process meeting minutes, proposals, manuals, reports, and procedures, then creates a Markdown digest and updates the project's living context documents.
Why use it?
It turns Word documents into information that is easier for an agent or team to search and use. It also preserves table structure and records details such as authorship and dates.

Agent for Claude Code

Written for Claude Code: installed under .claude/. Also seen: model in frontmatter; mentions CLAUDE.md; mentions OpenCode.

Part of the pm-workspace plugin — 124 commands, 75 agents shipped together

Good fit It helps process meeting minutes, proposals, manuals, reports, and procedures, then creates a Markdown digest and updates the project's living context documents.

Compare 6 agents from other repositories ↓
Install with agentmods
npx agentmods add agents/gonzalezpazmonica/pm-workspace/word-digest
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.

Clone the repo
git clone --depth 1 https://github.com/gonzalezpazmonica/pm-workspace

Made for: Claude Code.

Or install pm-workspace, the plugin that ships this one along with the rest of its 124 commands, 75 agents.

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 word-digest

README.md
[![agentmods](https://agentmods.dev/badge/agents/gonzalezpazmonica/pm-workspace/word-digest/github.svg)](https://agentmods.dev/agents/gonzalezpazmonica/pm-workspace/word-digest)
Your own site
<a href="https://agentmods.dev/agents/gonzalezpazmonica/pm-workspace/word-digest"><img src="https://agentmods.dev/badge/agents/gonzalezpazmonica/pm-workspace/word-digest/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 word-digest

Your own site · 80×15
<a href="https://agentmods.dev/agents/gonzalezpazmonica/pm-workspace/word-digest"><img src="https://agentmods.dev/badge/agents/gonzalezpazmonica/pm-workspace/word-digest.svg" alt="Reviewed on agentmods" width="80" height="20"></a>
Per session 83 Only the description is in the session, so the agent can decide to use it. The body loads when it is invoked.
When invoked 1,351 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 100% 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.

ModelPer sessionOnce invoked
Fable 5.1 $0.00083 $0.01351
Opus 5 $0.00042 $0.00675
Sonnet 5 $0.00017 $0.00270
Haiku 4.5 $0.00008 $0.00135

Measured 8d ago against content hash 79926313bdd2, method: parsed. Prices are Anthropic first-party input rates as of 2026-09-12, from the pricing page.

Security

Grade A, and why

word-digest 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 8d 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.

Origin

This is a copy

100% identical to word-digest — 0 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.

.claude/agents/word-digest.md · 151 lines

How it starts

The opening of the file, as written. The whole thing — 151 lines — stays where its author put it; the contents beside it link to each section on GitHub.

word-digest — Digestion Contextual de DOCX en 4 Fases

Agente especializado en extraer informacion de documentos Word (.docx) dentro de un proyecto pm-workspace. Extrae texto, tablas, imagenes embebidas y metadatos. Produce un digest .md estructurado y actualiza documentos de contexto del proyecto.

Dependencias

python-docx debe estar instalado:

pip install python-docx Pillow 2>/dev/null || pip3 install python-docx Pillow

Pipeline de 4 fases

Fase 1 — Extraccion bruta (sin contexto)

  1. Verificar que python-docx esta disponible. Si no: instalar
  2. Extraer metadatos: autor, fecha creacion, fecha modificacion, titulo
  3. Extraer texto de todos los parrafos con estilo (heading, body, list):
    from docx import Document
    doc = Document('{ruta_docx}')
    for para in doc.paragraphs:
        style = para.style.name if para.style else 'Normal'
        print(f'[{style}] {para.text}')
    
  4. Extraer tablas preservando estructura:
    for i, table in enumerate(doc.tables):
        print(f'--- TABLE {i+1} ---')
        for row in table.rows:
            print(' | '.join(cell.text.strip() for cell in row.cells))
    
  5. Extraer imagenes embebidas a carpeta temporal:
    from docx.opc.constants import RELATIONSHIP_TYPE as RT
    for rel in doc.part.rels.values():
        if 'image' in rel.reltype:
            img = rel.target_ref
            # guardar imagen para analisis visual
    
  6. Para imagenes significativas (>100x100px): leer con Read (Claude Vision)
  7. Marcar con [?] textos dudosos, siglas desconocidas, nombres ambiguos
  8. Detectar estructura: secciones, subsecciones, tablas, listas, notas al pie

Fase 2 — Carga de contexto y resolucion

Leer ficheros del proyecto para construir diccionario de resolucion:

1. projects/{proyecto}/CLAUDE.md
2. projects/{proyecto}/README.md
3. projects/{proyecto}/RULES.md (si existe)
4. projects/{proyecto}/GLOSSARY.md (si existe)
5. projects/{proyecto}/team/TEAM.md (si existe)
6. projects/{proyecto}/STATUS.md (si existe)

Read the full file on GitHub · 151 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. 8d ago First seen · 151 lines · 83 tokens per session scan A 79926313bdd2

Subscribe to this mod's changes

word-digest is an agent published in the GitHub repository gonzalezpazmonica/pm-workspace (49 stars, last pushed 6d ago), licensed MIT. It adds 83 tokens to every session and 1,351 once invoked, about $0.0004 per session on Opus 5. A static security scan graded it A with 0 findings. It is 100% identical to word-digest, differing in 0 lines, and is treated as a copy.

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