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.
npx agentmods add skills/chenchihcu/devspace-mcp/office-writingnpx skills add chenchihcu/DevSpace-MCP --skill office-writinggit clone --depth 1 https://github.com/chenchihcu/DevSpace-MCPWrote 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.
[](https://agentmods.dev/skills/chenchihcu/devspace-mcp/office-writing)<a href="https://agentmods.dev/skills/chenchihcu/devspace-mcp/office-writing"><img src="https://agentmods.dev/badge/skills/chenchihcu/devspace-mcp/office-writing.svg" alt="Measured on agentmods" height="20"></a>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 | $0.00027 | $0.00356 |
| Opus 5 | $0.00014 | $0.00178 |
| Sonnet 5 | $0.00005 | $0.00071 |
| Haiku 4.5 | $0.00003 | $0.00036 |
Grade A, and why
office-writing 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.
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.
What it actually says
office-writing
Purpose
Create controlled artifact plans for Word, PowerPoint, and Excel deliverables without bypassing DevSpace verification.
When to Use
- Drafting report outlines, meeting decks, checklists, or workbook specs.
- Turning analyzed content into office artifact structure.
- Preparing formatting and review checklists before artifact generation.
Inputs
- Source material or approved analysis.
- Artifact type: Word, PowerPoint, or Excel.
- Audience, meeting purpose, and required sections or fields.
Outputs
- Word section hierarchy, tables, review checklist, and conclusion limits.
- PowerPoint slide titles, key messages, chart placement, and meeting use.
- Excel fields, formulas, validation rules, conditional formatting, and chart source spec.
Workflow
- Confirm source data exists before writing conclusions.
- Produce artifact specs first; generate files only when an approved generator and verification path exist.
- Keep formulas, headings, and review checklist explicit.
Verification
- Check outline matches the source and audience.
- Check formulas and chart sources are named before Excel generation.
- For generated artifacts, require format/open checks before PASS.
Risks / Limits
- Without source data, output must remain an outline or template.
- First MVP does not embed full Office generators.
- Formatting claims require visual or open-file verification.
Forbidden Actions
- Do not create or overwrite files outside guarded tools.
- Do not claim generated Office files are valid without format verification.
- Do not read protected paths or secrets.
Example Task
Create a supplier meeting PowerPoint outline from an approved document-analysis result.
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 · 49 lines · 27 tokens per session scan A 04fdb6c9f7ed
office-writing is a skill published in the GitHub repository chenchihcu/DevSpace-MCP (0 stars, last pushed 2mo ago), licensed MIT. It adds 27 tokens to every session and 356 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.
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