DeepSeek Harness is an open-source framework for building and running AI agents, organized so that its functionality is provided through plugins. Developers use it to launch agent workflows through a local web interface or from source, while the catalogue add-ons extend the harness as plugins.
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 skills add deepseek-ai/deepseek-harness --skill office-xlsxgit clone --depth 1 https://github.com/deepseek-ai/deepseek-harnessWrote 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/deepseek-ai/deepseek-harness/office-xlsx)<a href="https://agentmods.dev/skills/deepseek-ai/deepseek-harness/office-xlsx"><img src="https://agentmods.dev/badge/skills/deepseek-ai/deepseek-harness/office-xlsx/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.
<a href="https://agentmods.dev/skills/deepseek-ai/deepseek-harness/office-xlsx"><img src="https://agentmods.dev/badge/skills/deepseek-ai/deepseek-harness/office-xlsx.svg" alt="Reviewed on agentmods" width="80" 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 5.1 | $0.00023 | $0.00935 |
| Opus 5.5 | $0.00009 | $0.00374 |
| Sonnet 5.5 | $0.00005 | $0.00187 |
| Haiku 4.5 | $0.00002 | $0.00093 |
Grade A, and why
office-xlsx 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.
How it starts
The opening of the file, as written. The whole thing — 53 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Excel workbooks
Follow an explicit user or applicable AGENTS.md requirement for an environment or library. Otherwise call load_workspace_dependencies and run its Python executable with bundled openpyxl and pandas. Do not install packages or search for a system Python for the default workflow. If the tool is unavailable, use an already configured environment and report a missing dependency only when it prevents the requested operation.
Keep scripts, working files, and outputs in the task workspace. The runtime and skill directory are shared read-only resources. Save to a new workbook unless the user requests an in-place edit.
Name Python scripts for their task, such as edit_xlsx.py; avoid module names such as inspect.py, openpyxl.py, or pandas.py that shadow imported libraries.
Read and modify
Use openpyxl for existing XLSX workbooks and targeted cell or style changes. Load with data_only=False when formulas must survive. Inspect sheet names, the affected cell types, formulas, styles, merged ranges, and referenced ranges before editing. Check the saved file by reopening it, including unchanged content that the request requires preserving.
Use pandas for data analysis and transformations. A DataFrame is not the workbook: exporting it over an existing file can lose sheets, formulas, charts, and formatting. Write analysis results back to the intended ranges with openpyxl. XlsxWriter can create new workbooks, but cannot read or modify existing ones.
For a new workbook, the selected Python environment can write editable values, styles, and formulas directly:
from openpyxl import Workbook
from openpyxl.styles import Font
workbook = Workbook()
sheet = workbook.active
sheet.title = "Revenue"
for row in [("Quarter", "Revenue"), ("Q1", 12), ("Q2", 18), ("Total", "=SUM(B2:B3)")]:
sheet.append(row)
for cell in sheet[1]:
cell.font = Font(bold=True)
sheet.column_dimensions["A"].width = 18
sheet.column_dimensions["B"].width = 18
workbook.save("report.xlsx")
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.
- yesterday Changed · -22 lines · -60 tokens per session 5b16d47b06d0
- 22d ago Changed · +18 lines · +43 tokens per session a1497cb17f7b
- 28d ago First seen · 57 lines · 40 tokens per session scan A b8394b54de0d
office-xlsx is a skill published in the GitHub repository deepseek-ai/deepseek-harness (250,433 stars, last pushed today), licensed MIT. It adds 23 tokens to every session and 935 once invoked, about $0.0001 per session on Opus 5.5. 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 2026-09-18.
Other skills, from other repositories
youtube-digest
A transcript extractor for YouTube videos. It reads available subtitles or automatically generated captions, can translate non-Chinese captions into Chinese, and can export the text to Excel, a spreadsheet application.
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investor-materials
Create and update pitch decks, one-pagers, investor memos, accelerator applications, financial models, and fundraising materials. Use when the user needs investor-facing documents, projections, use-of-funds tables, milestone plans, or materials that must stay internally consistent across multiple fundraising assets.
manage-taskboard
Manage work in the native DeepSeek Harness Taskboard with exact task ids and optimistic versions. Use when an Agent must inspect project work, claim an eligible todo, record progress or blockers, verify an implementation, submit it for human review, or release its own claim; also use when a human asks how to accept…
industry-research-method
A Chinese-language method for researching an industry by mapping its supply chain, tracking policies and news, and writing sourced reports. It separates the chain into upstream inputs, midstream production, and downstream distribution or use.
company-research-method
A documented process for researching a company using supplied files and selected public sources. It produces a company overview with business details, sourced financial figures, and stated risks.