Echo Agent is a self-hosted, long-running AI agent that connects language models, tools, memory, permissions, and messaging channels in one system. Individuals and teams use it for private automation that retains context across sessions, develops skills, schedules tasks, and requires approval for high-risk actions.
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 fuyuxiang/echo-agent --skill excel-authorgit clone --depth 1 https://github.com/fuyuxiang/echo-agentWrote 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/fuyuxiang/echo-agent/excel-author)<a href="https://agentmods.dev/skills/fuyuxiang/echo-agent/excel-author"><img src="https://agentmods.dev/badge/skills/fuyuxiang/echo-agent/excel-author/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/fuyuxiang/echo-agent/excel-author"><img src="https://agentmods.dev/badge/skills/fuyuxiang/echo-agent/excel-author.svg" alt="Reviewed on agentmods" width="80" height="20"></a>- NVIDIA SkillSpector pass
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 | $0.00028 | $0.00592 |
| Opus 5.5 | $0.00011 | $0.00237 |
| Sonnet 5.5 | $0.00006 | $0.00118 |
| Haiku 4.5 | $0.00003 | $0.00059 |
Grade A, and why
excel-author 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 1mo 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
Excel Author
Create professional Excel workbooks programmatically.
Install
pip install openpyxl
Quick Start
from openpyxl import Workbook
from openpyxl.styles import Font, PatternFill, Alignment, Border, Side
wb = Workbook()
ws = wb.active
ws.title = "月度报表"
# Headers
headers = ["日期", "类别", "金额", "备注"]
ws.append(headers)
for cell in ws[1]:
cell.font = Font(bold=True, size=12)
cell.fill = PatternFill("solid", fgColor="4472C4")
cell.font = Font(bold=True, color="FFFFFF")
# Data
ws.append(["2026-06-01", "餐饮", 85.5, "午餐"])
ws.append(["2026-06-01", "交通", 15.0, "地铁"])
ws.append(["2026-06-02", "购物", 299.0, ""])
# Formula
ws.append(["", "合计", "=SUM(C2:C4)", ""])
# Auto-width
for col in ws.columns:
max_len = max(len(str(cell.value or "")) for cell in col)
ws.column_dimensions[col[0].column_letter].width = max_len + 4
wb.save("report.xlsx")
Script
python3 scripts/create_xlsx.py from-csv data.csv --output report.xlsx
python3 scripts/create_xlsx.py from-json data.json --output report.xlsx
python3 scripts/create_xlsx.py quick "Report Title" --headers Name Age City --output output.xlsx
Templates
- Expense Report: Category breakdown with totals
- Project Tracker: Status, assignee, due date columns
- Data Analysis: Summary statistics + charts
Charts
from openpyxl.chart import BarChart, Reference
chart = BarChart()
chart.title = "月度支出"
data = Reference(ws, min_col=3, min_row=1, max_row=5)
cats = Reference(ws, min_col=2, min_row=2, max_row=5)
chart.add_data(data, titles_from_data=True)
chart.set_categories(cats)
ws.add_chart(chart, "E2")
Conventions
- Blue cells: input values
- Black cells: calculated/formula
- Green cells: final output/results
What ships with it
1 file 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.
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.
- 1mo ago First seen · 89 lines · 28 tokens per session scan A 4e929fccb762
excel-author is a skill published in the GitHub repository fuyuxiang/echo-agent (1,058 stars, last pushed today), licensed MIT. It adds 28 tokens to every session and 592 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 2026-08-30.
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