OpenClaw Master Skills is a curated, regularly updated collection of skills that extends an AI personal assistant platform with capabilities such as research, browser automation, presentation creation, and prompt work. It is intended for people using OpenClaw or MyClaw.ai to give their agents additional tasks and workflows. The catalogue contains many skills and agents from this collection.
Getting it into your agent
There is no command for this one: it runs only inside a plugin, and the catalogue could not identify which plugin ships it. The source is linked below.
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.
[](https://agentmods.dev/skills/leoyeai/openclaw-master-skills/achievement-qztc)<a href="https://agentmods.dev/skills/leoyeai/openclaw-master-skills/achievement-qztc"><img src="https://agentmods.dev/badge/skills/leoyeai/openclaw-master-skills/achievement-qztc/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/leoyeai/openclaw-master-skills/achievement-qztc"><img src="https://agentmods.dev/badge/skills/leoyeai/openclaw-master-skills/achievement-qztc.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 | $0.00035 | $0.06317 |
| Opus 5 | $0.00017 | $0.03159 |
| Sonnet 5 | $0.00007 | $0.01263 |
| Haiku 4.5 | $0.00003 | $0.00632 |
Grade A, and why
achievement-qztc 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 13d 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.
How it starts
The opening of the file, as written. The whole thing — 634 lines — stays where its author put it; the contents beside it link to each section on GitHub.
课程目标达成情况分析表生成工具(QZTC版)
根据Excel学生数据替换Word模板中的课程目标达成情况,生成新的分析表。
适用场景
- 根据Excel学生名单生成课程目标达成情况分析表
- 自动计算各课程目标的达成值(随机生成成绩,百分比表示)
文件路径
- 模板文件:
/Volumes/qztcm09/Desktop/temp/课程目标达成情况分析表-数据可视化-模版.docx - Excel数据:
/Volumes/qztcm09/Desktop/temp/数据可视化技术23级计算机.xls
使用步骤
步骤1:读取Excel数据
import pandas as pd
import shutil
import random
from docx import Document
from datetime import datetime
# 读取Excel
df = pd.read_excel('/Users/qztcm09/Desktop/temp/数据可视化技术23级计算机.xls')
# 排除旷考学生
df = df[df['备注'] != '旷考'].reset_index(drop=True)
# 自动判断当前学年和学期
now = datetime.now()
year = now.year
month = now.month
day= now.day
if 1 <= month <= 6:
# 1-6月:第一学期(上学年)
academic_year = f"{year-1} - {year}"
semester = "一"
else:
# 7-12月:第二学期(上学年)
academic_year = f"{year-1} - {year}"
semester = "二"
print(f"当前学年: {academic_year}, 学期: {semester}学期")
# 从"班级"字段提取年级、班级、专业信息
# 专业名称提取支持两种情况:
# 情况1: "23级计算机" → 年级=23, 专业=计算机
# 情况2: "23级软工2班" → 年级=23, 专业=软工
import re
class_name = df['班级'].iloc[0] if '班级' in df.columns else ''
match = re.search(r'(\d+)级', str(class_name))
grade = match.group(1) if match else '' # 如 "23"
# 提取专业:匹配 "XX级" 后面到 "XX班" 或结尾的部分
match = re.search(r'\d+级(.+?)(?:\d+班)?$', str(class_name))
major = match.group(1).strip() if match else '' # 如 "计算机" 或 "软工"
# 获取学生信息
students = df[['学号', '姓名']].copy()
print(f"学生人数: {len(students)}")
步骤2:复制模板并打开
template_path = '/Users/qztcm09/Desktop/temp/课程目标达成情况分析表-数据可视化-模版.docx'
output_path = '/Users/qztcm09/Desktop/temp/课程目标达成情况分析表-数据可视化-23级计算机.docx'
shutil.copy(template_path, output_path)
doc = Document(output_path)
步骤3:通用文本替换
⚠️ 重要:Word占位符可能被拆分成多个run,且表格单元格中可能有换行,需要特殊处理,保留原格式
def replace_text_preserve_format(para, replacements):
"""替换段落文本但保留格式"""
# 先收集所有run的文本
full_text = ''.join(run.text for run in para.runs if run.text)
# 检查是否有占位符
has_placeholder = any(old in full_text for old, _ in replacements)
if not has_placeholder:
return
# 执行替换
for old, new in replacements:
full_text = full_text.replace(old, new)
# 获取第一个run的格式作为基准
if para.runs:
first_run = para.runs[0]
font_name = first_run.font.name
font_size = first_run.font.size
font_bold = first_run.font.bold
font_italic = first_run.font.italic
else:
font_name, font_size, font_bold, font_italic = None, None, None, None
# 清空并用新文本创建单一run,保留格式
para.clear()
run = para.add_run(full_text)
if font_name:
run.font.name = font_name
if font_size:
run.font.size = font_size
if font_bold is not None:
run.font.bold = font_bold
if font_italic is not None:
run.font.italic = font_italic
return para
def replace_text_in_table_cell(cell, replacements):
"""替换表格单元格中的文本(处理单元格内换行的情况)"""
# 遍历单元格中的所有段落
for para in cell.paragraphs:
full_text = ''.join(run.text for run in para.runs if run.text)
has_placeholder = any(old in full_text for old, _ in replacements)
if has_placeholder:
# 获取格式
if para.runs:
first_run = para.runs[0]
font_name = first_run.font.name
font_size = first_run.font.size
font_bold = first_run.font.bold
font_italic = first_run.font.italic
else:
font_name, font_size, font_bold, font_italic = None, None, None, None
# 执行替换
for old, new in replacements:
full_text = full_text.replace(old, new)
# 清空并重新设置
para.clear()
run = para.add_run(full_text)
if font_name:
run.font.name = font_name
if font_size:
run.font.size = font_size
if font_bold is not None:
run.font.bold = font_bold
if font_italic is not None:
run.font.italic = font_italic
return cell
# 替换配置
replacements = [
('$acyear$', academic_year),
('$semester$', semester),
('$g$', grade),
('$major$', major),
('$total$', f'{len(students)}人'),
('$year$', str(year)),
('$month$', str(month)),
('$day$', str(day)),
]
# 替换表格中的文本
for table in doc.tables:
for row in table.rows:
for cell in row.cells:
replace_text_in_cell(cell, replacements)
# 替换段落中的文本(处理被拆分的情况,保留格式)
for para in doc.paragraphs:
replace_text_preserve_format(para, replacements)
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.
- 13d ago First seen · 634 lines · 35 tokens per session scan A dae66bf944ec
achievement-qztc is a skill published in the GitHub repository LeoYeAI/openclaw-master-skills (2,141 stars, last pushed 1mo ago), licensed MIT. It adds 35 tokens to every session and 6,317 once invoked, about $0.0002 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 2026-08-30.
Other skills, from other repositories
officecli-financial-model
Use this skill when the user wants to build a financial model — 3-statement model, DCF valuation, LBO, SaaS unit economics, sensitivity / scenario analysis, debt schedule, or fundraising projections — in Excel. Trigger on: 'financial model', '3-statement model', 'P&L + BS + CF', 'DCF', 'WACC', 'NPV', 'terminal value'…
officecli-xlsx
Use this skill any time a .xlsx file is involved -- as input, output, or both. This includes: creating spreadsheets, financial models, dashboards, or trackers; reading, parsing, or extracting data from any .xlsx file; editing, modifying, or updating existing workbooks; working with formulas, charts, pivot tables, or…
officecli-data-dashboard
Use this skill to build a multi-element Excel dashboard — Dashboard sheet on open, multiple formula-driven KPI cards, multiple charts, sparklines, and conditional formatting — from CSV or tabular input. Trigger on: 'dashboard', 'KPI dashboard', 'analytics dashboard', 'executive dashboard', 'metrics dashboard', 'CSV to…
officecli
Create, analyze, proofread, and modify Office documents (.docx, .xlsx, .pptx) using the officecli CLI tool. Use when the user wants to create, inspect, check formatting, find issues, add charts, or modify Office documents.
xlsx
Use this skill any time a spreadsheet file is the primary input or output. This means any task where the user wants to: open, read, edit, or fix an existing .xlsx, .xlsm, .csv, or .tsv file; create a new spreadsheet from scratch or from other data sources; or convert between tabular file formats. Also trigger for…
officecli
Use the optional iOfficeAI/OfficeCLI engine for advanced inspection, validation, copy-on-write editing, template merge, or visual rendering of existing .docx, .xlsx, and .pptx files. Prefer MateClaw's built-in renderDocx/renderXlsx/renderPptx tools for simple new documents. Use this skill when preserving an existing…