qqbot-media▌
sliverp/qqbot · updated Apr 8, 2026
MDX-style export adds YAML metadata + attribution linking explainx.ai and this canonical listing URL.
系统根据文件扩展名自动识别类型并路由：
QQBot 富媒体收发
用法
<qqmedia>路径或URL</qqmedia>
系统根据文件扩展名自动识别类型并路由：
.jpg/.png/.gif/.webp/.bmp→ 图片.silk/.wav/.mp3/.ogg/.aac/.flac等 → 语音.mp4/.mov/.avi/.mkv/.webm等 → 视频- 其他扩展名 → 文件
- 无扩展名的 URL → 默认按图片处理
接收媒体
- 用户发来的图片自动下载到本地，路径在上下文【附件】中，可直接用
<qqmedia>路径</qqmedia>回发 - 用户发来的语音路径在上下文中；若有 STT 能力则优先转写
规则
- 路径必须是绝对路径（以
/或http开头） - 标签必须用开闭标签包裹路径：
<qqmedia>路径</qqmedia> - 你有能力发送本地图片/文件——直接用标签包裹路径即可，不要说"无法发送"
- 发送语音时不要重复语音中已朗读的文字
- 多个媒体用多个标签
- 以会话上下文中的能力说明为准（如未启用语音则不要发语音）
- 发送前需检查文件大小，当文件超限时告知用户文件太大，QQBot 发送文件大小规则如下：
- 图片：最大 30MB
- 语音：最大 20MB
- 视频：最大 100MB
- 文件：最大 100MB
示例
这是你要的图片：
<qqmedia>/Users/xxx/photo.jpg</qqmedia>
<qqmedia>/tmp/tts/output.mp3</qqmedia>
视频在这里：
<qqmedia>https://example.com/video.mp4</qqmedia>
文件已准备好：
<qqmedia>/tmp/report.pdf</qqmedia>
How to use qqbot-media on Cursor
AI-first code editor with Composer
Prerequisites
Before installing skills in Cursor, ensure your development environment meets these requirements:
- ›Cursor installed and configured on your development machine
- ›Node.js version 16.0+ with npm package manager (verify with
node --version) - ›Active project directory or workspace where you want to add qqbot-media
Execute installation command
Execute the skills CLI command in your project's root directory to begin installation:
The skills CLI fetches qqbot-media from GitHub repository sliverp/qqbot and configures it for Cursor.
Select Cursor when prompted
The CLI will show a list of available agents. Use arrow keys to navigate and space to select Cursor:
Verify installation
Confirm successful installation by checking the skill directory location:
Reload or restart Cursor to activate qqbot-media. Access the skill through slash commands (e.g., /qqbot-media) or your agent's skill management interface.
Security & Verification Notice
We perform automated surface-level scans (Gen AI Scanner, Socket, Snyk) during installation. These checks detect common vulnerabilities but do not guarantee complete security. Always review skill source code and verify the publisher's reputation before production use.
Skills execute code in your development environment. Always verify the publisher's identity, review recent commits, and test in isolated environments before production deployment.
List & Monetize Your Skill
Submit your Claude Code skill and start earning
Use Cases▌
User Story & Requirements Generation
Create detailed user stories, acceptance criteria, and feature specs
Example
Generate user stories for 'password reset feature' with acceptance criteria, edge cases, and test scenarios
Reduce spec writing time by 50%, ensure comprehensive coverage
Competitive Analysis
Research competitors, compare features, identify gaps
Example
Analyze 5 competitor products, create feature comparison matrix, suggest differentiation opportunities
Complete competitive research in 2 hours instead of 2 days
Roadmap Prioritization
Evaluate features using frameworks (RICE, ICE, Kano) and create prioritized backlogs
Example
Score 20 feature ideas using RICE framework, generate prioritized roadmap with rationale
Make data-driven prioritization decisions faster
Stakeholder Communication
Draft PRDs, status updates, and stakeholder presentations
Example
Create executive summary of Q3 roadmap, monthly progress report, feature launch announcement
Save 3-5 hours/week on communication overhead
Implementation Guide▌
Prerequisites
- ›Claude Desktop or compatible AI client
- ›Access to product documentation and roadmap tools (Jira, Notion, etc.)
- ›Understanding of product management frameworks (RICE, Jobs-to-be-Done, etc.)
- ›Stakeholder contact information and communication channels
Time Estimate
30-60 minutes to see productivity improvements
Installation Steps
- 1.Install product management skill
- 2.Start with user story generation for known feature
- 3.Progress to competitive analysis: research 2-3 competitors
- 4.Use for roadmap prioritization: apply RICE/ICE scoring
- 5.Draft stakeholder communications and refine based on feedback
- 6.Build template library for recurring PM tasks
- 7.Share effective prompts with product team
Common Pitfalls
- ⚠Not validating competitive research—verify facts before sharing
- ⚠Accepting user stories without involving engineering team
- ⚠Over-relying on frameworks without qualitative judgment
- ⚠Not customizing outputs to company culture and communication style
- ⚠Skipping stakeholder validation of generated requirements
Best Practices▌
✓ Do
- +Validate research and competitive analysis with real data
- +Collaborate with engineering when generating technical requirements
- +Customize frameworks and templates to your company context
- +Use skill for first drafts, refine with stakeholder input
- +Document successful prompt patterns for PM tasks
- +Combine AI efficiency with human judgment and intuition
✗ Don't
- −Don't publish competitive analysis without fact-checking
- −Don't finalize user stories without engineering review
- −Don't make prioritization decisions solely on AI scoring
- −Don't skip customer validation of generated requirements
- −Don't ignore company-specific context and culture
💡 Pro Tips
- ★Provide context: company goals, constraints, customer feedback
- ★Ask for alternatives: 'Show 3 ways to prioritize this roadmap'
- ★Request stakeholder-specific formatting: 'Executive summary vs. engineering spec'
- ★Use skill for 70% generation + 30% customization to company needs
When to Use This▌
✓ Use When
Use for user story writing, competitive research, roadmap prioritization, stakeholder communication, and PRD drafting. Best for reducing repetitive documentation and research work.
✗ Avoid When
Avoid for strategic product vision (requires deep customer empathy), pricing decisions (needs market and financial expertise), or when face-to-face customer discovery is more valuable than speed.
Learning Path▌
- 1Basic: user stories, feature specs, status updates
- 2Intermediate: competitive analysis, prioritization frameworks, PRDs
- 3Advanced: product strategy, go-to-market planning, OKR setting
- 4Expert: product vision, market positioning, business model innovation
Discussion
Product Hunt–style comments (not star reviews)- No comments yet — start the thread.
Ratings
4.5★★★★★73 reviews- ★★★★★Harper Choi· Dec 24, 2024
qqbot-media has been reliable in day-to-day use. Documentation quality is above average for community skills.
- ★★★★★Kwame Martinez· Dec 24, 2024
I recommend qqbot-media for anyone iterating fast on agent tooling; clear intent and a small, reviewable surface area.
- ★★★★★William Ghosh· Dec 12, 2024
Solid pick for teams standardizing on skills: qqbot-media is focused, and the summary matches what you get after install.
- ★★★★★Dhruvi Jain· Dec 8, 2024
Useful defaults in qqbot-media — fewer surprises than typical one-off scripts, and it plays nicely with `npx skills` flows.
- ★★★★★Daniel Flores· Dec 8, 2024
Useful defaults in qqbot-media — fewer surprises than typical one-off scripts, and it plays nicely with `npx skills` flows.
- ★★★★★Harper Ndlovu· Dec 4, 2024
qqbot-media reduced setup friction for our internal harness; good balance of opinion and flexibility.
- ★★★★★Oshnikdeep· Nov 27, 2024
qqbot-media is among the better-maintained entries we tried; worth keeping pinned for repeat workflows.
- ★★★★★Chen Agarwal· Nov 27, 2024
qqbot-media is among the better-maintained entries we tried; worth keeping pinned for repeat workflows.
- ★★★★★Harper Agarwal· Nov 27, 2024
Useful defaults in qqbot-media — fewer surprises than typical one-off scripts, and it plays nicely with `npx skills` flows.
- ★★★★★Harper Abbas· Nov 15, 2024
qqbot-media fits our agent workflows well — practical, well scoped, and easy to wire into existing repos.
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