dbskill-upgrade

dontbesilent2025/dbskill · updated Apr 8, 2026

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$npx skills add https://github.com/dontbesilent2025/dbskill --skill dbskill-upgrade
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summary

升级 dbskill 到最新版本,显示更新内容。

skill.md

dbskill-upgrade

升级 dbskill 到最新版本,显示更新内容。

使用场景

  • 用户主动调用 /dbskill-upgrade 升级
  • 显示版本变化和更新内容

升级流程

Step 1: 检测安装位置

if [ -d "$HOME/.claude/skills/dbs" ]; then
  INSTALL_DIR="$HOME/.claude/skills"
  echo "Install location: $INSTALL_DIR"
else
  echo "ERROR: dbskill not found in ~/.claude/skills/"
  exit 1
fi

Step 2: 获取当前版本

OLD_VERSION=$(cat "$HOME/.claude/skills/dbskill-upgrade/../../VERSION" 2>/dev/null || echo "unknown")
echo "Current version: $OLD_VERSION"

Step 3: 获取远程版本

REMOTE_VERSION=$(curl -sL https://raw.githubusercontent.com/dontbesilent2025/dbskill/main/VERSION || echo "")
if [ -z "$REMOTE_VERSION" ]; then
  echo "ERROR: Cannot fetch remote version"
  exit 1
fi
echo "Remote version: $REMOTE_VERSION"

Step 4: 比较版本

如果 OLD_VERSION 等于 REMOTE_VERSION,告诉用户已是最新版本,结束。

否则继续升级。

Step 5: 备份当前版本

BACKUP_DIR="$HOME/.claude/skills/.dbskill-backup-$(date +%Y%m%d-%H%M%S)"
mkdir -p "$BACKUP_DIR"
cp -r "$HOME/.claude/skills"/dbs* "$BACKUP_DIR/" 2>/dev/null || true
echo "Backup created: $BACKUP_DIR"

Step 6: 下载最新版本

TMP_DIR=$(mktemp -d)
git clone --depth 1 https://github.com/dontbesilent2025/dbskill.git "$TMP_DIR/dbskill"
if [ $? -ne 0 ]; then
  echo "ERROR: Failed to clone repository"
  exit 1
fi
echo "Downloaded to: $TMP_DIR/dbskill"

Step 7: 替换旧版本

rm -rf "$HOME/.claude/skills"/dbs*
cp -r "$TMP_DIR/dbskill/skills"/dbs* "$HOME/.claude/skills/"
rm -rf "$TMP_DIR"
echo "Upgrade completed"

如果复制失败,从备份恢复:

if [ $? -ne 0 ]; then
  echo "ERROR: Upgrade failed, restoring from backup..."
  rm -rf "$HOME/.claude/skills"/dbs*
  cp -r "$BACKUP_DIR"/* "$HOME/.claude/skills/"
  echo "Restored from backup"
  exit 1
fi

Step 8: 显示更新内容

读取 $HOME/.claude/skills/dbs/../../README.md(如果存在),提取从 OLD_VERSIONREMOTE_VERSION 之间的更新内容。

格式:

dbskill v{REMOTE_VERSION} — 从 v{OLD_VERSION} 升级成功!

更新内容:
- [从 README 提取的更新要点]

升级完成!

Step 9: 清理备份

询问用户是否删除备份:

echo "Backup location: $BACKUP_DIR"
echo "Keep backup? (will be auto-deleted in 7 days if not used)"

不强制删除,让用户自己决定。

错误处理

  • 网络失败:提示用户检查网络连接
  • Git clone 失败:从备份恢复
  • 文件复制失败:从备份恢复

注意事项

  • 只支持通过 ~/.claude/skills/ 安装的版本
  • 升级前自动备份,失败时自动恢复
  • 不需要用户手动操作 git
how to use dbskill-upgrade

How to use dbskill-upgrade on Cursor

AI-first code editor with Composer

1

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 dbskill-upgrade
2

Execute installation command

Execute the skills CLI command in your project's root directory to begin installation:

$npx skills add https://github.com/dontbesilent2025/dbskill --skill dbskill-upgrade

The skills CLI fetches dbskill-upgrade from GitHub repository dontbesilent2025/dbskill and configures it for Cursor.

3

Select Cursor when prompted

The CLI will show a list of available agents. Use arrow keys to navigate and space to select Cursor:

◆ Which agents do you want to install to?
│ ── Universal (.agents/skills) ── always included ────
│ • Amp
│ • Antigravity
│ • Cline
│ • Codex
│ ●Cursor(selected)
│ • Cursor
│ • Windsurf
4

Verify installation

Confirm successful installation by checking the skill directory location:

.cursor/skills/dbskill-upgrade

Reload or restart Cursor to activate dbskill-upgrade. Access the skill through slash commands (e.g., /dbskill-upgrade) 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

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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. 1.Install product management skill
  2. 2.Start with user story generation for known feature
  3. 3.Progress to competitive analysis: research 2-3 competitors
  4. 4.Use for roadmap prioritization: apply RICE/ICE scoring
  5. 5.Draft stakeholder communications and refine based on feedback
  6. 6.Build template library for recurring PM tasks
  7. 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

  1. 1Basic: user stories, feature specs, status updates
  2. 2Intermediate: competitive analysis, prioritization frameworks, PRDs
  3. 3Advanced: product strategy, go-to-market planning, OKR setting
  4. 4Expert: product vision, market positioning, business model innovation

Discussion

Product Hunt–style comments (not star reviews)
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general reviews

Ratings

4.650 reviews
  • Ama Tandon· Dec 28, 2024

    dbskill-upgrade fits our agent workflows well — practical, well scoped, and easy to wire into existing repos.

  • Olivia Mensah· Dec 24, 2024

    dbskill-upgrade has been reliable in day-to-day use. Documentation quality is above average for community skills.

  • Noor Chen· Dec 16, 2024

    Registry listing for dbskill-upgrade matched our evaluation — installs cleanly and behaves as described in the markdown.

  • Chaitanya Patil· Dec 12, 2024

    dbskill-upgrade fits our agent workflows well — practical, well scoped, and easy to wire into existing repos.

  • Arya Jain· Nov 19, 2024

    dbskill-upgrade is among the better-maintained entries we tried; worth keeping pinned for repeat workflows.

  • Arjun Khan· Nov 7, 2024

    Useful defaults in dbskill-upgrade — fewer surprises than typical one-off scripts, and it plays nicely with `npx skills` flows.

  • Piyush G· Nov 3, 2024

    dbskill-upgrade is among the better-maintained entries we tried; worth keeping pinned for repeat workflows.

  • Arjun Smith· Oct 26, 2024

    I recommend dbskill-upgrade for anyone iterating fast on agent tooling; clear intent and a small, reviewable surface area.

  • Shikha Mishra· Oct 22, 2024

    Keeps context tight: dbskill-upgrade is the kind of skill you can hand to a new teammate without a long onboarding doc.

  • Kwame Tandon· Oct 10, 2024

    Keeps context tight: dbskill-upgrade is the kind of skill you can hand to a new teammate without a long onboarding doc.

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