fixing-metadata

ibelick/ui-skills · updated Jun 2, 2026

MDX-style export adds YAML metadata + attribution linking explainx.ai and this canonical listing URL.

$npx skills add https://github.com/ibelick/ui-skills --skill fixing-metadata
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summary

Audit and fix HTML metadata including titles, descriptions, canonical URLs, Open Graph tags, and structured data.

  • Covers eight priority categories: correctness and duplication, title and description, canonical and indexing, social cards, icons and manifest, structured data, locale and alternates, and tool boundaries
  • Ensures metadata consistency across page titles, descriptions, canonical URLs, and Open Graph tags; prevents duplicates and enforces deterministic values
  • Includes rules f
skill.md

Workflow

  1. Identify pages with missing or incorrect metadata (titles, descriptions, canonical, OG tags)
  2. Audit against the priority rules below — fix critical issues (duplicates, indexing) first
  3. Ensure title, description, canonical, and og:url all agree with each other
  4. Verify social cards render correctly on a real URL, not localhost
  5. Keep diffs minimal and scoped to metadata only — do not refactor unrelated code

when to apply

Reference these guidelines when:

  • adding or changing page titles, descriptions, canonical, robots
  • implementing Open Graph or Twitter card metadata
  • setting favicons, app icons, manifest, theme-color
  • building shared SEO components or layout metadata defaults
  • adding structured data (JSON-LD)
  • changing locale, alternate languages, or canonical routing
  • shipping new pages, marketing pages, or shareable links

rule categories by priority

priority category impact
1 correctness and duplication critical
2 title and description high
3 canonical and indexing high
4 social cards high
5 icons and manifest medium
6 structured data medium
7 locale and alternates low-medium
8 tool boundaries critical

quick reference

1. correctness and duplication (critical)

  • define metadata in one place per page, avoid competing systems
  • do not emit duplicate title, description, canonical, or robots tags
  • metadata must be deterministic, no random or unstable values
  • escape and sanitize any user-generated or dynamic strings
  • every page must have safe defaults for title and description

2. title and description (high)

  • every page must have a title
  • use a consistent title format across the site
  • keep titles short and readable, avoid stuffing
  • shareable or searchable pages should have a meta description
  • descriptions must be plain text, no markdown or quote spam

3. canonical and indexing (high)

  • canonical must point to the preferred URL for the page
  • use noindex only for private, duplicate, or non-public pages
  • robots meta must match actual access intent
  • previews or staging pages should be noindex by default when possible
  • paginated pages must have correct canonical behavior

4. social cards (high)

  • shareable pages must set Open Graph title, description, and image
  • Open Graph and Twitter images must use absolute URLs
  • prefer correct image dimensions and stable aspect ratios
  • og:url must match the canonical URL
  • use a sensible og:type, usually website or article
  • set twitter:card appropriately, summary_large_image by default

5. icons and manifest (medium)

  • include at least one favicon that works across browsers
  • include apple-touch-icon when relevant
  • manifest must be valid and referenced when used
  • set theme-color intentionally to avoid mismatched UI chrome
  • icon paths should be stable and cacheable

6. structured data (medium)

  • do not add JSON-LD unless it clearly maps to real page content
  • JSON-LD must be valid and reflect what is actually rendered
  • do not invent ratings, reviews, prices, or organization details
  • prefer one structured data block per page unless required

7. locale and alternates (low-medium)

  • set the html lang attribute correctly
  • set og:locale when localization exists
  • add hreflang alternates only when pages truly exist
  • localized pages must canonicalize correctly per locale

8. tool boundaries (critical)

  • prefer minimal changes, do not refactor unrelated code
  • do not migrate frameworks or SEO libraries unless requested
  • follow the project's existing metadata pattern (Next.js metadata API, react-helmet, manual head, etc.)

review guidance

  • fix critical issues first (duplicates, canonical, indexing)
  • ensure title, description, canonical, and og:url agree
  • verify social cards on a real URL, not localhost
  • prefer stable, boring metadata over clever or dynamic
  • keep diffs minimal and scoped to metadata only
how to use fixing-metadata

How to use fixing-metadata 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 fixing-metadata
2

Execute installation command

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

$npx skills add https://github.com/ibelick/ui-skills --skill fixing-metadata

The skills CLI fetches fixing-metadata from GitHub repository ibelick/ui-skills 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/fixing-metadata

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

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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

4.735 reviews
  • Ganesh Mohane· Dec 8, 2024

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

  • Kofi Chawla· Dec 8, 2024

    Solid pick for teams standardizing on skills: fixing-metadata is focused, and the summary matches what you get after install.

  • Amina Verma· Dec 4, 2024

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

  • Sakshi Patil· Nov 27, 2024

    fixing-metadata reduced setup friction for our internal harness; good balance of opinion and flexibility.

  • Meera Robinson· Nov 23, 2024

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

  • Chaitanya Patil· Oct 18, 2024

    We added fixing-metadata from the explainx registry; install was straightforward and the SKILL.md answered most questions upfront.

  • Meera Choi· Oct 14, 2024

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

  • Neel Diallo· Oct 10, 2024

    fixing-metadata reduced setup friction for our internal harness; good balance of opinion and flexibility.

  • Piyush G· Sep 25, 2024

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

  • Jin Reddy· Sep 25, 2024

    We added fixing-metadata from the explainx registry; install was straightforward and the SKILL.md answered most questions upfront.

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