humanize

humanizerai/agent-skills · updated May 10, 2026

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$npx skills add https://github.com/humanizerai/agent-skills --skill humanize
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summary

Transform AI-generated text into natural writing that bypasses AI detectors.

  • Three intensity levels (light, medium, aggressive) adjust how extensively the text is rewritten, with credit usage based on word count
  • Provides before/after AI detection scores to show improvement against detectors like GPTZero, Turnitin, and Originality.ai
  • Requires HumanizerAI API key and consumes 1 credit per word processed; detection scoring is free
skill.md

Humanize AI Text

Transform AI-generated content into natural, human-like writing using the HumanizerAI API.

How It Works

When the user invokes /humanize, you should:

  1. Parse $ARGUMENTS for text and optional --intensity flag
  2. Call the HumanizerAI API to humanize the text
  3. Present the humanized text with before/after scores
  4. Show remaining credits

Parsing Arguments

The user may provide:

  • Just text: /humanize [their text]
  • With intensity: /humanize --intensity aggressive [their text]

Default intensity is medium.

Intensity Levels

Value Name Description Best For
light Light Subtle changes, preserves style Already-edited text, low AI scores
medium Medium Balanced rewrites (default) Most use cases
aggressive Bypass Maximum bypass mode High AI scores, strict detectors

API Call

Make a POST request to https://humanizerai.com/api/v1/humanize:

Authorization: Bearer $HUMANIZERAI_API_KEY
Content-Type: application/json

{
  "text": "<user's text>",
  "intensity": "medium"
}

Response Format

Present results like this:

## Humanization Complete

**Score:** X → Y (improvement)
**Words Processed:** N
**Credits Remaining:** X

---
### Humanized Text

[The humanized text]

---

[Recommendation based on final score]

Credit Usage

Error Handling

Insufficient Credits

If the user doesn't have enough credits:

  1. Show how many credits are needed vs available
  2. Direct them to https://humanizerai.com/dashboard to top up

Invalid API Key

  1. Check HUMANIZERAI_API_KEY environment variable
  2. Direct to https://humanizerai.com to get a key

Rate Limit

If rate limited, suggest waiting or upgrading to Business plan.

how to use humanize

How to use humanize 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 humanize
2

Execute installation command

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

$npx skills add https://github.com/humanizerai/agent-skills --skill humanize

The skills CLI fetches humanize from GitHub repository humanizerai/agent-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/humanize

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

GET_STARTED →

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)
  • No comments yet — start the thread.
general reviews

Ratings

4.838 reviews
  • Chaitanya Patil· Dec 24, 2024

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

  • Pratham Ware· Dec 20, 2024

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

  • Michael Diallo· Dec 12, 2024

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

  • Arjun Abebe· Dec 8, 2024

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

  • Aisha Mensah· Nov 27, 2024

    humanize reduced setup friction for our internal harness; good balance of opinion and flexibility.

  • Piyush G· Nov 15, 2024

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

  • Evelyn Singh· Nov 3, 2024

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

  • Benjamin Malhotra· Oct 22, 2024

    humanize reduced setup friction for our internal harness; good balance of opinion and flexibility.

  • Ama Agarwal· Oct 18, 2024

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

  • Shikha Mishra· Oct 6, 2024

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

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