Agent skill

Content Scoring

Score content against the 10 GEO criteria with evidence and prioritized fixes.

Install Content Scoring

skills CLI

$ npx skills add mverab/eGEOagents --skill content-scoring -a claude-code

Project install by default; add -g for ~/.claude/skills/.

GitHub CLI

$ gh skill install mverab/eGEOagents content-scoring --agent claude-code

Project scope by default; add --scope user for a personal install. Needs GitHub CLI 2.90.0 or later (public preview).

Manual copy

$ git clone --depth 1 https://github.com/mverab/eGEOagents.git skills-src && mkdir -p .claude/skills && cp -r skills-src/.claude/skills/content-scoring .claude/skills/content-scoring && rm -rf skills-src

Use ~/.claude/skills/ instead of .claude/skills for a personal install. The folder must contain SKILL.md.

Claude Code skills documentation · loads skills from .claude/skills/

Paste into Claude Code

Install the "content-scoring" agent skill from https://github.com/mverab/eGEOagents/tree/main/.claude/skills/content-scoring into .claude/skills/content-scoring/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "content-scoring", then confirm the skill loads.

Claude Code copies the folder itself, the same result as the manual copy. Check what it changed before you commit it.

$skill-installer

$skill-installer install https://github.com/mverab/eGEOagents/tree/main/.claude/skills/content-scoring

Type this inside Codex. $skill-installer <name> installs a curated skill from openai/skills. The installer writes to $CODEX_HOME/skills (default ~/.codex/skills). Restart Codex if the skill does not show up.

skills CLI

$ npx skills add mverab/eGEOagents --skill content-scoring -a codex

Project install goes to .agents/skills/; add -g for ~/.codex/skills/.

GitHub CLI

$ gh skill install mverab/eGEOagents content-scoring --agent codex

Project scope by default (.agents/skills/); add --scope user for a personal install.

Manual copy

$ git clone --depth 1 https://github.com/mverab/eGEOagents.git skills-src && mkdir -p .agents/skills && cp -r skills-src/.claude/skills/content-scoring .agents/skills/content-scoring && rm -rf skills-src

Use ~/.agents/skills/ instead of .agents/skills for a personal install.

Codex skills documentation · loads skills from .agents/skills/

Paste into Codex

Install the "content-scoring" agent skill from https://github.com/mverab/eGEOagents/tree/main/.claude/skills/content-scoring into .agents/skills/content-scoring/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "content-scoring", then confirm the skill loads.

Codex copies the folder itself, the same result as the manual copy. Check what it changed before you commit it.

skills CLI

$ npx skills add mverab/eGEOagents --skill content-scoring -a cursor

Project install goes to .agents/skills/; add -g for ~/.cursor/skills/.

GitHub CLI

$ gh skill install mverab/eGEOagents content-scoring --agent cursor

Project scope by default (.agents/skills/); add --scope user for a personal install.

Manual copy

$ git clone --depth 1 https://github.com/mverab/eGEOagents.git skills-src && mkdir -p .cursor/skills && cp -r skills-src/.claude/skills/content-scoring .cursor/skills/content-scoring && rm -rf skills-src

Use ~/.cursor/skills/ instead of .cursor/skills for a personal install.

Cursor skills documentation · loads skills from .cursor/skills/, .agents/skills/, .claude/skills/, .codex/skills/

Paste into Cursor

Install the "content-scoring" agent skill from https://github.com/mverab/eGEOagents/tree/main/.claude/skills/content-scoring into .cursor/skills/content-scoring/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "content-scoring", then confirm the skill loads.

Cursor copies the folder itself, the same result as the manual copy. Check what it changed before you commit it.

gemini skills install

$ gemini skills install https://github.com/mverab/eGEOagents.git --path .claude/skills/content-scoring

--scope user (default) or --scope workspace; --path is the subfolder of the repo that holds the skill; --consent skips the security confirmation prompt.

skills CLI

$ npx skills add mverab/eGEOagents --skill content-scoring -a gemini-cli

Project install goes to .agents/skills/; add -g for ~/.gemini/skills/.

GitHub CLI

$ gh skill install mverab/eGEOagents content-scoring --agent gemini-cli

Project scope by default (.agents/skills/); add --scope user for a personal install.

Manual copy

$ git clone --depth 1 https://github.com/mverab/eGEOagents.git skills-src && mkdir -p .gemini/skills && cp -r skills-src/.claude/skills/content-scoring .gemini/skills/content-scoring && rm -rf skills-src

Use ~/.gemini/skills/ instead of .gemini/skills for a personal install, then run /skills reload.

Gemini CLI skills documentation · loads skills from .gemini/skills/, .agents/skills/

Paste into Gemini CLI

Install the "content-scoring" agent skill from https://github.com/mverab/eGEOagents/tree/main/.claude/skills/content-scoring into .gemini/skills/content-scoring/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "content-scoring", then confirm the skill loads.

Gemini CLI copies the folder itself, the same result as the manual copy. Check what it changed before you commit it.

GitHub CLI

$ gh skill install mverab/eGEOagents content-scoring

Installs for Copilot at project scope by default; add --scope user for a personal install. Preview a skill first with gh skill preview. Needs GitHub CLI 2.90.0 or later (public preview).

skills CLI

$ npx skills add mverab/eGEOagents --skill content-scoring -a github-copilot

Project install goes to .agents/skills/; add -g for ~/.copilot/skills/.

Manual copy

$ git clone --depth 1 https://github.com/mverab/eGEOagents.git skills-src && mkdir -p .github/skills && cp -r skills-src/.claude/skills/content-scoring .github/skills/content-scoring && rm -rf skills-src

Use ~/.copilot/skills/ instead of .github/skills for a personal install. Commit .github/skills so cloud agent and code review can use it.

GitHub Copilot skills documentation · loads skills from .github/skills/, .claude/skills/, .agents/skills/

Paste into GitHub Copilot

Install the "content-scoring" agent skill from https://github.com/mverab/eGEOagents/tree/main/.claude/skills/content-scoring into .github/skills/content-scoring/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "content-scoring", then confirm the skill loads.

GitHub Copilot copies the folder itself, the same result as the manual copy. Check what it changed before you commit it.

skills CLI

$ npx skills add mverab/eGEOagents --skill content-scoring -a opencode

OpenCode documents no install command of its own. Project install goes to .agents/skills/; add -g for ~/.config/opencode/skills/.

GitHub CLI

$ gh skill install mverab/eGEOagents content-scoring --agent opencode

Project scope by default (.agents/skills/); add --scope user for a personal install.

Manual copy

$ git clone --depth 1 https://github.com/mverab/eGEOagents.git skills-src && mkdir -p .opencode/skills && cp -r skills-src/.claude/skills/content-scoring .opencode/skills/content-scoring && rm -rf skills-src

Use ~/.config/opencode/skills/ instead of .opencode/skills for a personal install.

OpenCode skills documentation · loads skills from .opencode/skills/, .claude/skills/, .agents/skills/

Paste into OpenCode

Install the "content-scoring" agent skill from https://github.com/mverab/eGEOagents/tree/main/.claude/skills/content-scoring into .opencode/skills/content-scoring/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "content-scoring", then confirm the skill loads.

OpenCode copies the folder itself, the same result as the manual copy. Check what it changed before you commit it.

Facts

Skill name: content-scoring
GitHub stars: 197
Token cost: ~930 tokens
SKILL.md length: 165 words
Files: 1
Skills in repo: 5
Repo updated: Oct 8, 2026
First seen: Oct 7, 2026
Licence: MIT

At a glance

Score content against the 10 GEO criteria with evidence and prioritized fixes.

Users ask to score
SKILL.md covers The 10 GEO Criteria, Scoring Guide, Output Format and Rules
Instructions only: no scripts, shell commands, URLs or credentials in SKILL.md
Estimate ranking strength

What it does

Content Scoring is an agent skill from mverab/eGEOagents. Score content against the 10 GEO criteria with evidence and prioritized fixes. Use when users ask to score, rate, evaluate, or estimate ranking strength.

Its SKILL.md is about 930 tokens, which your agent loads only when the skill is triggered. It is a single SKILL.md file with no bundled scripts.

It sits in Marketing & SEO, covering AI search optimization. The repository describes itself as: Open-source Generative Engine Optimization (GEO) & Answer Engine Optimization (AEO) toolkit — optimize content to rank in ChatGPT, Perplexity, Gemini & Claude. AI SEO / LLM SEO… The licence is MIT.

When your agent uses it

Users ask to score
Estimate ranking strength

Example prompts

“/content-scoring”

What it can do on your machine

Read from SKILL.md and the folder at commit 58ee654. It shows what the files ask for, not the result of running them.

Tool permissions
Pre-approves nothing: there is no allowed-tools line, so your agent's usual permission prompts apply.
From allowed-tools in the SKILL.md frontmatter.
Runs code
No scripts in the folder and no shell commands in SKILL.md.
From the folder's file list and the shell code blocks in SKILL.md.
Network
No URLs in SKILL.md.
From URLs in SKILL.md, links to its own repository left out.
Credentials
Names no API keys, tokens, secrets or passwords.
From names ending in _API_KEY, _TOKEN, _SECRET, _KEY or _PASSWORD in SKILL.md.

Context cost

Content Scoring loads about 930 tokens when it runs. Until then it costs about 42 tokens; SKILL.md has 165 words of instructions outside code blocks.

Always · name and description, kept in context so the agent knows when to use it: ~42
When it runs · the whole SKILL.md, loaded when a task matches: ~930

Estimates: characters ÷ 4, the usual rule of thumb; real counts depend on the model's tokenizer. Scripts and assets cost tokens only if the agent reads them.

Safety

Auto-check passed

The automated check found no risky patterns in SKILL.md.

Automated static check — not a guarantee. Review scripts before installing. It scans the text of SKILL.md for risky patterns (piping downloads into a shell, reading credential files, hidden Unicode, destructive commands); files beside SKILL.md are not scanned.

SKILL.md

The full file from mverab/eGEOagents at commit 58ee654, republished under its MIT licence (© mverab). 165 words, ~930 tokens.

Download SKILL.mdSave it as .claude/skills/content-scoring/SKILL.md (or your agent's skills folder).

name: content-scoring
description: Score content against the 10 GEO criteria with evidence and prioritized fixes. Use when users ask to score, rate, evaluate, or estimate ranking strength.

Content Scoring Skill

When scoring content for GEO optimization:

The 10 GEO Criteria

Score each criterion 0-10:

#	Criterion	What to Look For
1	Ranking Emphasis	"best", "top", "#1", superlatives, leadership claims
2	User Intent	Direct answers, addresses specific needs, solves problems
3	Competitive Diff	Unique advantages, "unlike others", differentiators
4	Social Proof	Stats, testimonials, reviews, customer counts, ratings
5	Narrative	Engaging flow, persuasive language, compelling story
6	Authority	Expert tone, credentials, specific knowledge, confidence
7	USPs	Clear unique value, what makes it special
8	Urgency	Time limits, scarcity, "now", limited availability
9	Scannable	Headers, bullets, short paragraphs, clear structure
10	Factual	Verifiable claims, specific numbers, accurate info

Scoring Guide

0-2: Missing or severely lacking
3-4: Present but weak
5-6: Adequate, room for improvement
7-8: Good, minor improvements possible
9-10: Excellent, near optimal

Output Format

┌─────────────────────────────────────────────────────────────┐
│  📊 GEO CONTENT SCORE                                       │
├─────────────────────────────────────────────────────────────┤
│                                                             │
│  OVERALL SCORE: XX/100                                      │
│  ██████████████████░░░░░░░░░░  XX%                          │
│                                                             │
│  BREAKDOWN                                                  │
│  ─────────                                                  │
│  1. Ranking Emphasis    ████████░░  8/10                    │
│  2. User Intent         ██████████  10/10                   │
│  3. Competitive Diff    ████░░░░░░  4/10                    │
│  4. Social Proof        ██░░░░░░░░  2/10  ⚠️ Priority       │
│  5. Narrative           ██████░░░░  6/10                    │
│  6. Authority           ████████░░  8/10                    │
│  7. USPs                ██████░░░░  6/10                    │
│  8. Urgency             ░░░░░░░░░░  0/10  ⚠️ Priority       │
│  9. Scannable           ████████░░  8/10                    │
│  10. Factual            ██████████  10/10                   │
│                                                             │
│  TOP PRIORITIES                                             │
│  ──────────────                                             │
│  1. Add social proof (+15-20 points potential)              │
│  2. Add urgency signals (+5-10 points potential)            │
│  3. Strengthen competitive differentiation (+8 points)      │
│                                                             │
│  EVIDENCE                                                   │
│  ────────                                                   │
│  ✓ Good: "industry-leading solution" (ranking emphasis)     │
│  ✗ Missing: No customer testimonials (social proof)         │
│  ✗ Missing: No time-sensitive offers (urgency)              │
│                                                             │
└─────────────────────────────────────────────────────────────┘

Rules

Always show evidence from the actual content
Prioritize improvements by potential impact
Be specific about what's missing and how to fix it
Calculate total score as sum of all criteria

Files

Just SKILL.md in .claude/skills/content-scoring of mverab/eGEOagents.

Open the folder on GitHubat commit 58ee654

Compare with similar skills

Content Scoring next to the 5 skills that share the most tags, products or categories with it. Stars are the repository's; “used in” counts other GitHub owners with a copy.

Content Scoring compared with similar skills
Skill	Stars	Used in	Tokens	Auto-check	Licence	Repo updated
Content Scoring this skillmverab/eGEOagents	197	—	~930	Automated safety check: Pass	MIT	today
Geo Fundamentalswasp-lang/wasp	19k	9 repos	~861	Automated safety check: Pass	MIT	today
SEO GeoReScienceLab/opc-skills	1.8k	4 repos	~2.1k	Automated safety check: Pass	Apache-2.0	today
GEO-First SEO Audit Toolzubair-trabzada/geo-seo-claude	11k	—	~2.8k	Automated safety check: Notes	MIT	yesterday
GEO Monthly Delta Reportzubair-trabzada/geo-seo-claude	11k	—	~2.4k	Automated safety check: Notes	MIT	yesterday
SEO DataforseoAgriciDaniel/codex-seo	791	2 repos	~4.6k	Automated safety check: Pass	MIT	26 days ago

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Questions about Content Scoring

What does Content Scoring do?

Score content against the 10 GEO criteria with evidence and prioritized fixes. Content Scoring is an agent skill from mverab/eGEOagents. Score content against the 10 GEO criteria with evidence and prioritized fixes.

When should I use Content Scoring?

Content Scoring fits situations like: users ask to score; estimate ranking strength.

How do I install Content Scoring in Claude Code?

Run `npx skills add mverab/eGEOagents --skill content-scoring -a claude-code`. Or copy the skill folder (.claude/skills/content-scoring in mverab/eGEOagents) into .claude/skills/content-scoring in your project. Claude Code loads it when a task matches its description.

How do I install Content Scoring in Codex?

Run `npx skills add mverab/eGEOagents --skill content-scoring -a codex`. Or copy the skill folder (.claude/skills/content-scoring in mverab/eGEOagents) into .agents/skills/content-scoring in your project. Codex loads it when a task matches its description.

Can I use Content Scoring in Cursor, Gemini CLI or GitHub Copilot?

Cursor, Gemini CLI, GitHub Copilot and OpenCode also load SKILL.md folders. With the skills CLI, run `npx skills add mverab/eGEOagents --skill content-scoring -a cursor` (or -a gemini-cli, github-copilot or opencode for the others). To copy it by hand, put the folder in .cursor/skills/content-scoring, .gemini/skills/content-scoring, .github/skills/content-scoring and .opencode/skills/content-scoring in your project.

What does Content Scoring need to run?

SKILL.md names no scripts, command-line tools or credentials: Content Scoring is instructions for the agent only.

Does Content Scoring access the network?

SKILL.md contains no URLs. Any network use would come from the scripts or tools the agent runs. This is read from the text; nothing was executed.

Is Content Scoring safe to install?

Our automated static check of SKILL.md found no risky patterns, such as piping downloads into a shell, reading credential files or hidden Unicode. It is not a guarantee. Review the folder before installing.

What licence does Content Scoring use?

Content Scoring is published under the MIT licence (the repository's licence). It allows redistribution, so the full SKILL.md is shown on this page.

How many tokens does Content Scoring use?

About 930 tokens (SKILL.md is roughly 3.7k characters). Agents keep only the skill's name and description in context until a task matches; then they load SKILL.md in full.

What are the alternatives to Content Scoring?

Skills that share tags, products or a category with Content Scoring: Geo Fundamentals (wasp-lang/wasp, 19k stars), SEO Geo (ReScienceLab/opc-skills, 1.8k stars), GEO-First SEO Audit Tool (zubair-trabzada/geo-seo-claude, 11k stars) and GEO Monthly Delta Report (zubair-trabzada/geo-seo-claude, 11k stars). The comparison table on this page puts their stars, adoption, token cost, safety result and licence side by side.

Who maintains Content Scoring?

mverab (a GitHub user) maintains it in mverab/eGEOagents, which has 197 GitHub stars. The repository holds 5 skills in this directory. The repository was last updated on October 8, 2026.

Source: mverab/eGEOagents on GitHub. Facts on this page come from the repository at the commit we read; the author's words are quoted as theirs.

Content Scoring

Install Content Scoring

Facts

At a glance

What it does

When your agent uses it

Example prompts

What it can do on your machine

Tool permissions

Runs code

Network

Credentials

Context cost

Safety

SKILL.md

Content Scoring Skill

The 10 GEO Criteria

Scoring Guide

Output Format

Rules

Files

Compare with similar skills

Similar skills

Geo Fundamentals

SEO Geo

GEO-First SEO Audit Tool

GEO Monthly Delta Report

SEO Dataforseo

Fire Your SEO Agency

More from mverab/eGEOagents

Competitive Analysis

Geo Loop

Schema Generator

Validation Doctor

Questions about Content Scoring

Install Content Scoring

Facts

At a glance

What it does

When your agent uses it

Example prompts

What it can do on your machine

Tool permissions

Runs code

Network

Credentials

Context cost

Safety

SKILL.md

Content Scoring Skill

The 10 GEO Criteria

Scoring Guide

Output Format

Rules

Files

Compare with similar skills

Similar skills

More from mverab/eGEOagents

Related

Questions about Content Scoring