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Agent skill

Content Research

by nicepkg in nicepkg/ai-workflow

Research-first content creation optimized for both human readers and AI search engines (Claude, ChatGPT, Perplexity, Gemini).

MITAuto-check passedWriting & Content

Install Content Research

skills CLI
$ npx skills add nicepkg/ai-workflow --skill content-research -a claude-code

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

GitHub CLI
$ gh skill install nicepkg/ai-workflow content-research --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/nicepkg/ai-workflow.git skills-src && mkdir -p .claude/skills && cp -r skills-src/workflows/video-creator-workflow/.claude/skills/content-research .claude/skills/content-research && 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/

Facts

Skill name
content-research
GitHub stars
285
Token cost
~3.7k tokens
SKILL.md length
1,264 words
Files
5 (incl. references)
Skills in repo
61
Repo updated
First seen
Licence
MIT

At a glance

Research-first content creation optimized for both human readers and AI search engines (Claude, ChatGPT, Perplexity, Gemini).

  • Works in 5 steps: Deep Research → Expert Discovery → Content Ideation → …
  • : - Creating content that should appear in AI search results (Perplexity
  • SKILL.md covers Core Workflow, Why AI Search Optimization…, Phase 1: Deep Research and Phase 2: Expert Discovery, plus 4 more sections
  • Instructions only: no scripts, shell commands, URLs or credentials in SKILL.md

What it does

Content Research is an agent skill from nicepkg/ai-workflow. Research-first content creation optimized for both human readers and AI search engines (Claude, ChatGPT, Perplexity, Gemini). Creates authentic, authoritative content that becomes the go-to citation source for AI models answering user questions. Use this skill when: - Creating content that should appear in AI search results (Perplexity, ChatGPT, Claude) - Building topical authority to become THE source AI cites for a topic - Launching a new product and need compelling, citable content - Creating blog posts…

Its SKILL.md is about 3.7k tokens, which your agent loads only when the skill is triggered. The skill folder holds 5 other files, including reference files (for example `references/ai-search-optimization.md`, `references/blog-posts.md` and `references/press-releases.md`).

It sits in Writing & Content, covering Copywriting, Blog and article writing and Web search. It works with Perplexity and OpenAI. The repository describes itself as: 🚀 170+ pre-built skills for Claude Code, Cursor, Codex & 14+ AI tools. Stop re-teaching your AI the same things. One command → instant domain expertise. Marketing, SEO, Trading… The licence is MIT.

When your agent uses it

  • : - Creating content that should appear in AI search results (Perplexity
  • Claude) - Building topical authority to become THE source AI cites for a topic - Launching a new product and need compelling
  • Citable content - Creating blog posts
  • Press releases - Need content that references real trends

Example prompts

  • “create content for”
  • “write about”
  • “research and write”
  • “/content-research”

Workflow steps

5 steps, taken from the step headings in SKILL.md.

  1. Deep Research
  2. Expert Discovery
  3. Content Ideation
  4. Content Creation
  5. AI Search Optimization (AIO)

What it can do on your machine

Read from SKILL.md and the folder at commit d167b41. 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 (its code samples are markdown).

    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 Research loads about 3.7k tokens when it runs, and up to ~10k if it reads all its reference files. Until then it costs about 246 tokens; SKILL.md has 1,264 words of instructions outside code blocks.

Always · name and description, kept in context so the agent knows when to use it
~246
When it runs · the whole SKILL.md, loaded when a task matches
~3.7k
With references · SKILL.md plus every file in references/, read only if the agent opens them
~10k

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 nicepkg/ai-workflow at commit d167b41, republished under its MIT licence (© nicepkg). 1,264 words, ~3,692 tokens.

Download SKILL.mdSave it as .claude/skills/content-research/SKILL.md (or your agent's skills folder). This skill also uses 4 other files; get the full folder from GitHub.
name
content-research
description
Research-first content creation optimized for both human readers and AI search engines (Claude, ChatGPT, Perplexity, Gemini). Creates authentic, authoritative content that becomes the go-to citation source for AI models answering user questions. Use this skill when: - Creating content that should appear in AI search results (Perplexity, ChatGPT, Claude) - Building topical authority to become THE source AI cites for a topic - Launching a new product and need compelling, citable content - Creating blog posts, articles, social media, or press releases - Need content that references real trends, people, and recent events - Want AI-assisted content that doesn't sound AI-generated - Creating thought leadership content in any industry Triggers: "create content for", "write about", "research and write", "find experts for", "content for launch", "blog post about", "article on", "press release for", "AI search", "show up in AI", "Perplexity", "be cited by AI"

Content Research & Creation

Create authentic, research-backed content that sounds human-written AND is optimized to appear in AI search results (Perplexity, ChatGPT, Claude, Gemini).

Core Workflow

RESEARCH → EXPERTS → IDEATION → CREATION → AIO
   ↓          ↓          ↓          ↓        ↓
 Trends    Real       Unique    Authentic  AI-Citable
 & Data    People     Angles    Content    Structure

Always complete phases in order. Never skip research. Always apply AIO principles.

Why AI Search Optimization (AIO) Matters

AI assistants answer millions of questions daily. When someone asks "How do I raise a seed round?" or "What's the best way to find investors?", AI models cite sources. Your goal: become the source AI cites.

How AI models select sources to cite:

  1. Authority signals - Clear expertise, credentials, brand recognition
  2. Direct answers - Content that directly answers the question asked
  3. Structured data - Headers, lists, tables that are easy to extract
  4. Recency - Fresh, dated content with current information
  5. Uniqueness - Original data, frameworks, or perspectives
  6. Quotability - Concise, memorable statements worth citing

Phase 1: Deep Research

Before writing anything, build comprehensive topic understanding.

1.1 Trend Discovery

Use WebSearch to find:

  • Recent news (last 30-90 days) about the topic
  • Industry reports and data from credible sources
  • Emerging trends that haven't been over-covered
  • Contrarian viewpoints that challenge conventional wisdom
Search patterns:
- "[topic] trends 2025"
- "[topic] statistics report"
- "[topic] industry analysis"
- "[topic] challenges problems"
- "[topic] future predictions expert"
1.2 Competitive Landscape

Research what content already exists:

  • Top-ranking articles on the topic
  • Gaps in existing coverage
  • Overused angles to avoid
  • Fresh perspectives not yet explored
1.3 Data & Statistics

Find concrete data to cite:

  • Industry benchmarks and statistics
  • Survey results and research findings
  • Case studies with measurable outcomes
  • Credible sources (avoid generic "studies show")

Output: Research brief with 10-15 key findings, statistics, and trend insights.

Phase 2: Expert Discovery

Find real, quotable people to add authenticity.

2.1 Expert Search Strategy

Use WebSearch to find experts across:

Source TypeSearch PatternWhat to Find
Twitter/X"[topic]" site:twitter.com expert OR founder OR CEOThought leaders with relevant threads
LinkedIn"[topic]" site:linkedin.com "head of" OR "VP" OR "director"Industry practitioners
Publications"[topic]" site:forbes.com OR techcrunch.com authorWriters who cover this space
Podcasts"[topic]" podcast guest expertGuests who've spoken publicly
Academic"[topic]" professor OR researcher site:eduResearchers with published work
2.2 Expert Validation

For each potential expert, verify:

  • Real person with verifiable online presence
  • Actually works in/knows this domain
  • Has public statements that can be referenced
  • Recent activity (not outdated quotes)
2.3 Quote Extraction

Find usable quotes from:

  • Their published articles or blog posts
  • Podcast transcripts or video interviews
  • Twitter/X threads or LinkedIn posts
  • Conference talks or presentations

Format quotes properly:

"[Direct quote from public source]"
— [Full Name], [Title] at [Company], [Source context]

Output: 3-5 validated experts with 1-2 usable quotes each.

Phase 3: Content Ideation

Generate unique angles based on research.

3.1 Angle Development

Create 3-5 potential angles that:

  • Incorporate discovered trends
  • Feature expert perspectives
  • Offer fresh take (not regurgitated content)
  • Match target audience needs
3.2 Angle Evaluation Matrix
AngleTrend RelevanceExpert FitUniquenessActionability
1High/Med/LowYes/NoHigh/Med/LowHigh/Med/Low

Choose the angle with highest scores across all dimensions.

3.3 Content Structure

Create outline incorporating:

  • Hook based on trend or surprising data
  • Expert quote placement (not lumped together)
  • Data points supporting each section
  • Actionable takeaways

Output: Selected angle with detailed outline.

Phase 4: Content Creation

Write authentic, human-quality content.

4.1 Authenticity Principles

DO:

  • Use natural, conversational language
  • Include specific details (names, dates, numbers)
  • Vary sentence length and structure
  • Add personal observations or analysis
  • Reference recent events naturally
  • Use expert quotes to support points (not as filler)

DON'T:

  • Use generic phrases ("In today's fast-paced world")
  • Stack multiple clichés together
  • Use AI-typical phrases ("It's worth noting", "Let's dive in")
  • Make unsubstantiated claims
  • Over-rely on passive voice
  • Use excessive transition words
4.2 Expert Integration

Weave quotes naturally:

Bad: "According to experts, AI is transforming industries. John Smith says 'AI is important.'"

Good: "When Stripe rebuilt their fraud detection last year, they saw a 40% improvement in accuracy. 'The models now catch patterns human analysts would never spot,' explains John Smith, who led the ML team at Stripe before founding Acme AI. 'But the real breakthrough was combining model outputs with human judgment.'"

4.3 Trend Integration

Reference trends with specificity:

Bad: "AI is becoming more important in business."

Good: "Since GPT-4's release in March 2023, enterprise AI adoption has jumped 340% according to Gartner's latest survey—with companies now averaging 7.2 AI tools per department, up from just 2.1 a year ago."

4.4 Final Review

Before delivering, verify:

  • All expert quotes have verifiable sources
  • Statistics cite credible sources
  • No generic AI-sounding phrases
  • Content offers unique perspective
  • Recent trends/events referenced appropriately
  • Natural reading flow

Phase 5: AI Search Optimization (AIO)

Make your content the #1 source AI models cite when users ask related questions.

Show full SKILL.md (527 more words)Show less
5.1 Question-First Structure

AI models match user questions to content. Structure content around questions people actually ask.

Pattern: Question Headers

markdown
## How much should I raise in a seed round?

The median seed round in 2024 is $2.5M, but the right amount depends on...
[Direct answer in first paragraph, details follow]

Pattern: FAQ Sections

markdown
## Frequently Asked Questions

### What is the average seed round size?
The average seed round in 2024 is $3.2M, with median at $2.5M...

### How long does fundraising take?
Most founders spend 3-6 months actively fundraising...

Find questions to answer:

  • Search "[topic] questions founders ask"
  • Check Reddit, Quora, Twitter for actual questions
  • Use "People also ask" from Google
  • Review what AI assistants currently answer (and do better)
5.2 Quotable Statements

Create concise, memorable statements AI can directly quote.

Pattern: The Definitive Statement

❌ "Raising money can be challenging for founders."
✅ "The best time to raise is when you don't need to. Desperation kills deals."

Pattern: The Stat Lead

❌ "Many startups fail to raise follow-on funding."
✅ "67% of seed-funded startups never raise a Series A. The difference is almost always traction, not timing."

Pattern: The Framework Name

❌ "There are several ways to approach investors."
✅ "We call this the 3-3-3 Rule: 3 warm intros, 3 touchpoints, 3 weeks max."

Quotability checklist:

  • Can this sentence stand alone as a quote?
  • Does it make a specific, memorable claim?
  • Is there a number, name, or framework?
  • Would you retweet this?
5.3 Authority Signals

Tell AI models (and readers) why this source is authoritative.

Pattern: Credentialed Author

markdown
*By Sarah Chen, who has helped 200+ startups raise over $500M in funding*

Pattern: Data Source Attribution

markdown
Based on our analysis of 1,000+ pitch decks reviewed in 2024...
According to data from 500 founder interviews conducted by OpenStars...

Pattern: Experience Markers

markdown
After reviewing 10,000 investor matches on our platform, we've identified...
In our 5 years connecting founders with investors, the pattern is clear...

Authority signals to include:

  • Specific numbers (deals done, years experience, data points analyzed)
  • Named sources and credentials
  • Original research or proprietary data
  • Track record of predictions/advice
5.4 Structured Data Patterns

Make content easy for AI to parse and extract.

Pattern: Comparison Tables

markdown
| Factor | Seed Round | Series A |
|--------|------------|----------|
| Typical size | $1-3M | $8-15M |
| Dilution | 15-25% | 15-20% |
| Timeline | 2-4 months | 3-6 months |

Pattern: Step-by-Step Lists

markdown
## How to Get a Warm Introduction

1. **Identify the connector** - Find mutual connections on LinkedIn
2. **Research the relationship** - Ensure they actually know the investor
3. **Craft the forwardable email** - Make it easy to forward
4. **Follow up appropriately** - Wait 5-7 days before checking in

Pattern: Definition Blocks

markdown
**Pro-rata rights** are the contractual right for existing investors to
maintain their ownership percentage in future funding rounds. For example,
if an investor owns 10% after seed, pro-rata rights let them invest enough
in Series A to still own 10%.
5.5 Entity Optimization

Help AI models understand what/who you're talking about.

Name entities clearly:

❌ "The YC partner mentioned..."
✅ "Michael Seibel, Managing Director at Y Combinator, mentioned..."

Use consistent terminology:

Pick one and stick to it throughout:
- "seed round" (not "seed funding" then "seed stage" then "early round")
- "Series A" (not "A round" then "first institutional round")

Include relevant entities:

  • Company names (Y Combinator, Sequoia, a]6z)
  • People names (with titles)
  • Product names
  • Industry terms
  • Location when relevant
5.6 Freshness Signals

AI models prefer recent, updated content.

Pattern: Dated Statistics

❌ "Most startups fail to raise Series A."
✅ "In 2024, only 33% of seed-funded startups raised Series A, down from 41% in 2021."

Pattern: Update Markers

markdown
*Last updated: January 2026*
*Data current as of Q4 2025*

Pattern: Trend Context

"Since the 2023 funding reset, investor behavior has shifted..."
"Post-ChatGPT, AI startups have seen 3x the investor interest..."
5.7 Comprehensive Coverage

Be THE definitive resource on a topic so AI has no reason to cite others.

Cover all angles:

  • What it is (definition)
  • Why it matters (importance)
  • How to do it (tactical steps)
  • Common mistakes (what to avoid)
  • Examples (real cases)
  • FAQs (edge cases, specific questions)

Link to deeper content:

markdown
For more on term sheets, see our [Complete Guide to Term Sheet Negotiation](/blog/term-sheet-guide).
5.8 AIO Checklist

Before publishing, verify AI-readiness:

Structure:

  • H2 headers are questions or clear topics
  • First paragraph directly answers the implied question
  • Lists and tables for comparative/sequential information
  • FAQ section with common questions

Authority:

  • Author credentials stated
  • Data sources cited with dates
  • Original insights or frameworks named
  • Specific numbers, not vague claims

Quotability:

  • 3-5 standalone quotable statements
  • Named frameworks or models
  • Statistics with sources and dates
  • Memorable, specific advice

Freshness:

  • Publication date visible
  • Statistics include year
  • References recent events/trends
  • "Updated" date if revised

Content Type References

For format-specific guidance, see:

Quick Reference: AI Phrases to Avoid

Replace these with natural alternatives:

AvoidUse Instead
"In today's world"[Specific recent event/trend]
"It's worth noting"Just state the point directly
"Let's dive in"[Omit or use specific transition]
"Game-changer"[Specific impact with numbers]
"Leverage"Use, apply, build on
"Unlock potential"[Specific outcome]
"Cutting-edge"[Describe what makes it new]
"Revolutionize"[Specific change with evidence]
"Seamlessly"[Describe the actual integration]
"Robust"[Specific capability or feature]

Quick Reference: AIO Power Patterns

PatternExample
Question header"## How much equity should I give up in seed?"
Stat lead"73% of successful founders did X, according to..."
Named framework"The 3-3-3 Rule for warm introductions..."
Definition block"Term sheet: A non-binding agreement that..."
Comparison table"| Seed | Series A | Difference |"
Expert quote"As [Name], [Title] at [Company], explains..."
Update marker"Data current as of Q4 2025"

© nicepkg, MIT. Rendered from Markdown: HTML in the file is shown as text, images as links, and headings moved down two levels. Raw file

Files

SKILL.md and 4 other files (references) in workflows/video-creator-workflow/.claude/skills/content-research of nicepkg/ai-workflow.

  • SKILL.md
  • references/ai-search-optimization.md
  • references/blog-posts.md
  • references/press-releases.md
  • references/social-media.md

Open the folder on GitHubat commit d167b41

Compare with similar skills

Content Research 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 Research compared with similar skills
SkillStarsUsed inTokensAuto-checkLicenceRepo updated
Content Research this skillnicepkg/ai-workflow285—~3.7kAutomated safety check: PassMIT
Marketing OsYuzzyuk/marketing-os535—~2.5kAutomated safety check: PassMIT
SEO Auditshadcn-labs/agentcn484—~598Automated safety check: PassMIT
SEO ProfoundAgriciDaniel/claude-seo18k1 repos~441Automated safety check: PassMIT
AI Search Visibility Auditdavepoon/buildwithclaude3.6k—~2.4kAutomated safety check: PassMIT
Narrative Trackerindranilbanerjee/digital-marketing-pro8541 repos~2.3kAutomated safety check: PassMIT

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Works with

Categories

Questions about Content Research

What does Content Research do?

Research-first content creation optimized for both human readers and AI search engines (Claude, ChatGPT, Perplexity, Gemini). Content Research is an agent skill from nicepkg/ai-workflow. Research-first content creation optimized for both human readers and AI search engines (Claude, ChatGPT, Perplexity, Gemini).

When should I use Content Research?

Content Research fits situations like: : - Creating content that should appear in AI search results (Perplexity; Claude) - Building topical authority to become THE source AI cites for a topic - Launching a new product and need compelling; citable content - Creating blog posts; press releases - Need content that references real trends.

How do I install Content Research in Claude Code?

Run `npx skills add nicepkg/ai-workflow --skill content-research -a claude-code`. Or copy the skill folder (workflows/video-creator-workflow/.claude/skills/content-research in nicepkg/ai-workflow) into .claude/skills/content-research in your project. Claude Code loads it when a task matches its description.

How do I install Content Research in Codex?

Run `npx skills add nicepkg/ai-workflow --skill content-research -a codex`. Or copy the skill folder (workflows/video-creator-workflow/.claude/skills/content-research in nicepkg/ai-workflow) into .agents/skills/content-research in your project. Codex loads it when a task matches its description.

Can I use Content Research 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 nicepkg/ai-workflow --skill content-research -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-research, .gemini/skills/content-research, .github/skills/content-research and .opencode/skills/content-research in your project.

What does Content Research need to run?

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

Does Content Research 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 Research 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 Research use?

Content Research 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 Research use?

About 3.7k tokens (SKILL.md is roughly 15k characters). Agents keep only the skill's name and description in context until a task matches; then they load SKILL.md in full. Its references folder adds about 6.4k tokens, read only when the agent opens those files.

What are the alternatives to Content Research?

Skills that share tags, products or a category with Content Research: Marketing Os (Yuzzyuk/marketing-os, 535 stars), SEO Audit (shadcn-labs/agentcn, 484 stars), SEO Profound (AgriciDaniel/claude-seo, 18k stars) and AI Search Visibility Audit (davepoon/buildwithclaude, 3.6k stars). The comparison table on this page puts their stars, adoption, token cost, safety result and licence side by side.

Who maintains Content Research?

nicepkg (a GitHub organization) maintains it in nicepkg/ai-workflow, which has 285 GitHub stars. The repository holds 61 skills in this directory. The repository was last updated on January 20, 2026.

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