content-research

content-research is a skill for Claude Code, Codex from Livus-AI/Skills-MCP. It costs 50 tokens per session (539 once invoked), scanned A, original, MIT.

A research workflow that gathers recent information about a topic and turns it into a structured brief for creating content.

In plain words
What is it for?
Use it to research a subject, identify key companies or people, and prepare material for posts or other content.
Why use it?
It reduces the work of finding relevant developments, statistics, sources, and the main story before writing.

Skill for Claude CodeCodex

Written for no agent in particular: nothing here depends on one.

Good fit Use it to research a subject, identify key companies or people, and prepare material for posts or other content.

Compare 6 skills from other repositories ↓
Install with agentmods
npx agentmods add skills/livus-ai/skills-mcp/content-research
Install

Getting it into your agent

One page per mod, every tool's command on it. A separate URL per tool would split the same page into five that compete with each other.

Any agent
npx skills add Livus-AI/Skills-MCP --skill content-research
Clone the repo
git clone --depth 1 https://github.com/Livus-AI/Skills-MCP

Made for: Claude Code, Codex.

Wrote this? Show the measurements

A badge with what this costs and how it scanned, read live from this page, so it follows the numbers instead of freezing them. Markdown for a README, HTML for a documentation site or a project page.

agentmods badge for content-research

README.md
[![agentmods](https://agentmods.dev/badge/skills/livus-ai/skills-mcp/content-research/github.svg)](https://agentmods.dev/skills/livus-ai/skills-mcp/content-research)
Your own site
<a href="https://agentmods.dev/skills/livus-ai/skills-mcp/content-research"><img src="https://agentmods.dev/badge/skills/livus-ai/skills-mcp/content-research/github.svg" alt="Measured on agentmods" height="20"></a>

Or the 80×15 button, for a site that already has a row of RSS and ATOM ones. Only the verdict fits; the numbers stay here.

agentmods 80×15 button for content-research

Your own site · 80×15
<a href="https://agentmods.dev/skills/livus-ai/skills-mcp/content-research"><img src="https://agentmods.dev/badge/skills/livus-ai/skills-mcp/content-research.svg" alt="Reviewed on agentmods" width="80" height="20"></a>
Per session 50 Skills are progressive disclosure: only the name and description are preloaded; the body loads when the skill is used.
When invoked 539 The whole file, excluding the scripts and references it only reads on demand.
Security scan A 0 findings. A grade says what 26 rules found in the file — not that it is safe.
Origin original No closer match found in the catalogue.
Token cost

What it costs to keep this loaded

Counted locally with the o200k_base tokenizer, which is exact for GPT models; Claude uses its own tokenizer and its counts differ. Treat this as one consistent yardstick across the catalogue rather than a bill. Prices are per million input tokens.

ModelPer sessionOnce invoked
Fable 5.1 $0.00050 $0.00539
Opus 5.5 $0.00020 $0.00216
Sonnet 5.5 $0.00010 $0.00108
Haiku 4.5 $0.00005 $0.00054

Measured 2mo ago against content hash 86ed8ebb4837, method: parsed. Prices are Anthropic first-party input rates as of 2026-10-07, from the pricing page.

Security

Grade A, and why

content-research scanned grade A with 0 findings against 26 rules in 11 categories — prompt injection, anti-refusal, data exfiltration, privilege escalation, supply chain, agent snooping, system-prompt leakage, SSRF and excessive agency — measured 2mo ago.

A static scan of the body, not an audit. Every finding is printed with the line that produced it so you can judge whether it matters here. A mod is markdown that instructs an agent; that is exactly why what it instructs is worth reading.

Nothing flagged

None of the 26 patterns this scan looks for appear in this file: no shell pipes, no recursive deletes, no credential paths, no hidden text, no instruction-override or anti-refusal phrasing, no agent-config snooping. That is not a guarantee, it is the absence of the things that are checkable.

skills/content-research/SKILL.md · 75 lines

How it starts

The opening of the file, as written. The whole thing — 75 lines — stays where its author put it; the contents beside it link to each section on GitHub.

Content Research Skill

Gather and synthesize raw information on a single topic into a structured brief that serves as the foundation for multi-platform content creation.

Workflow

  1. Receive topic from user or identify trending topic in niche
  2. Research using web search, news, and authoritative sources
  3. Synthesize findings into the Research Brief format
  4. Output structured brief for downstream content generation

Research Goals

When researching a topic, focus on:

  1. 3-5 significant recent developments - What's new and noteworthy?
  2. 1-2 surprising statistics - Data that challenges assumptions or creates shock value
  3. Core narrative - What's the bigger story or trend?
  4. Key players - Companies, tools, or people driving the change
  5. Actionable takeaway - One clear action the audience can take

Output Format

Always structure the research brief as follows:

## Research Brief: [Topic]

**Core Narrative:** [1-2 sentence summary of the main story or trend]

**Key Developments:**
1. [Development 1]: [Brief description with source]
2. [Development 2]: [Brief description with source]
3. [Development 3]: [Brief description with source]

**Surprising Data:**
- [Statistic]: [Context and source link]

**Key Players:**
- [Company/Tool/Person 1]
- [Company/Tool/Person 2]

**Actionable Takeaway:** [Single, clear action someone can take]

**Sources:**
- [Source 1 URL]
- [Source 2 URL]

Quality Checklist

Before completing the research brief, verify:

  • All claims have credible sources
  • Statistics are recent (within last 6 months preferred)
  • Core narrative is clear and compelling
  • Takeaway is specific and actionable
  • Brief is concise (under 500 words)

Next Steps

After completing the research brief, proceed to:

  • twitter-thread-generator - Convert brief into Twitter thread
  • linkedin-post-adapter - Adapt for LinkedIn audience
  • newsletter-expander - Expand into full newsletter issue

Read the full file on GitHub · 75 lines

Changes

What this file has done since we first saw it

Hashed on every crawl. A supply-chain change to an agent config is a question of when, not whether, so the history is kept rather than the latest state alone.

  1. 2mo ago First seen · 75 lines · 50 tokens per session scan A 86ed8ebb4837

Subscribe to this mod's changes

content-research is a skill published in the GitHub repository Livus-AI/Skills-MCP (2 stars, last pushed 5mo ago), licensed MIT. It adds 50 tokens to every session and 539 once invoked, about $0.0002 per session on Opus 5.5. A static security scan graded it A with 0 findings. No closer match exists in the catalogue, so it is treated as the original; first seen 2026-08-31.

Related

content-research compared with skills from other repositories

content-research next to 6 skills from other repositories
ModTypeStarsLast pushLicenceScanTokensWorks with
content-researchLivus-AI/Skills-MCPSkill25mo agoMITA50Claude Code, Codex
imagegenopenai/codexSkill134ktodayApache-2.0A113Codex
local-ai-agentsmicrosoft/ai-agents-for-beginnersSkill79ktodayMITA200Claude Code, Codex
playwright-climicrosoft/playwrightSkill99ktodayApache-2.0A19Claude Code
systematic-debuggingobra/superpowersSkill314k3d agoMITA21Claude Code
next-cache-components-adoptionvercel/next.jsSkill143ktodayMITA95Claude Code
chat-pet-sprite-creationmicrosoft/vscodeSkill195ktodayMITA53Claude Code, Codex