Competitor Channel Analysis Agent

Competitor Channel Analysis Agent is a skill for Claude Code, Codex from SamurAIGPT/open-ai-youtube-agent. It costs 23 tokens per session (847 once invoked), scanned A, original, MIT.

An agent for examining a competitor's public YouTube channel, including its upload timing, videos that perform best, and repeated title or tag patterns.

In plain words
What is it for?
It is for comparing one to three channels, finding videos that outperform a channel's usual results, and reviewing upload frequency and title or tag patterns.
Why use it?
It organizes channel data to help explain what appears to be working and how a competitor's growth compares with other channels.

Skill for Claude CodeCodex

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

Good fit It is for comparing one to three channels, finding videos that outperform a channel's usual results, and reviewing upload frequency and title or tag patterns.

Compare 6 skills from other repositories ↓
Install with agentmods
npx agentmods add skills/samuraigpt/open-ai-youtube-agent/competitor-channel-analysis
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 SamurAIGPT/open-ai-youtube-agent --skill competitor-channel-analysis
Clone the repo
git clone --depth 1 https://github.com/SamurAIGPT/open-ai-youtube-agent

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 Competitor Channel Analysis Agent

README.md
[![agentmods](https://agentmods.dev/badge/skills/samuraigpt/open-ai-youtube-agent/competitor-channel-analysis/github.svg)](https://agentmods.dev/skills/samuraigpt/open-ai-youtube-agent/competitor-channel-analysis)
Your own site
<a href="https://agentmods.dev/skills/samuraigpt/open-ai-youtube-agent/competitor-channel-analysis"><img src="https://agentmods.dev/badge/skills/samuraigpt/open-ai-youtube-agent/competitor-channel-analysis/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 Competitor Channel Analysis Agent

Your own site · 80×15
<a href="https://agentmods.dev/skills/samuraigpt/open-ai-youtube-agent/competitor-channel-analysis"><img src="https://agentmods.dev/badge/skills/samuraigpt/open-ai-youtube-agent/competitor-channel-analysis.svg" alt="Reviewed on agentmods" width="80" height="20"></a>
Per session 23 Skills are progressive disclosure: only the name and description are preloaded; the body loads when the skill is used.
When invoked 847 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 $0.00023 $0.00847
Opus 5 $0.00012 $0.00424
Sonnet 5 $0.00005 $0.00169
Haiku 4.5 $0.00002 $0.00085

Measured 2d ago against content hash 485e87f83221, method: parsed. Prices are Anthropic first-party input rates as of 2026-09-11, from the pricing page.

Security

Grade A, and why

Competitor Channel Analysis Agent 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 2d 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.

agents/competitor-channel-analysis/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.

Competitor Channel Analysis Agent

Mission

Turn a competitor's public channel into a structured read on what's actually working for them — which videos overperform their channel average, how often they upload, and what title/tag patterns show up on their best videos.

Use this agent when

  • A user wants to know why a competitor channel is growing faster.
  • A user wants a list of a competitor's top-performing videos with what made them work.
  • A user wants to benchmark upload frequency against 2-3 competitor channels.

Required inputs

  • The competitor channel(s) to analyze (1-3 recommended for a focused comparison).
  • Optional: a time window (e.g. "last 90 days").

Required connections

  • A Muapi API key (muapi).

Available Muapi capabilities

  • youtube.video_info — per-video stats/metadata (views, likes, comment count, channel details, tags). Backed by Muapi's live SEO API: POST /api/v1/seo-youtube-video-info (live, tested 2026-09-09).
  • youtube.channel_videos — still planned; a dedicated "list a channel's recent videos" endpoint is not wired up on Muapi. Until it ships, seed the video list from seo-youtube-organic searches for the channel's name/niche keywords instead of a true channel-video listing, and say so explicitly.

Workflow

  1. Pull the competitor channel's recent video list via youtube.channel_videos.
  2. Pull per-video stats via youtube.video_info for each.
  3. Compute the channel's average performance (views, engagement) and flag videos significantly above that average as overperformers.
  4. For overperforming videos, extract common patterns: title structure, tag overlap, thumbnail style (if inspectable), topic clustering.
  5. Compute upload cadence (videos per week/month) over the requested window.
  6. If multiple competitors were supplied, compare cadence and overperformer patterns side by side.
  7. Summarize: cadence, top videos with why they likely overperformed, and any repeatable pattern worth adapting (not copying).

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. 2d ago Changed · -1 lines 485e87f83221
  2. 3d ago Changed 0d7cd4643f4a
  3. 12d ago First seen · 76 lines · 23 tokens per session scan A f64374a35520

Subscribe to this mod's changes

Competitor Channel Analysis Agent is a skill published in the GitHub repository SamurAIGPT/open-ai-youtube-agent (2 stars, last pushed 2d ago), licensed MIT. It adds 23 tokens to every session and 847 once invoked, about $0.0001 per session on Opus 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 2026-08-30.

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