competitive-research

competitive-research is a command for Claude Code from revaya-ai/revaya-aios-workspace-template. It costs 0 tokens per session (645 once invoked), scanned A, original, MIT.

A competitive research command that studies what AI consultants, educators, automation specialists, and coaches publish and sell. Competitive research means examining similar providers to find common approaches and gaps.

In plain words
What is it for?
Use it with a named competitor or its default categories to research content angles, lead magnets, positioning, and opportunities for your Business AI OS.
Why use it?
It gives you a view of competing content, offers, positioning, and missed topics before you decide what to publish.

Command for Claude Code

Written for Claude Code: $ARGUMENTS substitution. Also seen: mentions subagents; mentions Claude Code.

Good fit Use it with a named competitor or its default categories to research content angles, lead magnets, positioning, and opportunities for your Business AI OS.

Compare 6 commands from other repositories ↓
Install with agentmods
npx agentmods add commands/revaya-ai/revaya-aios-workspace-template/competitive-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.

Clone the repo
git clone --depth 1 https://github.com/revaya-ai/revaya-aios-workspace-template

Made for: Claude Code.

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 competitive-research

README.md
[![agentmods](https://agentmods.dev/badge/commands/revaya-ai/revaya-aios-workspace-template/competitive-research/github.svg)](https://agentmods.dev/commands/revaya-ai/revaya-aios-workspace-template/competitive-research)
Your own site
<a href="https://agentmods.dev/commands/revaya-ai/revaya-aios-workspace-template/competitive-research"><img src="https://agentmods.dev/badge/commands/revaya-ai/revaya-aios-workspace-template/competitive-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 competitive-research

Your own site · 80×15
<a href="https://agentmods.dev/commands/revaya-ai/revaya-aios-workspace-template/competitive-research"><img src="https://agentmods.dev/badge/commands/revaya-ai/revaya-aios-workspace-template/competitive-research.svg" alt="Reviewed on agentmods" width="80" height="20"></a>
Per session 0 Only the description is in the session, so the agent can decide to use it. The body loads when it is invoked.
When invoked 645 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 $0.00000 $0.00645
Opus 5 $0.00000 $0.00322
Sonnet 5 $0.00000 $0.00129
Haiku 4.5 $0.00000 $0.00064

Measured 11d ago against content hash 3556d9c41787, method: parsed. Prices are Anthropic first-party input rates as of 2026-09-11, from the pricing page.

Security

Grade A, and why

competitive-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 11d 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.

.claude/commands/competitive-research.md · 79 lines

How it starts

The opening of the file, as written. The whole thing — 79 lines — stays where its author put it; the contents beside it link to each section on GitHub.

Competitive Research

Competitor content analysis agent. Analyzes what AIOS consultants, Claude educators, and AI coaches are doing — content angles, lead magnets, positioning, and gaps you can fill.

Variables

target: $ARGUMENTS (optional — specific competitor name, or leave blank to run on default list)


Instructions

You are analyzing the competitive content landscape for your Business AI OS positioning. The goal is to understand what others in this space are doing, identify what's working, and find the gaps you can own.

Default competitor categories (use when no specific target provided)

  1. AIOS / AI OS service providers — people selling AI operating system builds or productized AI consulting
  2. Claude educators and content creators — people teaching Claude, Claude Code, or Claude-specific workflows
  3. AI automation consultants — people building n8n, Zapier, or general AI automation for businesses
  4. Solopreneur AI coaches — people teaching solo operators how to use AI in their business

Step 1: Dispatch research subagent

Use the Agent tool (general-purpose) to search the web. Instruct the agent to:

  • Search for active creators/consultants in each category above (or the named target)
  • Find: their LinkedIn presence, YouTube content, website positioning, lead magnets, and any visible pricing
  • Look for: what topics they post about, what angles they take, what their lead magnets offer
  • Note: follower counts or engagement signals where visible
  • Search for: gaps — topics nobody is covering, angles nobody is taking, audiences being underserved

Step 2: Compile the brief

# Competitive Research Brief
**Date:** YYYY-MM-DD
**Target:** [specific competitor or "default landscape"]

## Competitor Profiles

### [Name / Handle]
- Platform: [LinkedIn / YouTube / etc.]
- Positioning: [how they describe themselves]
- Content themes: [what they post about]
- Lead magnet: [what free resource they offer, if any]
- Pricing signal: [any visible pricing]
- Audience size: [follower count if visible]
- What they do well: [specific strength]
- What they miss: [gap or weakness]

[repeat for each competitor]

## Content Themes They Own
[Topics that are well-covered — you should differentiate, not duplicate]

## Lead Magnet Formats in Use
[What free resources are common in this space]

## Positioning Gaps
[Angles, audiences, or problems nobody is addressing well]

## your Opportunities
[Specific differentiation plays — where your background, story, or method gives her an edge nobody else has]

## Hooks/Angles you Could Counter or Complement
[Specific post angles that respond to or build on competitor content]

Read the full file on GitHub · 79 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. 11d ago First seen · 79 lines · 0 tokens per session scan A 3556d9c41787

Subscribe to this mod's changes

competitive-research is a command published in the GitHub repository revaya-ai/revaya-aios-workspace-template (2 stars, last pushed 6mo ago), licensed MIT. It costs nothing until one of its globs matches a file; then it loads 645 tokens. 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.