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.
git clone --depth 1 https://github.com/revaya-ai/revaya-aios-workspace-templateWrote 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.
[](https://agentmods.dev/commands/revaya-ai/revaya-aios-workspace-template/competitive-research)<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.
<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>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.
| Model | Per session | Once 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 |
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.
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)
- AIOS / AI OS service providers — people selling AI operating system builds or productized AI consulting
- Claude educators and content creators — people teaching Claude, Claude Code, or Claude-specific workflows
- AI automation consultants — people building n8n, Zapier, or general AI automation for businesses
- 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]
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.
- 11d ago First seen · 79 lines · 0 tokens per session scan A 3556d9c41787
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.
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