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.
npx agentmods add commands/ad-superpowers/ad-superpowers-plugin/competitive-landscape-analyzergit clone --depth 1 https://github.com/Ad-Superpowers/ad-superpowers-pluginWrote 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/ad-superpowers/ad-superpowers-plugin/competitive-landscape-analyzer)<a href="https://agentmods.dev/commands/ad-superpowers/ad-superpowers-plugin/competitive-landscape-analyzer"><img src="https://agentmods.dev/badge/commands/ad-superpowers/ad-superpowers-plugin/competitive-landscape-analyzer.svg" alt="Measured on agentmods" 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 | $0.00046 | $0.01530 |
| Opus 5 | $0.00023 | $0.00765 |
| Sonnet 5 | $0.00009 | $0.00306 |
| Haiku 4.5 | $0.00005 | $0.00153 |
Grade A, and why
competitive-landscape-analyzer 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 6d 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 — 140 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Platforms: meta, google_ads, linkedin, tiktok Tier: pro
This command requires the Ad Superpowers MCP connector to access your ad account data. Connect at https://app.adsuperpowers.ai if you haven't already.
Competitive Intelligence & Ad Strategy Analysis
Conduct competitive analysis for [specify company_name] in [specify industry]. Known competitors: To be discovered. Focus: general.
OUTPUT FORMAT (CRITICAL - follow this EXACT structure)
EXECUTIVE SUMMARY
- Competitive landscape overview (2-3 sentences)
- [specify company_name]'s position: [leader/challenger/niche/new entrant]
- Top 3 threats with threat level (High/Medium/Low)
- Top 3 opportunities (gaps in competitor coverage)
COMPETITOR PROFILES (top 3-5)
For each competitor:
| Attribute | Details |
|---|---|
| Website | [URL] |
| Size/Revenue | [estimate] |
| Target Audience | [segments] |
| Value Proposition | [their main pitch] |
| Strengths | [2-3 bullets] |
| Weaknesses | [2-3 bullets] |
AD PRESENCE OVERVIEW
| Competitor | Meta Ads | Google Ads | TikTok | Est. Monthly Spend |
|---|
COMPETITIVE THREAT MATRIX
| Competitor | Market Share /10 | Ad Aggressiveness /10 | Brand Strength /10 | Innovation /10 | Total /40 | Trend |
|---|---|---|---|---|---|---|
| 30-40: Critical | 20-29: Significant | 10-19: Moderate | <10: Low |
POSITIONING MAP
Axes: [Dimension 1] (Low-High) x [Dimension 2] (Low-High)
| Company | X Position | Y Position | Quadrant |
|---|---|---|---|
| White space opportunities: [underserved positions] |
STRATEGIC RECOMMENDATIONS
Defensive: [protect against top threats] Offensive: [exploit competitor gaps] Messaging differentiation:
| Angle | Why It Works | Competitors Not Using |
|---|
Positioning statement: "For [audience] who [need], [specify company_name] is the [category] that [differentiator]. Unlike [competitors], we [unique benefit]."
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.
- 6d ago First seen · 140 lines · 46 tokens per session scan A 4b58e21e6a22
competitive-landscape-analyzer is a command published in the GitHub repository Ad-Superpowers/ad-superpowers-plugin (5 stars, last pushed 7d ago), licensed MIT. It adds 46 tokens to every session and 1,530 once invoked, about $0.0002 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 2026-08-31.
Other commands, from other repositories
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meta-audit
Full Meta Ads account audit, tailored to ecommerce or lead-gen automatically.
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First-run setup for the ga-mcp-full MCP server — install the CLI if needed, then complete the browser login.
auth-logout
Clear cached Google Analytics OAuth credentials for the ga-mcp-full MCP server.
ad-brief
Generate a production-ready creative brief from a scripted Pipeline ad. Includes shot list, filming card, B-roll suggestions, text overlay specs, and equipment notes. Ready to print and film.
ad-polish
Strip AI patterns from ad copy and scripts. Makes text sound like a real person wrote it, not a language model. Run on any Pipeline record before launch.