AAS Core is a local control plane for coding agents that lets them search a large catalogue of skills, choose a stack, validate it, and create a reproducible plan. It is used to assemble and review agent workflows through its CLI, local MCP server, catalogue, plugins, and Workbench. The catalogue add-ons provide the skills, plugins, bundles, and workflows that AAS Core helps agents select and validate.
Getting it into your agent
This one installs as part of its plugin. Adding the marketplace and installing the plugin brings it with everything else the plugin ships.
/plugin marketplace add sickn33/agentic-awesome-skills/plugin install agentic-awesome-skillsWrote 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/skills/sickn33/agentic-awesome-skills/apify-competitor-intelligence)<a href="https://agentmods.dev/skills/sickn33/agentic-awesome-skills/apify-competitor-intelligence"><img src="https://agentmods.dev/badge/skills/sickn33/agentic-awesome-skills/apify-competitor-intelligence/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/skills/sickn33/agentic-awesome-skills/apify-competitor-intelligence"><img src="https://agentmods.dev/badge/skills/sickn33/agentic-awesome-skills/apify-competitor-intelligence.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 | $0.00039 | $0.01470 |
| Opus 5 | $0.00019 | $0.00735 |
| Sonnet 5 | $0.00008 | $0.00294 |
| Haiku 4.5 | $0.00004 | $0.00147 |
Grade A, and why
apify-competitor-intelligence 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.
Copies of this mod
8 near-identical copies found in the catalogue:
- apify-competitor-intelligence — 100% identical, 1 lines differ
- apify-competitor-intelligence — 100% identical, 1 lines differ
- apify-competitor-intelligence — 95% identical, 3 lines differ
- apify-competitor-intelligence — 95% identical, 3 lines differ
- apify-competitor-intelligence — 95% identical, 3 lines differ
- apify-competitor-intelligence — 95% identical, 3 lines differ
- apify-competitor-intelligence — 95% identical, 3 lines differ
- apify-competitor-intelligence — 91% identical, 13 lines differ
How it starts
The opening of the file, as written. The whole thing — 144 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Competitor Intelligence
Analyze competitors using Apify Actors to extract data from multiple platforms.
When to Use
- You need competitor benchmarks for content, reviews, pricing, ads, audience, or channel performance.
- The task involves selecting Apify Actors to compare competitors across maps, booking, social, or video platforms.
- You need structured competitor data plus synthesized takeaways for strategy or positioning.
Prerequisites
(No need to check it upfront)
.envfile withAPIFY_TOKEN- Node.js 20.6+ (for native
--env-filesupport) mcpcCLI tool:npm install -g @apify/mcpc
Workflow
Copy this checklist and track progress:
Task Progress:
- [ ] Step 1: Identify competitor analysis type (select Actor)
- [ ] Step 2: Fetch Actor schema via mcpc
- [ ] Step 3: Ask user preferences (format, filename)
- [ ] Step 4: Run the analysis script
- [ ] Step 5: Summarize findings
Step 1: Identify Competitor Analysis Type
Select the appropriate Actor based on analysis needs:
| User Need | Actor ID | Best For |
|---|---|---|
| Competitor business data | compass/crawler-google-places |
Location analysis |
| Competitor contact discovery | poidata/google-maps-email-extractor |
Email extraction |
| Feature benchmarking | compass/google-maps-extractor |
Detailed business data |
| Competitor review analysis | compass/Google-Maps-Reviews-Scraper |
Review comparison |
| Hotel competitor data | voyager/booking-scraper |
Hotel benchmarking |
| Hotel review comparison | voyager/booking-reviews-scraper |
Review analysis |
| Competitor ad strategies | apify/facebook-ads-scraper |
Ad creative analysis |
| Competitor page metrics | apify/facebook-pages-scraper |
Page performance |
| Competitor content analysis | apify/facebook-posts-scraper |
Post strategies |
| Competitor reels performance | apify/facebook-reels-scraper |
Reels analysis |
| Competitor audience analysis | apify/facebook-comments-scraper |
Comment sentiment |
| Competitor event monitoring | apify/facebook-events-scraper |
Event tracking |
| Competitor audience overlap | apify/facebook-followers-following-scraper |
Follower analysis |
| Competitor review benchmarking | apify/facebook-reviews-scraper |
Review comparison |
| Competitor ad monitoring | apify/facebook-search-scraper |
Ad discovery |
| Competitor profile metrics | apify/instagram-profile-scraper |
Profile analysis |
| Competitor content monitoring | apify/instagram-post-scraper |
Post tracking |
| Competitor engagement analysis | apify/instagram-comment-scraper |
Comment analysis |
| Competitor reel performance | apify/instagram-reel-scraper |
Reel metrics |
| Competitor growth tracking | apify/instagram-followers-count-scraper |
Follower tracking |
| Comprehensive competitor data | apify/instagram-scraper |
Full analysis |
| API-based competitor analysis | apify/instagram-api-scraper |
API access |
| Competitor video analysis | streamers/youtube-scraper |
Video metrics |
| Competitor sentiment analysis | streamers/youtube-comments-scraper |
Comment sentiment |
| Competitor channel metrics | streamers/youtube-channel-scraper |
Channel analysis |
| TikTok competitor analysis | clockworks/tiktok-scraper |
TikTok data |
| Competitor video strategies | clockworks/tiktok-video-scraper |
Video analysis |
| Competitor TikTok profiles | clockworks/tiktok-profile-scraper |
Profile data |
What ships with it
1 file beside SKILL.md in the same directory: the scripts, references and assets a skill reads on demand. Not counted in the per-session cost; read them before you install if any of them is executable.
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.
- 2d ago Changed · +1 lines 2e7b81d3740c
- 4d ago First seen · 143 lines · 39 tokens per session scan A 4c4e4dc38e25
apify-competitor-intelligence is a skill published in the GitHub repository sickn33/agentic-awesome-skills (46,184 stars, last pushed yesterday), licensed MIT. It adds 39 tokens to every session and 1,470 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 2026-09-05.
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