AGENT SKILLBY SUPERAMPED
Competitor discovery
AT A GLANCE
Competitor discovery is a go-to-market agent skill from superamped. Use when you don't know who your competitors are, when entering a new market, or when refreshing the competitor list after a pivot or market shift. The superamped/ai-marketing-skills repository on GitHub has 49 stars and the MIT license. To add it, run npx skills add superamped/ai-marketing-skills --skill competitor-discovery
- SOURCE REPOSITORY
- superamped/ai-marketing-skills (opens GitHub in a new tab)
- REPO STARS
- SOURCE REPOSITORY
- LICENSE
- MIT
- CATEGORIES
- SKILL.MD SIZE
- 4.2 KB112 LINES
QUICK ANSWER
- WHAT IT IS01
- Use when you don't know who your competitors are, when entering a new market, or when refreshing the competitor list after a pivot or market shift. The value is a focused slice of competitive research judgment, useful when several similar skills cover the same ground.
- INPUTS02
- Context for competitive research: your goals, audience, constraints, and any source material the skill asks for.
- OUTPUT03
- A ready-to-use result for competitive research: the analysis, copy, or recommendations the agent produces.
INSTALL
One command adds this skill from its source repository.
npx skills add superamped/ai-marketing-skills --skill competitor-discoveryREAD THE SKILL.MD BELOW BEFORE YOU RUN IT. SKILLS INSTRUCT YOUR AGENT.
SKILL.MD
The full file, as published in the source repository. Copy it, download it or open it on GitHub.
ON THIS PAGE · 9
Competitor Discovery#
Usage#
Use when you don't know who your competitors are, when entering a new market, or when refreshing the competitor list after a pivot or market shift.
Process#
Step 1: Gather Inputs#
Ask the user for:
- Product description — what it does, what category it's in, key features
- Target audience — who buys or uses the product (role, industry, company size)
- Known competitors (optional) — names or URLs to include without searching
- Number to find (optional) — default: 5-7
Step 2: Build Search Queries#
Construct 4-6 search queries mixing these angles:
- Category: "[category] tools 2025 2026" or "[category] software"
- Alternative: "[product name] alternatives" or "tools like [product name]"
- Problem: "[primary use case] solution" or "[pain point] tool"
- Audience: "best [category] for [target company type]" or "[category] for [target role]"
- Comparison: "best [category] compared" or "top [category] platforms"
- Review sites: "[category] G2" or "[category] Capterra" (to mine company names from lists)
Tailor queries to the product type. A B2B SaaS product needs different queries than a marketplace or agency service.
Step 3: Search and Collect#
Run web searches for each query. For each result:
- Extract company names and domains that appear across multiple results
- Pull companies listed on review/comparison sites (G2, Capterra, etc.) — these are strong signals
- Skip aggregator sites themselves, job boards, news articles about funding, and clearly unrelated results
Compile a candidate list of 8-12 companies. For each, note:
- Name
- URL (homepage)
- How found — which search queries surfaced them
Rank candidates by frequency — companies appearing in 3+ different searches are almost certainly direct competitors.
Step 4: Quick Profile Each Candidate#
For each candidate, fetch their homepage (and pricing page if easily accessible) and extract:
- One-liner — what they say they do, in their own words
- Target audience signals — who the site speaks to
- Overlap — how directly they compete (direct / adjacent / tangential)
Classify each candidate:
- Direct competitor — same problem, same audience, similar solution
- Adjacent competitor — same audience but different approach, or same approach but different audience
- Tangential — some overlap but fundamentally different product
Drop tangential candidates unless the list would be too short (fewer than 3 direct competitors).
Step 5: Present for Confirmation#
Present the ranked list to the user:
I found these competitors for [product name]:
Direct competitors:
1. [Name] — [one-liner] — [url]
2. [Name] — [one-liner] — [url]
3. [Name] — [one-liner] — [url]
Adjacent competitors:
4. [Name] — [one-liner] — [url]
5. [Name] — [one-liner] — [url]
Should I save these? Any to add or remove?Wait for user confirmation. They may know competitors that web search missed, or flag false positives.
Output Format#
# Competitor Discovery: [Product Name]
**Date:** [current date]
**Competitors found:** [X]
## Competitors
| # | Name | URL | Type | One-Liner |
|---|------|-----|------|-----------|
| 1 | [name] | [url] | Direct | [what they do] |
| 2 | [name] | [url] | Direct | [what they do] |
| 3 | [name] | [url] | Adjacent | [what they do] |
## Search Queries Used
- [query 1] — [X results]
- [query 2] — [X results]
## Recommended Next Steps
- Run competitor-site-analysis on top competitors for full profiles (pricing, moats, GTM signals)
- Run competitor-landscape after 2+ analyses for cross-competitor comparison and positioning mapRules#
- Never include a company without visiting their site — one-liners must come from their actual homepage.
- Never guess at pricing — only note what's publicly visible on the homepage or pricing page.
- Never include more than 7 competitors without user approval — keep the list focused.
- If web search returns fewer than 3 relevant competitors, the category may be too niche — try broader search terms.
- If the market appears very crowded (15+ candidates found), suggest focusing on direct competitors only.
- Re-run every 6 months or after significant product/market changes.
FAQ
07 QUESTIONS
01What is the Competitor discovery agent skill?
Use when you don't know who your competitors are, when entering a new market, or when refreshing the competitor list after a pivot or market shift. It is listed under go-to-market in the 100xLab agent skills directory.
02How do I install Competitor discovery in Cursor, Claude Code, or Codex?
Run npx skills add superamped/ai-marketing-skills --skill competitor-discovery in the project where you want it, then ask your agent for the skill by name. The --skill flag installs only Competitor discovery, not every skill in the repository.
03What does the Competitor discovery SKILL.md cover?
The SKILL.md includes sections on Usage, Process, Step 1: Gather Inputs, Step 2: Build Search Queries, Step 3: Search and Collect and Step 4: Quick Profile Each Candidate. Read the full text on this page or in plain markdown at /resources/agent-skills/superamped-ai-marketing-skills--competitor-discovery--1gxzmlt/raw.
04Which agents can use Competitor discovery?
Competitor discovery installs with the cross-agent skills installer (npx skills add), which sets it up for agents such as Claude Code, Cursor and Codex. Each agent loads the SKILL.md when you ask for the skill by name.
05What license is Competitor discovery under?
The superamped/ai-marketing-skills repository declares the MIT license. Read the license file in the repository before you copy or redistribute the skill.
06Is Competitor discovery free to use?
Reading, copying and installing Competitor discovery costs nothing: it is published in a public GitHub repository under the MIT license. Reuse and redistribution follow that license.
07Where is the source of Competitor discovery?
Competitor discovery comes from https://github.com/superamped/ai-marketing-skills, which has 49 GitHub stars. The SKILL.md is at https://github.com/superamped/ai-marketing-skills/blob/HEAD/skills/research/competitor-discovery/SKILL.md. The author is superamped.
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ATTRIBUTION
Competitor discovery was written by its original authors and is published in superamped/ai-marketing-skills (opens GitHub in a new tab) under the MIT license. All rights stay with the original authors.
100xLab did not write, maintain or endorse this skill. This page lists it for discovery. Repo stars belong to the source repository, not to the skill. Review any skill before you install it.