Community Discovery

Community Discovery

Usage

Use when finding communities to engage with organically, identifying where a target market spends time online, or planning community-led GTM strategy.

Process

Step 1: Gather Inputs

Ask the user for:

1. Audience description — who they're targeting (job title, industry, stage). Example: "B2B SaaS founders at seed stage", "freelance UX designers", "e-commerce store owners"
2. Product category (optional) — what they sell, to help filter relevance and identify tool-adjacent communities
3. Minimum member count (optional) — exclude communities below a threshold (default: no minimum — small communities are included with a flag)

Extract from the audience description:

• Identity/role: Who is the person (founder, marketer, developer, etc.)
• Industry/vertical: What sector or market they're in
• Business type/stage: Solo, SMB, startup, agency, enterprise — or consumer
• Problem domain: What they're trying to solve (inferred from product category if provided)

Step 2: Generate Search Queries

Generate 8 search queries to surface communities across platform types. Mix these angles:

Platform-specific queries:

• "slack community [identity/role]"
• "discord server [industry/niche]"
• "facebook group [job title or problem]"
• "linkedin group [industry]"
• "[identity] community forum"

Directory-based queries:

• "hive.one [audience topic]"
• "slofile [slack community] [niche]"
• "disboard [discord] [niche]"

Discovery-angle queries:

• "best communities for [identity]"
• "where do [audience] hang out online"
• "[industry] online community"

Step 3: Search Platform Directories

Search these community directories first — they surface communities across many platforms in one pass:

| Directory | What It Indexes | How to Search | |-----------|----------------|---------------| | hive.one | Audience-indexed communities by topic | Search by topic or person | | slofile.com | Public Slack workspaces | Search by keyword | | disboard.org | Discord servers by tag | Search by tag/keyword | | discadia.com | Discord servers | Search by category/keyword | | commsor.com | Community index | Browse by category |

For each directory, search with the audience's identity, industry, and problem domain terms. Collect all relevant results.

Step 4: Search Each Platform Directly

Reddit

Search for subreddits using:

• "site:reddit.com [identity/role]"
• "reddit [industry] community"
• "r/findareddit [audience description]"

Collect subreddit name, member count, and description.

Slack & Discord

Use slofile.com and disboard.org searches from Step 3. Also search:

• "[industry] slack community"
• "[niche] discord server"

Facebook Groups

Search: "facebook group [identity/role]" and "facebook group [industry]". Note: member counts require browsing Facebook directly — estimate when not verifiable.

LinkedIn Groups

Search: "linkedin group [industry]" and "linkedin group [job title]". Note: LinkedIn groups vary widely in activity — flag low-activity groups.

Other Platforms

Search for:

• Mighty Networks / Circle: "[industry] community mighty networks" or "[niche] circle community"
• Geneva: "[identity] geneva community"
• Luma: "[niche] luma community events"
• Discourse forums: "[industry] forum site:community. OR site:forum."
• Industry-specific forums: "[industry] forum" + check known industry directories

Step 5: Normalize All Results

Compile all discovered communities into a single list. For each entry, record:

| Field | Description | |-------|-------------| | Name | Community name | | URL | Direct link to the community | | Platform Type | Reddit / Slack / Discord / Facebook Group / LinkedIn Group / Forum / Other | | Member Count | Total member/subscriber count (or "unverified" if unknown) | | Description | One-line summary of what the community is about | | Source | Where it was discovered (directory name or search) |

Deduplication: If the same community appears from multiple sources, keep one entry and note it appeared in multiple places (stronger signal of relevance).

Member count = 0 or unknown: Include but flag as "unverified." Small/unknown-size communities are still worth noting if relevance is high.

Step 6: Score Each Community

Score every community on two dimensions:

Dimension 1: Relevance (1–5)

| Score | Signal | |-------|--------| | 5 | Community is built specifically for this exact audience (identity + industry match) | | 4 | Strong match — same role or same industry, minor gaps | | 3 | Adjacent — related audience, overlapping interests | | 2 | Loose match — your audience is a minority here | | 1 | Tangential — topic overlap but very different audience |

Dimension 2: Noise (1–5)

| Score | Signal | |-------|--------| | 1 | Very low noise — tightly moderated, mostly signal | | 2 | Low noise — mostly on-topic with occasional spam | | 3 | Moderate noise — mixed quality, some spam | | 4 | High noise — significant spam or off-topic content | | 5 | Very high noise — dominated by promotions or irrelevant content |

Signal-to-Noise Rating

| Rating | Criteria | |--------|----------| | High | Relevance ≥ 4 AND Noise ≤ 2 | | Medium | Relevance 3–4 OR Noise = 3 (not both extremes) | | Low | Relevance ≤ 2 OR Noise ≥ 4 |

Step 7: Sort and Finalize

Sort the full list:

1. Primary: Signal-to-Noise rating (High → Medium → Low)
2. Secondary: Member count (largest first within each tier)

Flag communities where member count is unverified — place them after verified-count communities within the same S/N tier.

Output Format

# Community Discovery: [Audience Description]

**Date:** [current date]
**Audience:** [description]
**Communities found:** [count] across [X] platforms
**Signal-to-Noise breakdown:** High: [X] | Medium: [X] | Low: [X]

---

## High Signal Communities

| # | Name | URL | Platform | Members | S/N | Notes |
|---|------|-----|----------|---------|-----|-------|
| 1 | [name] | [url] | [type] | [count] | High | [brief note on why it's a fit] |

---

## Medium Signal Communities

| # | Name | URL | Platform | Members | S/N | Notes |
|---|------|-----|----------|---------|-----|-------|
| 1 | [name] | [url] | [type] | [count] | Medium | [brief note] |

---

## Low Signal Communities

| # | Name | URL | Platform | Members | S/N | Notes |
|---|------|-----|----------|---------|-----|-------|
| 1 | [name] | [url] | [type] | [count] | Low | [brief note] |

---

## Platform Coverage Summary

| Platform | Count | High S/N | Notes |
|----------|-------|----------|-------|
| Reddit | X | X | [observation] |
| Slack | X | X | |
| Discord | X | X | |
| Facebook Groups | X | X | |
| LinkedIn Groups | X | X | |
| Forums/Other | X | X | |

---

## Observations

[2-3 bullet points on where this audience is most concentrated, any surprising findings, or gaps]

## Recommended Next Steps

1. [e.g., "Join the top 3 High S/N communities and lurk for 1 week before engaging"]
2. [e.g., "No LinkedIn groups had high activity — deprioritize LinkedIn as a community channel"]

Rules

• Aim for 100+ communities total. If the audience is niche, 50 is acceptable — flag it.
• Platform coverage matters more than raw count. A list with 100 Reddit results and 0 Slack results may miss important communities.
• Community size is a secondary factor. A 200-member Slack group of exactly your target buyer is often more valuable than a 50k-member Discord with 5% audience match.
• Never invent communities that weren't found via search — only include verified results.
• Never guess member counts — mark unknown counts as "unverified."
• Don't skip platforms because they seem unlikely — search all 5 categories and let the results speak.
• If fewer than 20 communities are found, the search was too narrow — broaden by using more generic identity/industry terms.
• If the audience description is very broad (e.g., "small businesses", "marketers"), ask the user to narrow it before proceeding.
• Flag if all high-signal communities are very small (under 500 members) — the audience may not have a strong online community presence.

Source & license

This open-source skill is cataloged on AgentStack and links to its original source — we do not rehost the code.

• Author: superamped
• Source: superamped/ai-marketing-skills
• License: MIT
• Homepage: https://superamped.com

Install and usage instructions live in the source repository linked above.