community-discovery

community-discovery is a skill for Claude Code, Codex from Maudeunfledged834/startup-founder-skills. It costs 55 tokens per session (1,539 once invoked), scanned A, a copy of community-discovery, MIT.

A process for finding online groups where a target audience spends time, including Slack groups, Discord servers, Reddit communities, forums, and other communities. It considers the group's relevance, activity, rules, and promotion fit.

In plain words
What is it for?
Use it to discover communities for feedback, organic promotion, launch support, partnerships, beta recruitment, or community-led growth.
Why use it?
It reduces the time spent searching for places to reach potential customers, partners, beta testers, or design partners. It also helps avoid promoting in communities that are a poor fit.

Skill for Claude CodeCodex

Written for no agent in particular: nothing here depends on one.

Good fit Use it to discover communities for feedback, organic promotion, launch support, partnerships, beta recruitment, or community-led growth.

Compare 6 skills from other repositories ↓
Install with agentmods
npx agentmods add skills/maudeunfledged834/startup-founder-skills/community-discovery
Install

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.

Any agent
npx skills add Maudeunfledged834/startup-founder-skills --skill community-discovery
Clone the repo
git clone --depth 1 https://github.com/Maudeunfledged834/startup-founder-skills

Made for: Claude Code, Codex.

Wrote 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.

agentmods badge for community-discovery

README.md
[![agentmods](https://agentmods.dev/badge/skills/maudeunfledged834/startup-founder-skills/community-discovery/github.svg)](https://agentmods.dev/skills/maudeunfledged834/startup-founder-skills/community-discovery)
Your own site
<a href="https://agentmods.dev/skills/maudeunfledged834/startup-founder-skills/community-discovery"><img src="https://agentmods.dev/badge/skills/maudeunfledged834/startup-founder-skills/community-discovery/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.

agentmods 80×15 button for community-discovery

Your own site · 80×15
<a href="https://agentmods.dev/skills/maudeunfledged834/startup-founder-skills/community-discovery"><img src="https://agentmods.dev/badge/skills/maudeunfledged834/startup-founder-skills/community-discovery.svg" alt="Reviewed on agentmods" width="80" height="20"></a>
Per session 55 Skills are progressive disclosure: only the name and description are preloaded; the body loads when the skill is used.
When invoked 1,539 The whole file, excluding the scripts and references it only reads on demand.
Security scan A 0 findings. A grade says what 26 rules found in the file — not that it is safe.
Origin 100% copy Near-identical to another mod in the catalogue.
Token cost

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.

ModelPer sessionOnce invoked
Fable 5.1 $0.00055 $0.01539
Opus 5 $0.00028 $0.00770
Sonnet 5 $0.00011 $0.00308
Haiku 4.5 $0.00006 $0.00154

Measured 12d ago against content hash afbde436fdc7, method: parsed. Prices are Anthropic first-party input rates as of 2026-09-12, from the pricing page.

Security

Grade A, and why

community-discovery 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 12d 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.

Origin

This is a copy

100% identical to community-discovery — 0 lines differ, which has more behind it and is treated as the original. This page carries a canonical link to it rather than competing with it.

skills/community-discovery/SKILL.md · 122 lines

How it starts

The opening of the file, as written. The whole thing — 122 lines — stays where its author put it; the contents beside it link to each section on GitHub.

Community Discovery

When to Use

  • Founder wants to find online communities where their target customers are active
  • Founder wants to identify channels for organic promotion and community-led growth
  • Founder wants to build relationships in relevant communities before launching
  • Founder wants to find beta testers, early adopters, or design partners
  • Founder wants distribution beyond paid ads and cold outreach

Context Required

  • Target customer profile (role, industry, interests, seniority)
  • Product category and the problem it solves
  • What the founder wants from communities (feedback, users, partnerships, awareness)
  • Founder's bandwidth for community engagement (lurk and post vs. become a regular)

Workflow

  1. Map the community landscape — identify where your target audience spends time online:
    • Reddit: find subreddits by searching for the problem you solve, competitor names, and industry terms. Check subscriber count, post frequency, and moderation rules.
    • Slack: search Slofile, Slack directories, and Google "[industry] slack community" to find relevant workspaces.
    • Discord: search Disboard, Discord.me, and Google "[topic] discord server" for relevant servers.
    • Forums & others: Indie Hackers, Hacker News, Stack Overflow, niche forums, Facebook Groups, LinkedIn Groups.
  2. Qualify each community — not all communities are equal. Score each on:
    • Relevance: does your target customer actually hang out here?
    • Activity: are there regular posts and discussions (not a ghost town)?
    • Size: big enough to matter, small enough to stand out (sweet spot: 1K-50K members)
    • Promotion tolerance: does the community allow product mentions, or is it strictly no self-promotion?
    • Quality of discussion: are conversations substantive or just spam and memes?
  3. Categorize by engagement type — sort communities into:
    • Promote: explicitly allows product sharing, launch announcements, or "Show X" posts
    • Contribute-first: allows organic mentions if you're a genuine, helpful member first
    • Listen-only: valuable for research and voice-of-customer, but no promotion allowed
  4. Build the engagement plan — for each community:
    • Join and observe for 1-2 weeks before posting
    • Identify the norms (how do regulars communicate? what gets upvoted/praised?)
    • Plan your first 5 contributions (helpful answers, not product pitches)
    • Plan when and how to introduce your product (if appropriate)
  5. Create the community map — output a prioritized list with engagement strategy for each.

Read the full file on GitHub · 122 lines

Changes

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.

  1. 12d ago First seen · 122 lines · 55 tokens per session scan A afbde436fdc7

Subscribe to this mod's changes

community-discovery is a skill published in the GitHub repository Maudeunfledged834/startup-founder-skills (6 stars, last pushed today), licensed MIT. It adds 55 tokens to every session and 1,539 once invoked, about $0.0003 per session on Opus 5. A static security scan graded it A with 0 findings. It is 100% identical to community-discovery, differing in 0 lines, and is treated as a copy.

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