How opendirectory Hit 10,000 npm Downloads and 350+ GitHub Stars in One Month From Scratch

TL;DR

• Project: opendirectory, our own open-source agent skill directory built for founders who hate marketing
• Where we started: New repo, domain, zero audience. Everything from scratch.
• What we did: Shipped 56+ skills we were already using for our own GTM work, then ran the same distribution engine we run for clients across Reddit, Instagram, and an outbound layer
• What happened in 30 days:
  • 10,000+ npm downloads of @opendirectory.dev/skills
  • 350+ GitHub stars on the repository
  • 5,028 clones in a single 14-day window from 431 unique cloners
  • 232,500+ Reddit views across 7 posts, including a 104K hit on r/ClaudeAI and a 70K hit on r/codex
  • ~68,600 Instagram reach across 5 newer posts plus a 256K-view Brand Alchemy Reel breakout
  • 6,989 leads in our outbound pipeline, 28.5% open rate, 29 repo stars attributed to email recipients
  • 2 outside contributors shipped 6-7 skills on their own
• Why this matters: This is the engine we run for clients, executed on ourselves. without any paid promotions, sponsorships, no and warm intros. The numbers below are what 30 days of the playbook look like on a brand new product.

What opendirectory is

The agent skills space blew up between late 2025 and early 2026. Anthropic shipped Skills in October 2025. Codex, OpenClaw, Antigravity, Gemini CLI, and GithubCopilot followed with their own takes. Every CLI agent reads skills slightly differently, and the good skills sit scattered across private repos, gists, and a handful of personal directories.

opendirectory is our fix for that. One installable directory, 56+ skills today, every skill cross-compatible with Claude Code, Codex, OpenCode, Antigravity, GithubCopilot, Gemini CLI, and OpenClaw. The skills are curated for founders and technical marketers who want to ship GTM work.

The ones pulling the most traffic:

• brand-alchemy, a brand naming agent that runs phonosemantic analysis and checks domain availability across TLDs
• cold-email-verifier, which turns a CSV of guessed emails into verified, sequenceable leads
• cook-the-blog, the skill that wrote this case study
• meta-tribeV2-skill, which uses Meta's fMRI model to score video hooks before you post them
• human-tone, which strips AI slop out of marketing copy

Every skill installs with one command:

npx "@opendirectory.dev/skills" list

That gives you the menu. Each skill has its own install line on its page on opendirectory.dev.

The Challenge

A skill directory is a brutal launch problem. Three reasons:

- Supply is exploding, demand is fragmented. Every lab and tooling company shipped skills in the last 6 months. The supply side is saturated. But founders who need skills do not have a single discovery surface, and the ones who know about skills find them through Twitter screenshots and obscure subreddits.

- Directories need both sides at once. A directory with no skills loses developers. A directory with no developers loses contributors. We had to bootstrap supply and demand together, without the brand authority Anthropic gets by default on its own skill page.

- This was not a client project. Varnan was launching its own product, so we could not lean on a founder's network or a pre-built waitlist. We had us, the skills we were using for revenue work, and the same distribution stack we use for clients.

The Strategy

We treated opendirectory like any client open-source project and ran the same engine. Four moves.

Move 1: Ship skills we were already using for revenue

We did not build skills to launch a directory. We built a directory to organize skills we were already using.

brand-alchemy came out of client naming sessions. cook-the-blog is the skill writing this case study right now. cold-email-verifier powers our outbound work. meta-tribeV2-skill came from us trying to pre-score Reels hooks before posting.

Every featured skill in the launch had been tested against real Varnan client work. That decision did more for credibility than any pitch deck could, because when developers tried the skills, the skills solved problems they already had.

Move 2: Ship the install path before posting anything

Before a single Reel or Reddit thread went live, we shipped three things:

• The site at opendirectory.dev, with the install command above the fold and a categorized skill list visible in 5 seconds
• The npm package @opendirectory.dev/skills, so installation is one terminal command
• The repo at github.com/Varnan-Tech/opendirectory with a contributing guide, a contributor merch incentive, and a skill structure ready for PRs

Most launches we audit skip the install path. People land on a launch post and bounce because the install takes more than 10 seconds to find. We refused to ship until that gap closed.

Move 3: Run Reddit and Instagram in parallel, against different audiences

Reddit and Instagram do different jobs. Reddit converts technical, decision-driven audiences. Instagram drives volume and qualified comments from the AI-curious developer crowd. We ran them at the same time but with different content.

The Reddit play used curated listicles. Each post ranked skills inside a skill-friendly subreddit. The Instagram play used product demos showing skills running in real terminal sessions.

We followed Reddit's 90/10 rule (90% value, 10% promo) and kept brand mentions to the skill name and a single GitHub link. The reddit-post-engine skill on the directory automates this workflow now, fetching subreddit rules and top posts before drafting.

Move 4: Build an outbound layer on top of the launch traffic

The launch did its job at the top of the funnel. We built a second layer underneath it.

Using the demand signals from the directory itself, we generated a target list of developers who star skills, agent tooling, and adjacent open-source AI repos. We verified contact information, sequenced multi-touch outreach, and tracked who opened, clicked, and starred the repo.

The point is: stars and downloads were the top of the funnel, not the whole funnel.

The Reddit Numbers

The standout was the r/ClaudeAI "Top 6 Claude Skills" post at 104K views, with a 34.3% US, 5.7% India, 5.2% UK split. The first 4 hours pulled close to 30K views off the algorithmic boost from the listicle format.

The r/codex post at 70K views came from a subreddit that was still under-served on skill content when we posted. Early-mover advantage in a niche subreddit is worth more than the same effort spent in a saturated one.

The full Reddit list:

• r/ClaudeAI: Top 6 Claude Skills: 15th April to 3rd May
• r/codex: Top 10 Open-Source Codex Skills
• r/ClaudeAI: Top 10 Open-Source Claude Skills from 1st-15th April
• r/ClaudeAI: 20 Claude Skills for Marketing, Launch and Sales
• r/ClaudeGTM: Top 5 Open-Source AI Skills for Technical Marketers
• r/gtmengineering: Top 6 Open-Source Claude/OpenClaw Skills for GTM

The Instagram Numbers

The Brand Alchemy Reel is the one that broke out. 256K views, 7K+ likes, 5,255 comments on a single skill demo. The hook was watching the skill name a real product live, score the names phonosemantically, then check domain availability. The 5,255 comments were almost all "send me the link" or "how do I install this." That comment pattern is the one that converts to a star and a download.

The post links:

• Brand Alchemy Reel
• Launch Reel (April 11)
• Carousel (April)
• Product carousel (May)

Creator and Directory Amplification

Gabriel Adamuchi, a creator with ~100K followers in the AI agents space, featured opendirectory in his own carousel. He found the repo on his own from the reddit post, and posted about it. That feature drove a separate wave of repo visits and stars.

koourse.ai, a public directory of AI skills, listed us. The koourse.ai referral now sits at 289 views and 107 unique visitors against the repo in the most recent 14-day window. That listing is permanent. Traffic keeps coming with no further effort from us.

The GitHub Numbers

The repo's traffic dashboard from a 14-day window in mid-May:

• 5,028 clones, with 431 unique cloners
• 6,765 views, with 2,475 unique visitors
• Most popular pages: /tree/main/skills/brand-alchemy at 1,430 views and 992 unique, the repo overview at 1,378 views and 873 unique, /tree/main/skills at 494 views and 323 unique

Referring sites tell the same story as the funnel:

Reddit drove more raw traffic to the repo than GitHub itself, Instagram, and Google combined. That matches what we see across every dev-tool case study we run: when the audience is technical, Reddit converts harder per view than any other platform.

Star history for the repo, live:

The Outbound Funnel

Most case studies skip this part. Top-of-funnel views are easy to brag about. The number that matters is what happens after.

State of the outbound pipeline at the time of writing:

• 6,989 total leads in the system
• 1,000 sent in the first sequence
• 285 opened
• 28.5% open rate
• 29 stars on the repo directly attributed to email recipients
• 2.90% star-from-email rate, the conversion from a cold email to a GitHub star

28.5% open rate on cold dev outbound is well above category average. The 2.90% star rate, which requires opening the email, clicking through, and starring a public repo, is significantly higher than what cold dev outreach delivers in our reference set. The sequence is still scaling, and we expect both numbers to settle as we move from 1,000 sends to 2,000+.

We are not breaking out the targeting methodology since we use the same playbook for client outbound. The point is the funnel works: launch traffic at the top, outbound layer underneath, both pointing at the same npm install.

The Contributor Story

Two outside contributors found the repo cold, read the contributing guide, and shipped 4 to 5 skills between them, with 8 total commits on the main branch. We did not recruit them, did not pay them, did not know they were coming.

That is the strongest signal of a healthy open-source project. People building on it without being asked.

The contributor incentive is live in the CONTRIBUTING.md, with merch for high-quality skill submissions. We are moving this into a formal contributor program in the next 30 days.

Why It Worked

Pulling back over the 30 days, four things made the difference.

The skills were real before the launch. When developers installed brand-alchemy or cold-email-verifier, they got something that solved a problem on day one. The 5,255 comments on the Brand Alchemy Reel were people asking for the install, because they had the same naming problem the skill solved.

Reddit and Instagram did different jobs. Reddit drove qualified traffic from listicles inside skill-friendly subreddits. Instagram drove follows, comments, and qualified product demos. We did not pick the channels because they were popular. We picked them because our ICP was on them and ready to install something useful.

The content was honest. The Reddit listicles included skills we did not build. The Instagram videos showed the product running, not promised outcomes. The install command was visible on the site and on every post. Qualified people self-selected in, unqualified people self-selected out, and the community quality stayed high.

We closed the loop into outbound. Most open-source launches stop at the star count. We treated the stars as the top of the funnel and built an outbound layer that converts launch traffic into sales conversations. The 6,989 leads in the pipeline are the revenue side of the same engine.

What's Next

The next 30 days:

• More featured skills, drawn from internal Varnan skills we have not published yet
• A Codex-first push, since the r/codex post outperformed everything else per view and we have not fully served that audience yet
• The outbound sequence at scale, moving from 1,000 sends to 2,000+ as we verify more of the 6,989 leads
• A formal contributor program for the people who have already shipped, including the merch incentive in CONTRIBUTING.md

The Launch Video

We also created a full product launch video for opendirectory entirely in-house, using AI tools. 500+ prompts, one week of iteration, and about $150 in compute and API costs. Every frame you see below was generated, scored, and refined through Hyperframes by HeyGen.

The process was closer to film production than content generation. We wrote shot-by-shot direction, scored each scene against the brand narrative we were building (founders who ship), and discarded more frames than we kept. The video cost less in dollars than it did in craft decisions, which is the honest math of working with these tools at production quality.

This is something we can do for your product too. If you have a launch coming up and want a video that doesn't feel templated, the same process that produced this direction, iteration, polish applies to whatever you're shipping.

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