GitDiagram Repository Overview
ahmedkhaleel2004/gitdiagram
Explains the architecture of a public GitHub repository through GitDiagram: how the code is organized, the main components with paths, and a Mermaid diagram.
Given your SDK or library name, searches GitHub code search for public repos that import or require it, classifies each repo as company org, affiliated developer, solo developer, or tutorial noise…
$ npx skills add Varnan-Tech/opendirectory --skill sdk-adoption-tracker -a claude-codeProject install by default; add -g for ~/.claude/skills/.
$ gh skill install Varnan-Tech/opendirectory sdk-adoption-tracker --agent claude-codeProject scope by default; add --scope user for a personal install. Needs GitHub CLI 2.90.0 or later (public preview).
$ git clone --depth 1 https://github.com/Varnan-Tech/opendirectory.git skills-src && mkdir -p .claude/skills && cp -r skills-src/skills/sdk-adoption-tracker .claude/skills/sdk-adoption-tracker && rm -rf skills-srcUse ~/.claude/skills/ instead of .claude/skills for a personal install. The folder must contain SKILL.md.
Claude Code skills documentation · loads skills from .claude/skills/
Install the "sdk-adoption-tracker" agent skill from https://github.com/Varnan-Tech/opendirectory/tree/main/skills/sdk-adoption-tracker into .claude/skills/sdk-adoption-tracker/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "sdk-adoption-tracker", then confirm the skill loads.Claude Code copies the folder itself, the same result as the manual copy. Check what it changed before you commit it.
$skill-installer install https://github.com/Varnan-Tech/opendirectory/tree/main/skills/sdk-adoption-trackerType this inside Codex. $skill-installer <name> installs a curated skill from openai/skills. The installer writes to $CODEX_HOME/skills (default ~/.codex/skills). Restart Codex if the skill does not show up.
$ npx skills add Varnan-Tech/opendirectory --skill sdk-adoption-tracker -a codexProject install goes to .agents/skills/; add -g for ~/.codex/skills/.
$ gh skill install Varnan-Tech/opendirectory sdk-adoption-tracker --agent codexProject scope by default (.agents/skills/); add --scope user for a personal install.
$ git clone --depth 1 https://github.com/Varnan-Tech/opendirectory.git skills-src && mkdir -p .agents/skills && cp -r skills-src/skills/sdk-adoption-tracker .agents/skills/sdk-adoption-tracker && rm -rf skills-srcUse ~/.agents/skills/ instead of .agents/skills for a personal install.
Codex skills documentation · loads skills from .agents/skills/
Install the "sdk-adoption-tracker" agent skill from https://github.com/Varnan-Tech/opendirectory/tree/main/skills/sdk-adoption-tracker into .agents/skills/sdk-adoption-tracker/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "sdk-adoption-tracker", then confirm the skill loads.Codex copies the folder itself, the same result as the manual copy. Check what it changed before you commit it.
$ npx skills add Varnan-Tech/opendirectory --skill sdk-adoption-tracker -a cursorProject install goes to .agents/skills/; add -g for ~/.cursor/skills/.
$ gh skill install Varnan-Tech/opendirectory sdk-adoption-tracker --agent cursorProject scope by default (.agents/skills/); add --scope user for a personal install.
$ git clone --depth 1 https://github.com/Varnan-Tech/opendirectory.git skills-src && mkdir -p .cursor/skills && cp -r skills-src/skills/sdk-adoption-tracker .cursor/skills/sdk-adoption-tracker && rm -rf skills-srcUse ~/.cursor/skills/ instead of .cursor/skills for a personal install.
Cursor skills documentation · loads skills from .cursor/skills/, .agents/skills/, .claude/skills/, .codex/skills/
Install the "sdk-adoption-tracker" agent skill from https://github.com/Varnan-Tech/opendirectory/tree/main/skills/sdk-adoption-tracker into .cursor/skills/sdk-adoption-tracker/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "sdk-adoption-tracker", then confirm the skill loads.Cursor copies the folder itself, the same result as the manual copy. Check what it changed before you commit it.
$ gemini skills install https://github.com/Varnan-Tech/opendirectory.git --path skills/sdk-adoption-tracker--scope user (default) or --scope workspace; --path is the subfolder of the repo that holds the skill; --consent skips the security confirmation prompt.
$ npx skills add Varnan-Tech/opendirectory --skill sdk-adoption-tracker -a gemini-cliProject install goes to .agents/skills/; add -g for ~/.gemini/skills/.
$ gh skill install Varnan-Tech/opendirectory sdk-adoption-tracker --agent gemini-cliProject scope by default (.agents/skills/); add --scope user for a personal install.
$ git clone --depth 1 https://github.com/Varnan-Tech/opendirectory.git skills-src && mkdir -p .gemini/skills && cp -r skills-src/skills/sdk-adoption-tracker .gemini/skills/sdk-adoption-tracker && rm -rf skills-srcUse ~/.gemini/skills/ instead of .gemini/skills for a personal install, then run /skills reload.
Gemini CLI skills documentation · loads skills from .gemini/skills/, .agents/skills/
Install the "sdk-adoption-tracker" agent skill from https://github.com/Varnan-Tech/opendirectory/tree/main/skills/sdk-adoption-tracker into .gemini/skills/sdk-adoption-tracker/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "sdk-adoption-tracker", then confirm the skill loads.Gemini CLI copies the folder itself, the same result as the manual copy. Check what it changed before you commit it.
$ gh skill install Varnan-Tech/opendirectory sdk-adoption-trackerInstalls for Copilot at project scope by default; add --scope user for a personal install. Preview a skill first with gh skill preview. Needs GitHub CLI 2.90.0 or later (public preview).
$ npx skills add Varnan-Tech/opendirectory --skill sdk-adoption-tracker -a github-copilotProject install goes to .agents/skills/; add -g for ~/.copilot/skills/.
$ git clone --depth 1 https://github.com/Varnan-Tech/opendirectory.git skills-src && mkdir -p .github/skills && cp -r skills-src/skills/sdk-adoption-tracker .github/skills/sdk-adoption-tracker && rm -rf skills-srcUse ~/.copilot/skills/ instead of .github/skills for a personal install. Commit .github/skills so cloud agent and code review can use it.
GitHub Copilot skills documentation · loads skills from .github/skills/, .claude/skills/, .agents/skills/
Install the "sdk-adoption-tracker" agent skill from https://github.com/Varnan-Tech/opendirectory/tree/main/skills/sdk-adoption-tracker into .github/skills/sdk-adoption-tracker/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "sdk-adoption-tracker", then confirm the skill loads.GitHub Copilot copies the folder itself, the same result as the manual copy. Check what it changed before you commit it.
$ npx skills add Varnan-Tech/opendirectory --skill sdk-adoption-tracker -a opencodeOpenCode documents no install command of its own. Project install goes to .agents/skills/; add -g for ~/.config/opencode/skills/.
$ gh skill install Varnan-Tech/opendirectory sdk-adoption-tracker --agent opencodeProject scope by default (.agents/skills/); add --scope user for a personal install.
$ git clone --depth 1 https://github.com/Varnan-Tech/opendirectory.git skills-src && mkdir -p .opencode/skills && cp -r skills-src/skills/sdk-adoption-tracker .opencode/skills/sdk-adoption-tracker && rm -rf skills-srcUse ~/.config/opencode/skills/ instead of .opencode/skills for a personal install.
OpenCode skills documentation · loads skills from .opencode/skills/, .claude/skills/, .agents/skills/
Install the "sdk-adoption-tracker" agent skill from https://github.com/Varnan-Tech/opendirectory/tree/main/skills/sdk-adoption-tracker into .opencode/skills/sdk-adoption-tracker/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "sdk-adoption-tracker", then confirm the skill loads.OpenCode copies the folder itself, the same result as the manual copy. Check what it changed before you commit it.
sdk-adoption-trackerGiven your SDK or library name, searches GitHub code search for public repos that import or require it, classifies each repo as company org, affiliated developer, solo developer, or tutorial noise…
SDK Adoption Tracker is an agent skill from Varnan-Tech/opendirectory. Given your SDK or library name, searches GitHub code search for public repos that import or require it, classifies each repo as company org, affiliated developer, solo developer, or tutorial noise, scores by adoption signal strength, detects new adopters by date, and outputs a ranked list of who is building on you with outreach context per high-signal company. Use when asked to find who uses your SDK, track SDK adoption, find companies building on your library, identify warm leads from existing SDK users, or see…
Its SKILL.md is about 7.7k tokens, which your agent loads only when the skill is triggered. The skill folder holds 9 other files, including scripts and reference files (for example `README.md`, `evals/evals.json` and `references/import-patterns.md`). Compatibility notes: ["claude-code","gemini-cli","github-copilot"]
It sits in Development, covering Codebase onboarding. It works with GitHub. The repository describes itself as: AI Agent Skills built for Founders who hate Marketing. The licence is MIT.
8 steps, taken from the step headings in SKILL.md.
Read from SKILL.md and the folder at commit 62e437a. It shows what the files ask for, not the result of running them.
Pre-approves nothing: there is no allowed-tools line, so your agent's usual permission prompts apply.
From allowed-tools in the SKILL.md frontmatter.
Ships 1 file in scripts/ (Python), which the agent can run.
Shell commands in SKILL.md call:
python3curlFrom the folder's file list and the shell code blocks in SKILL.md.
Hosts in commands or code, which the agent is likely to contact:
api.github.comgithub.comFrom URLs in SKILL.md, links to its own repository left out.
Names these keys or tokens, usually read from environment variables:
GITHUB_TOKENFrom names ending in _API_KEY, _TOKEN, _SECRET, _KEY or _PASSWORD in SKILL.md.
["claude-code","gemini-cli","github-copilot"]
From compatibility in the SKILL.md frontmatter.
SDK Adoption Tracker loads about 7.7k tokens when it runs, and up to ~10k if it reads all its reference files. Until then it costs about 199 tokens; SKILL.md has 767 words of instructions outside code blocks.
Estimates: characters ÷ 4, the usual rule of thumb; real counts depend on the model's tokenizer. Scripts and assets cost tokens only if the agent reads them.
The automated check found no risky patterns in SKILL.md.
Automated static check — not a guarantee. Review scripts before installing. It scans the text of SKILL.md for risky patterns (piping downloads into a shell, reading credential files, hidden Unicode, destructive commands); the scripts in this folder are not scanned.
The full file from Varnan-Tech/opendirectory at commit 62e437a, republished under its MIT licence (© Varnan-Tech). 767 words, ~7,671 tokens.
.claude/skills/sdk-adoption-tracker/SKILL.md (or your agent's skills folder). This skill also uses 6 other files; get the full folder from GitHub.Take an SDK name. Search GitHub for public repos that import it. Score each repo by company signal, activity, and noise indicators. Enrich high-signal repos with owner and contributor data. Output a ranked adoption report with outreach context for company adopters.
Critical rule: Every repo in the output must exist in the GitHub code search API response. Every company name must come from the GitHub user or org API company or name field. Every contributor handle must come from the GitHub contributors API response. If any field is empty in the API, write "not listed" -- do not infer, guess, or extrapolate.
| The agent will want to... | Why that's wrong |
|---|---|
| Run code search without GITHUB_TOKEN | Unauthenticated code search hits a 3 req/min secondary rate limit and fails on any meaningful scan. GITHUB_TOKEN is required. Stop at Step 1 with a clear error if it is missing. |
| Include forks of the SDK itself | Repos that fork the SDK are contributors or mirrors, not adopters. Filter out repos where fork == true AND the repo name matches the SDK name. |
| Send all 500 raw search results to the AI | Code search can return up to 500 results, most of which are noise. Filter and score locally first. Send only the top 20 high-signal repos to the AI analysis step. |
| Report tutorial and example repos as adopters | Repos with "example", "tutorial", "demo", "learn", "sample", "playground", "starter" in the name or description are not production users. Mark as tutorial_noise and exclude from lead briefs. |
| Invent company names or contact handles | Every company name must come from the GitHub company or org name field. Every contributor handle must come from the contributors API response. If a field is empty, write "not listed". |
| Use one import pattern for all ecosystems | require('sdk') will not find Python users. Auto-detect ecosystem from the SDK name and build ecosystem-specific patterns. Ask the user if auto-detection is ambiguous. |
if [ -z "$GITHUB_TOKEN" ]; then
echo "ERROR: GITHUB_TOKEN is required for code search."
echo "Add a token at github.com/settings/tokens (no scopes needed for public repos)."
echo "Without it, GitHub code search hits a 3 req/min secondary rate limit and fails."
exit 1
fi
echo "GITHUB_TOKEN: set"
curl -s -H "Authorization: Bearer $GITHUB_TOKEN" \
-H "Accept: application/vnd.github+json" \
"https://api.github.com/rate_limit" | python3 -c "
import json, sys
d = json.load(sys.stdin)
search = d['resources']['search']
core = d['resources']['core']
print(f'Search rate: {search[\"remaining\"]}/{search[\"limit\"]} remaining')
print(f'Core rate: {core[\"remaining\"]}/{core[\"limit\"]} remaining')
"If search remaining is 0: stop. Tell the user the reset time from X-RateLimit-Reset.
Collect from the conversation:
@company/my-sdk, requests, github.com/org/go-sdk)npm, python, go, gem) -- auto-detected if not providedAuto-detect ecosystem:
@ or contains -: npm/ or -: pythongithub.com/: goIf no SDK name is provided: Ask: "Which SDK or library would you like to track? Provide the package name as it appears in import statements (e.g. stripe, @clerk/nextjs, requests)."
python3 << 'PYEOF'
import json, sys, re
sdk_name = "SDK_NAME_HERE"
ecosystem_override = "" # leave empty for auto-detect
exclude_owner = "" # optional: owner name to exclude (usually the SDK publisher)
product_context = "" # optional: what your product does
# Auto-detect ecosystem
if ecosystem_override:
ecosystem = ecosystem_override
elif sdk_name.startswith("@") or "-" in sdk_name:
ecosystem = "npm"
elif re.match(r'^[a-z][a-z0-9_]*$', sdk_name):
ecosystem = "python"
elif "github.com/" in sdk_name:
ecosystem = "go"
else:
ecosystem = "generic"
print(f"SDK: {sdk_name}")
print(f"Ecosystem: {ecosystem}")
print(f"Exclude owner: {exclude_owner or '(none)'}")
with open("/tmp/sat-input.json", "w") as f:
json.dump({
"sdk_name": sdk_name,
"ecosystem": ecosystem,
"exclude_owner": exclude_owner,
"product_context": product_context
}, f)
PYEOFCheck for standalone script first -- it handles Steps 3-5 in one call.
ls scripts/fetch.py 2>/dev/null && echo "script available" || echo "script not found"If the script is available, run it and skip to Step 6:
python3 scripts/fetch.py "$(python3 -c "import json; d=json.load(open('/tmp/sat-input.json')); print(d['sdk_name'])")" \
--ecosystem "$(python3 -c "import json; d=json.load(open('/tmp/sat-input.json')); print(d['ecosystem'])")" \
--exclude "$(python3 -c "import json; d=json.load(open('/tmp/sat-input.json')); print(d.get('exclude_owner',''))")" \
--output /tmp/sat-script-out.jsonThen load into the temp file format Steps 6-8 expect:
python3 << 'PYEOF'
import json
out = json.load(open("/tmp/sat-script-out.json"))
json.dump(out["raw_results"], open("/tmp/sat-raw-results.json", "w"), indent=2)
json.dump(out["scored"], open("/tmp/sat-scored.json", "w"), indent=2)
json.dump(out["enriched"], open("/tmp/sat-enriched.json", "w"), indent=2)
print(f"Loaded: {len(out['raw_results'])} raw | {len(out['scored'])} scored | {len(out['enriched'])} enriched")
PYEOFIf the script is not available, run the inline code below.
Build import patterns and search GitHub code for each:
python3 << 'PYEOF'
import json, urllib.request, ssl, time, os
from datetime import datetime, timezone
ctx = ssl._create_unverified_context()
token = os.environ["GITHUB_TOKEN"]
headers = {
"Accept": "application/vnd.github+json",
"Authorization": f"Bearer {token}",
"User-Agent": "sdk-adoption-tracker/1.0"
}
data = json.load(open("/tmp/sat-input.json"))
sdk_name = data["sdk_name"]
ecosystem = data["ecosystem"]
# Build query patterns per ecosystem
if ecosystem == "npm":
# Use sdk name without @ prefix for bare searches
bare = sdk_name.lstrip("@").replace("/", "/")
queries = [
f'require("{sdk_name}")',
f"require('{sdk_name}')",
f'from "{sdk_name}"',
f"from '{sdk_name}'",
]
elif ecosystem == "python":
queries = [
f"import {sdk_name}",
f"from {sdk_name} import",
f"from {sdk_name}.",
]
elif ecosystem == "go":
queries = [f'"{sdk_name}"']
else:
queries = [sdk_name]
print(f"Building queries for {sdk_name} ({ecosystem}):")
for q in queries:
print(f" {q}")
seen_repos = {} # full_name -> first match
search_rate_remaining = 30
flags = []
for i, query in enumerate(queries):
if search_rate_remaining <= 2:
flags.append(f"Code search rate limit low ({search_rate_remaining}) -- skipped remaining patterns")
print(f" Rate limit low ({search_rate_remaining}), stopping early")
break
url = f"https://api.github.com/search/code?q={urllib.parse.quote(query)}&per_page=100"
req = urllib.request.Request(url, headers=headers)
try:
with urllib.request.urlopen(req, timeout=20, context=ctx) as resp:
search_rate_remaining = int(resp.headers.get("X-RateLimit-Remaining", 10))
raw = json.loads(resp.read())
items = raw.get("items", [])
total = raw.get("total_count", 0)
print(f" Pattern '{query}': {total} total, {len(items)} fetched | rate_remaining={search_rate_remaining}")
for item in items:
repo = item.get("repository", {})
full_name = repo.get("full_name", "")
if full_name and full_name not in seen_repos:
seen_repos[full_name] = {
"full_name": full_name,
"name": repo.get("name", ""),
"owner_login": repo.get("owner", {}).get("login", ""),
"owner_type": repo.get("owner", {}).get("type", ""),
"file_path": item.get("path", ""),
"matched_pattern": query,
"html_url": repo.get("html_url", ""),
"description": repo.get("description") or "",
}
except urllib.error.HTTPError as e:
if e.code == 403:
flags.append(f"Code search rate limit hit on pattern '{query}'")
print(f" Rate limit hit (403) on '{query}'")
break
else:
print(f" HTTP {e.code} on '{query}'")
except Exception as e:
print(f" Error on '{query}': {e}")
# Respect 10 req/min code search limit
if i < len(queries) - 1:
time.sleep(6)
results = list(seen_repos.values())
json.dump(results, open("/tmp/sat-raw-results.json", "w"), indent=2)
print(f"\nTotal unique repos found: {len(results)}")
if flags:
print("Flags:", flags)
import urllib.parse # ensure imported
PYEOFIf 0 results: Tell the user: "No repos found importing {sdk_name}. GitHub code search indexing takes 1-4 weeks for new packages. If the SDK is established, check the import patterns in references/import-patterns.md."
No API call. Pure Python. Filter noise, compute adoption score, classify each repo.
python3 << 'PYEOF'
import json
from datetime import datetime, timezone
data = json.load(open("/tmp/sat-input.json"))
exclude_owner = data.get("exclude_owner", "").lower()
sdk_name = data["sdk_name"].lower().split("/")[-1].replace("@", "")
results = json.load(open("/tmp/sat-raw-results.json"))
TUTORIAL_WORDS = {"example", "tutorial", "demo", "learn", "sample", "starter",
"boilerplate", "template", "playground", "test", "course", "workshop"}
scored = []
now = datetime.now(tz=timezone.utc)
for repo in results:
full_name = repo["full_name"]
owner_login = repo.get("owner_login", "").lower()
repo_name = repo.get("name", "").lower()
description = (repo.get("description") or "").lower()
owner_type = repo.get("owner_type", "User")
# Exclude the SDK owner's own repos
if exclude_owner and owner_login == exclude_owner.lower():
continue
# Detect tutorial noise
name_words = set(repo_name.replace("-", " ").replace("_", " ").split())
desc_words = set(description.split())
is_tutorial = bool((name_words | desc_words) & TUTORIAL_WORDS)
# Also exclude if repo name IS the SDK name (likely a fork)
if repo_name == sdk_name or repo_name.startswith(sdk_name + "-"):
is_tutorial = True # treat as noise
# Classification tier
if is_tutorial:
tier = "tutorial_noise"
elif owner_type == "Organization":
tier = "company_org"
else:
tier = "solo_dev" # will be upgraded to affiliated_dev in Step 5 if company field populated
# Adoption score (filled with partial data now, enriched in Step 5)
score = 0
if owner_type == "Organization": score += 50
if not is_tutorial: score += 20
# stars, days_since_push, is_fork, is_archived added in Step 5
scored.append({
**repo,
"tier": tier,
"is_tutorial": is_tutorial,
"adoption_score": score,
"enriched": False
})
# Sort: company_org first, then by tier
tier_order = {"company_org": 0, "affiliated_dev": 1, "solo_dev": 2, "tutorial_noise": 3}
scored.sort(key=lambda x: (tier_order.get(x["tier"], 9), -x["adoption_score"]))
json.dump(scored, open("/tmp/sat-scored.json", "w"), indent=2)
tiers = {}
for r in scored:
tiers[r["tier"]] = tiers.get(r["tier"], 0) + 1
print(f"Classification:")
for tier, count in sorted(tiers.items(), key=lambda x: tier_order.get(x[0], 9)):
print(f" {tier}: {count}")
print(f"Total: {len(scored)} repos")
non_noise = [r for r in scored if r["tier"] != "tutorial_noise"]
print(f"\nTop repos for enrichment (non-noise): {len(non_noise)}")
for r in non_noise[:5]:
print(f" {r['full_name']} ({r['tier']}) -- {r.get('description','')[:60]}")
PYEOFIf all repos are tutorial_noise: Stop. Tell the user: "All repos found appear to be tutorials or examples. No production adopters detected in public GitHub. The SDK may be too new, or the package name is generic enough that search results are dominated by examples."
Fetch full repo metadata, owner profile, and top contributors for non-noise repos. Skip tutorial_noise repos entirely.
python3 << 'PYEOF'
import json, urllib.request, ssl, os, time
from datetime import datetime, timezone
ctx = ssl._create_unverified_context()
token = os.environ["GITHUB_TOKEN"]
headers = {
"Accept": "application/vnd.github+json",
"Authorization": f"Bearer {token}",
"User-Agent": "sdk-adoption-tracker/1.0"
}
scored = json.load(open("/tmp/sat-scored.json"))
core_remaining = 5000
flags = []
def gh_get(path):
global core_remaining
req = urllib.request.Request(f"https://api.github.com{path}", headers=headers)
try:
with urllib.request.urlopen(req, timeout=15, context=ctx) as resp:
remaining = resp.headers.get("X-RateLimit-Remaining")
if remaining:
core_remaining = int(remaining)
return json.loads(resp.read())
except urllib.error.HTTPError as e:
if e.code == 404:
return None
raise
except Exception:
return None
target = [r for r in scored if r["tier"] != "tutorial_noise"]
print(f"Enriching {len(target)} repos (skipping tutorial_noise)...")
enriched = []
for item in target:
full_name = item["full_name"]
owner_login = item["owner_login"]
owner_type = item["owner_type"]
if core_remaining <= 10:
flags.append(f"Core rate limit low ({core_remaining}) -- skipped enrichment for {full_name} and remaining repos")
enriched.append({**item, "enriched": False})
continue
# Fetch full repo metadata
repo_data = gh_get(f"/repos/{full_name}")
if not repo_data:
print(f" {full_name}: repo not found")
continue
stars = repo_data.get("stargazers_count", 0)
is_fork = repo_data.get("fork", False)
is_archived = repo_data.get("archived", False)
language = repo_data.get("language") or ""
description = repo_data.get("description") or item.get("description", "")
pushed_at = repo_data.get("pushed_at") or ""
created_at = repo_data.get("created_at") or ""
repo_url = repo_data.get("html_url", f"https://github.com/{full_name}")
# Compute days since last push
days_since_push = 999
if pushed_at:
pushed_dt = datetime.fromisoformat(pushed_at.replace("Z", "+00:00"))
days_since_push = (datetime.now(tz=timezone.utc) - pushed_dt).days
days_since_created = 999
if created_at:
created_dt = datetime.fromisoformat(created_at.replace("Z", "+00:00"))
days_since_created = (datetime.now(tz=timezone.utc) - created_dt).days
# Fetch owner profile (user or org)
owner_profile = {}
company = ""
org_website = ""
if owner_type == "Organization":
org_data = gh_get(f"/orgs/{owner_login}")
if org_data:
company = org_data.get("name") or owner_login
org_website = org_data.get("blog") or ""
owner_profile = {
"type": "org",
"name": org_data.get("name") or owner_login,
"description": org_data.get("description") or "",
"website": org_website,
"email": org_data.get("email") or "",
"public_repos": org_data.get("public_repos", 0),
"followers": org_data.get("followers", 0),
}
else:
user_data = gh_get(f"/users/{owner_login}")
if user_data:
company = user_data.get("company") or ""
owner_profile = {
"type": "user",
"name": user_data.get("name") or owner_login,
"company": company,
"bio": user_data.get("bio") or "",
"blog": user_data.get("blog") or "",
"followers": user_data.get("followers", 0),
"twitter_username": user_data.get("twitter_username") or "not listed",
}
# Upgrade tier if company field is populated
if company and item["tier"] == "solo_dev":
item["tier"] = "affiliated_dev"
# Fetch top contributors (skip if rate limit low)
top_contributors = []
if core_remaining > 20:
contributors = gh_get(f"/repos/{full_name}/contributors?per_page=3")
if contributors:
top_contributors = [
{"login": c.get("login", ""), "contributions": c.get("contributions", 0)}
for c in contributors[:3]
]
# Compute final adoption score
score = 0
if owner_type == "Organization": score += 50
if company and company.strip(): score += 20
score += min(stars, 500) / 10
if days_since_push < 30: score += 30
if days_since_push < 7: score += 20
if not is_fork: score += 10
if not is_archived: score += 10
if not item.get("is_tutorial", False): score += 20
tier = item["tier"]
if is_archived or is_fork:
tier = "tutorial_noise" if item.get("is_tutorial") else tier
enriched_item = {
**item,
"description": description,
"stars": stars,
"language": language,
"is_fork": is_fork,
"is_archived": is_archived,
"days_since_push": days_since_push,
"days_since_created": days_since_created,
"pushed_at": pushed_at,
"created_at": created_at,
"repo_url": repo_url,
"tier": tier,
"adoption_score": round(score, 1),
"company": company,
"org_website": org_website,
"owner_profile": owner_profile,
"top_contributors": top_contributors,
"enriched": True,
}
enriched.append(enriched_item)
print(f" {full_name} | tier={tier} | score={round(score,1)} | "
f"stars={stars} | pushed={days_since_push}d ago | "
f"company={company or 'not listed'} | rate={core_remaining}")
time.sleep(0.1)
enriched.sort(key=lambda x: -x["adoption_score"])
json.dump(enriched, open("/tmp/sat-enriched.json", "w"), indent=2)
print(f"\nEnrichment complete: {len(enriched)} repos | rate_remaining={core_remaining}")
if flags:
for f in flags:
print(f" FLAG: {f}")
PYEOFPrint top adopters, then generate outreach briefs for high-signal company repos.
python3 << 'PYEOF'
import json
from datetime import datetime, timezone
enriched = json.load(open("/tmp/sat-enriched.json"))
data = json.load(open("/tmp/sat-input.json"))
product_context = data.get("product_context", "")
sdk_name = data["sdk_name"]
high_signal = [r for r in enriched if r["adoption_score"] >= 80]
medium = [r for r in enriched if 40 <= r["adoption_score"] < 80]
noise = [r for r in enriched if r["adoption_score"] < 40 or r["tier"] == "tutorial_noise"]
print("=== DATA FOR ADOPTION BRIEF GENERATION ===")
print(f"SDK: {sdk_name}")
print(f"Product context: {product_context or '(none provided)'}")
print()
for item in (high_signal + medium)[:20]:
prof = item.get("owner_profile", {})
contribs = item.get("top_contributors", [])
primary = contribs[0] if contribs else {}
print(f"REPO: {item['full_name']} (tier={item['tier']}, score={item['adoption_score']})")
print(f" Stars: {item.get('stars', 0)} | Language: {item.get('language','?')} | "
f"Pushed: {item.get('days_since_push', '?')} days ago")
print(f" Description: {item.get('description','none')}")
print(f" SDK found in: {item.get('file_path','?')}")
print(f" Owner type: {item.get('owner_type','?')} | Company: {item.get('company','not listed')}")
if prof.get("type") == "org":
print(f" Org: {prof.get('name')} | Website: {prof.get('website','none')} | "
f"Repos: {prof.get('public_repos',0)}")
elif prof.get("type") == "user":
print(f" User: {prof.get('name')} | Company: {prof.get('company','not listed')} | "
f"Twitter: {prof.get('twitter_username','not listed')} | "
f"Followers: {prof.get('followers',0)}")
if primary:
print(f" Top contributor: @{primary.get('login')} ({primary.get('contributions',0)} commits)")
print()
PYEOFUsing the repo data printed above, generate an adoption brief for each HIGH-SIGNAL repo (score >= 80).
Rules:
Write your briefs to /tmp/sat-briefs.json with this structure:
{
"adoption_briefs": [
{
"repo": "owner/repo-name",
"tier": "company_org",
"adoption_score": 124.0,
"company": "Company Name or not listed",
"top_contributor": "@handle or not listed",
"twitter": "@handle or not listed",
"stars": 234,
"language": "TypeScript",
"sdk_file": "src/api/client.ts",
"why_reach_out": "2-3 sentences specific to this repo's signals",
"suggested_message": "2-4 sentences naming the repo, SDK file, and product_context connection"
}
]
}After writing, confirm:
python3 -c "
import json
d = json.load(open('/tmp/sat-briefs.json'))
print(f'Briefs generated: {len(d.get(\"adoption_briefs\", []))}')
for b in d['adoption_briefs']:
print(f' {b[\"repo\"]} ({b[\"tier\"]}): score={b[\"adoption_score\"]} company={b[\"company\"]}')
"python3 << 'PYEOF'
import json
raw = json.load(open("/tmp/sat-raw-results.json"))
enriched = json.load(open("/tmp/sat-enriched.json"))
briefs = json.load(open("/tmp/sat-briefs.json"))
failures = []
# Verify every repo in briefs exists in raw search results
raw_full_names = {r["full_name"] for r in raw}
for brief in briefs.get("adoption_briefs", []):
if brief.get("repo") not in raw_full_names:
failures.append(f"Brief for unknown repo '{brief.get('repo')}' not in code search results -- removed")
briefs["adoption_briefs"] = [
b for b in briefs.get("adoption_briefs", []) if b.get("repo") in raw_full_names
]
# Verify briefs are sorted by adoption_score descending
scores = [b["adoption_score"] for b in briefs.get("adoption_briefs", [])]
if scores != sorted(scores, reverse=True):
briefs["adoption_briefs"].sort(key=lambda x: -x["adoption_score"])
failures.append("Re-sorted briefs by adoption_score descending")
# Check for em dashes
briefs_str = json.dumps(briefs)
if "—" in briefs_str:
briefs_str = briefs_str.replace("—", " - ")
briefs = json.loads(briefs_str)
failures.append("Fixed: em dash characters removed from briefs")
# Check for forbidden words
forbidden = ["powerful", "robust", "seamless", "innovative", "game-changing",
"streamline", "leverage", "transform", "revolutionize"]
full_text = json.dumps(briefs).lower()
for word in forbidden:
if word in full_text:
failures.append(f"Warning: forbidden word '{word}' found in briefs -- review before presenting")
# Check required fields
for brief in briefs.get("adoption_briefs", []):
for field in ["repo", "tier", "adoption_score", "company", "top_contributor",
"why_reach_out", "suggested_message"]:
if brief.get(field) is None:
failures.append(f"Missing field '{field}' in brief for {brief.get('repo', '?')}")
output = {
"enriched": enriched,
"briefs": briefs,
"data_quality_flags": failures
}
json.dump(output, open("/tmp/sat-output.json", "w"), indent=2)
print(f"QA complete. Issues found: {len(failures)}")
for f in failures:
print(f" - {f}")
if not failures:
print("All QA checks passed.")
PYEOFpython3 << 'PYEOF'
import json, os
from datetime import datetime, timezone
output = json.load(open("/tmp/sat-output.json"))
enriched = output["enriched"]
briefs_map = {b["repo"]: b for b in output["briefs"].get("adoption_briefs", [])}
flags = output["data_quality_flags"]
data = json.load(open("/tmp/sat-input.json"))
sdk_name = data["sdk_name"]
date_str = datetime.now(tz=timezone.utc).strftime("%Y-%m-%d")
high_signal = [r for r in enriched if r["adoption_score"] >= 80]
medium = [r for r in enriched if 40 <= r["adoption_score"] < 80]
noise = [r for r in enriched if r["adoption_score"] < 40 or r["tier"] == "tutorial_noise"]
# Compute velocity buckets
new_7d = sum(1 for r in enriched if r.get("days_since_created", 999) <= 7)
new_30d = sum(1 for r in enriched if r.get("days_since_created", 999) <= 30)
# Load previous snapshot for comparison
slug = sdk_name.replace("@", "").replace("/", "-")
prev_repos = set()
prev_path = f"docs/sdk-adopters/"
if os.path.isdir(prev_path):
import glob
prev_files = sorted(glob.glob(f"{prev_path}{slug}-*.json"))
if prev_files:
try:
prev_data = json.load(open(prev_files[-1]))
prev_repos = {r["full_name"] for r in prev_data.get("enriched", [])}
except Exception:
pass
new_since_last = len({r["full_name"] for r in enriched} - prev_repos) if prev_repos else None
tier_counts = {}
for r in enriched:
tier_counts[r["tier"]] = tier_counts.get(r["tier"], 0) + 1
lines = [
f"## SDK Adoption Report: {sdk_name}",
f"Repos found: {len(enriched)} | Company repos: {tier_counts.get('company_org', 0)} | "
f"Active (30 days): {sum(1 for r in enriched if r.get('days_since_push', 999) <= 30)} | Date: {date_str}",
"",
"---",
"",
"### Adoption Velocity",
f"New repos last 7 days: {new_7d}",
f"New repos last 30 days: {new_30d}",
]
if new_since_last is not None:
lines.append(f"New since last run: {new_since_last}")
lines += ["", "---", ""]
if high_signal or medium:
lines += ["### Top Adopters", ""]
lines += [
"| Rank | Repo | Stars | Tier | Score | Pushed | Language |",
"|---|---|---|---|---|---|---|",
]
for i, r in enumerate((high_signal + medium)[:15], 1):
pushed_label = f"{r.get('days_since_push','?')}d ago"
lines.append(
f"| {i} | [{r['full_name']}]({r.get('repo_url', '')}) | "
f"{r.get('stars',0):,} | {r['tier']} | {r['adoption_score']} | "
f"{pushed_label} | {r.get('language','?')} |"
)
lines += ["", "---", ""]
if high_signal:
lines += ["### Adoption Briefs (score >= 80)", ""]
for r in high_signal:
brief = briefs_map.get(r["full_name"], {})
prof = r.get("owner_profile", {})
lines.append(f"#### {r['full_name']} [score: {r['adoption_score']}]")
lines.append(f"Owner: {r['owner_login']} ({r['owner_type']})")
lines.append(f"Stars: {r.get('stars',0):,} | Language: {r.get('language','?')} | "
f"Last pushed: {r.get('days_since_push','?')} days ago")
if r.get("description"):
lines.append(f"What they're building: {r['description']}")
lines.append(f"SDK found in: {r.get('file_path','?')}")
if r.get("company") and r["company"] != "not listed":
lines.append(f"Company: {r['company']}")
if r.get("org_website"):
lines.append(f"Website: {r['org_website']}")
contribs = r.get("top_contributors", [])
if contribs:
lines.append(f"Top contributor: @{contribs[0]['login']} ({contribs[0]['contributions']} commits)")
lines.append("")
if brief.get("why_reach_out"):
lines.append(f"**Why reach out:** {brief['why_reach_out']}")
if brief.get("suggested_message"):
lines.append(f"\n**Suggested message:**")
lines.append(f"> {brief['suggested_message']}")
lines += ["", "---", ""]
lines += [
"### Adoption Breakdown",
"",
"| Tier | Count |",
"|---|---|",
]
for tier in ["company_org", "affiliated_dev", "solo_dev", "tutorial_noise"]:
count = tier_counts.get(tier, 0)
lines.append(f"| {tier} | {count} |")
lines += ["", "---", ""]
lines.append(f"Data quality notes: {'; '.join(flags) if flags else 'None'}")
output_dir = f"docs/sdk-adopters"
os.makedirs(output_dir, exist_ok=True)
md_path = f"{output_dir}/{slug}-{date_str}.md"
json_path = f"{output_dir}/{slug}-{date_str}.json"
open(md_path, "w").write("\n".join(lines))
json.dump({"enriched": enriched, "briefs": output["briefs"]}, open(json_path, "w"), indent=2)
print("\n".join(lines))
print(f"\nSaved to: {md_path}")
print(f"JSON snapshot: {json_path} (used for velocity tracking on next run)")
PYEOFClean up temp files:
rm -f /tmp/sat-input.json /tmp/sat-raw-results.json /tmp/sat-scored.json \
/tmp/sat-enriched.json /tmp/sat-briefs.json /tmp/sat-output.json© Varnan-Tech, MIT. Rendered from Markdown: HTML in the file is shown as text, images as links, and headings moved down two levels. Raw file
SKILL.md and 6 other files (scripts, references) in skills/sdk-adoption-tracker of Varnan-Tech/opendirectory.
Open the folder on GitHubat commit 62e437a
SDK Adoption Tracker next to the 5 skills that share the most tags, products or categories with it. Stars are the repository's; “used in” counts other GitHub owners with a copy.
| Skill | Stars | Used in | Tokens | Auto-check | Licence | Repo updated |
|---|---|---|---|---|---|---|
| SDK Adoption Tracker this skillVarnan-Tech/opendirectory | 674 | — | ~7.7k | Automated safety check: Pass | MIT | |
| GitDiagram Repository Overviewahmedkhaleel2004/gitdiagram | 18k | — | ~427 | Automated safety check: Pass | MIT | |
| GitDiagram Repo Architectureahmedkhaleel2004/gitdiagram | 18k | — | ~429 | Automated safety check: Pass | MIT | |
| Octocode Code Researchbgauryy/octocode | 949 | — | ~1.5k | Automated safety check: Pass | MIT | |
| Releaseyoanbernabeu/grepai | 1.9k | — | ~918 | Automated safety check: Pass | MIT | |
| BTCA Local Repo Searchstickerdaniel/linkedin-mcp-server | 3.8k | — | ~660 | Automated safety check: Pass | Apache-2.0 |
ahmedkhaleel2004/gitdiagram
Explains the architecture of a public GitHub repository through GitDiagram: how the code is organized, the main components with paths, and a Mermaid diagram.
ahmedkhaleel2004/gitdiagram
Explains how a public GitHub repository is built by fetching its GitDiagram architecture diagram, components and optional explainer video.
bgauryy/octocode
Researches code with evidence: traces callers, imports and cross-repo links, diagnoses failures and reports findings with exact file and line references and a confidence label.
yoanbernabeu/grepai
Create a new release for grepai. An agent skill from yoanbernabeu/grepai.
stickerdaniel/linkedin-mcp-server
Searches git repositories cloned locally under a sandbox folder to answer questions with cited links and complete code snippets.
POW-Software/ByteSync
Analyze a GitHub issue in depth and produce a detailed specification based on codebase analysis.
Varnan-Tech/opendirectory
A skill your agent uses when fetching, searching, or analyzing transcripts from Lenny's Podcast, Dwarkesh Podcast, Cheeky Pint, 20VC, or A16z Podcast.
Varnan-Tech/opendirectory
Creates professionally designed B2B SaaS e-books in HTML + CSS, exported as print-ready PDF.
Varnan-Tech/opendirectory
Given a product utility and ICP, researches the internet to find the specific channels.
Varnan-Tech/opendirectory
Generates and updates README.md and API reference docs by reading your codebase's functions, routes, types, schemas, and architecture.
Varnan-Tech/opendirectory
Generates data visualization charts (bar, line, area, pie, doughnut, scatter, radar, treemap) as PNG using Apache ECharts v6.
Varnan-Tech/opendirectory
Creates animated looping GIFs from CSS animations (default) or AI image-to-video.
Works with
Categories
Given your SDK or library name, searches GitHub code search for public repos that import or require it, classifies each repo as company org, affiliated developer, solo developer, or tutorial noise…. SDK Adoption Tracker is an agent skill from Varnan-Tech/opendirectory. Given your SDK or library name, searches GitHub code search for public repos that import or require it, classifies each repo as company org, affiliated developer, solo developer, or tutorial noise, scores by adoption signal strength, detects new adopters by date, and outputs a ranked list of who is building on you with outreach context per high-signal company.
SDK Adoption Tracker fits situations like: asked to find who uses your SDK; track SDK adoption; find companies building on your library; identify warm leads from existing SDK users.
Run `npx skills add Varnan-Tech/opendirectory --skill sdk-adoption-tracker -a claude-code`. Or copy the skill folder (skills/sdk-adoption-tracker in Varnan-Tech/opendirectory) into .claude/skills/sdk-adoption-tracker in your project. Claude Code loads it when a task matches its description.
Run `npx skills add Varnan-Tech/opendirectory --skill sdk-adoption-tracker -a codex`. Or copy the skill folder (skills/sdk-adoption-tracker in Varnan-Tech/opendirectory) into .agents/skills/sdk-adoption-tracker in your project. Codex loads it when a task matches its description.
Cursor, Gemini CLI, GitHub Copilot and OpenCode also load SKILL.md folders. With the skills CLI, run `npx skills add Varnan-Tech/opendirectory --skill sdk-adoption-tracker -a cursor` (or -a gemini-cli, github-copilot or opencode for the others). To copy it by hand, put the folder in .cursor/skills/sdk-adoption-tracker, .gemini/skills/sdk-adoption-tracker, .github/skills/sdk-adoption-tracker and .opencode/skills/sdk-adoption-tracker in your project.
Going by SKILL.md and its folder, SDK Adoption Tracker needs Python for the scripts in its folder, the command-line tools its instructions call (python3 and curl) and credentials named GITHUB_TOKEN. Our summary lists: Python 3; A credential in GITHUB_TOKEN. Compatibility (from SKILL.md): ["claude-code","gemini-cli","github-copilot"].
SKILL.md names 2 domains. In commands or code: api.github.com and github.com; the agent is likely to contact these when it follows the instructions. This is read from the text; nothing was executed.
Our automated static check of SKILL.md found no risky patterns, such as piping downloads into a shell, reading credential files or hidden Unicode. It is not a guarantee. The check reads SKILL.md only: the scripts in the folder are not scanned, so read them before running anything.
SDK Adoption Tracker is published under the MIT licence (the repository's licence). It allows redistribution, so the full SKILL.md is shown on this page.
About 7.7k tokens (SKILL.md is roughly 31k characters). Agents keep only the skill's name and description in context until a task matches; then they load SKILL.md in full. Its references folder adds about 2.5k tokens, read only when the agent opens those files.
Skills that share tags, products or a category with SDK Adoption Tracker: GitDiagram Repository Overview (ahmedkhaleel2004/gitdiagram, 18k stars), GitDiagram Repo Architecture (ahmedkhaleel2004/gitdiagram, 18k stars), Octocode Code Research (bgauryy/octocode, 949 stars) and Release (yoanbernabeu/grepai, 1.9k stars). The comparison table on this page puts their stars, adoption, token cost, safety result and licence side by side.
Varnan-Tech (a GitHub organization) maintains it in Varnan-Tech/opendirectory, which has 674 GitHub stars. The repository holds 61 skills in this directory. The repository was last updated on August 16, 2026.
Source: Varnan-Tech/opendirectory on GitHub. Facts on this page come from the repository at the commit we read; the author's words are quoted as theirs.