Writing Livekit Scenarios
livekit-examples/agent-starter-python
Creates and maintains the scenarios a LiveKit agent simulation runs, and wires the agent to consume them.
Implement Customer.io load testing and horizontal scaling. An agent skill from jeremylongshore/tons-of-skills-marketplace.
$ npx skills add jeremylongshore/tons-of-skills-marketplace --skill customerio-load-scale -a claude-codeProject install by default; add -g for ~/.claude/skills/.
$ gh skill install jeremylongshore/tons-of-skills-marketplace customerio-load-scale --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/jeremylongshore/tons-of-skills-marketplace.git skills-src && mkdir -p .claude/skills && cp -r skills-src/skills/.curated/customerio-load-scale .claude/skills/customerio-load-scale && 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 "customerio-load-scale" agent skill from https://github.com/jeremylongshore/tons-of-skills-marketplace/tree/main/skills/.curated/customerio-load-scale into .claude/skills/customerio-load-scale/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "customerio-load-scale", 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/jeremylongshore/tons-of-skills-marketplace/tree/main/skills/.curated/customerio-load-scaleType 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 jeremylongshore/tons-of-skills-marketplace --skill customerio-load-scale -a codexProject install goes to .agents/skills/; add -g for ~/.codex/skills/.
$ gh skill install jeremylongshore/tons-of-skills-marketplace customerio-load-scale --agent codexProject scope by default (.agents/skills/); add --scope user for a personal install.
$ git clone --depth 1 https://github.com/jeremylongshore/tons-of-skills-marketplace.git skills-src && mkdir -p .agents/skills && cp -r skills-src/skills/.curated/customerio-load-scale .agents/skills/customerio-load-scale && rm -rf skills-srcUse ~/.agents/skills/ instead of .agents/skills for a personal install.
Codex skills documentation · loads skills from .agents/skills/
Install the "customerio-load-scale" agent skill from https://github.com/jeremylongshore/tons-of-skills-marketplace/tree/main/skills/.curated/customerio-load-scale into .agents/skills/customerio-load-scale/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "customerio-load-scale", 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 jeremylongshore/tons-of-skills-marketplace --skill customerio-load-scale -a cursorProject install goes to .agents/skills/; add -g for ~/.cursor/skills/.
$ gh skill install jeremylongshore/tons-of-skills-marketplace customerio-load-scale --agent cursorProject scope by default (.agents/skills/); add --scope user for a personal install.
$ git clone --depth 1 https://github.com/jeremylongshore/tons-of-skills-marketplace.git skills-src && mkdir -p .cursor/skills && cp -r skills-src/skills/.curated/customerio-load-scale .cursor/skills/customerio-load-scale && 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 "customerio-load-scale" agent skill from https://github.com/jeremylongshore/tons-of-skills-marketplace/tree/main/skills/.curated/customerio-load-scale into .cursor/skills/customerio-load-scale/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "customerio-load-scale", 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/jeremylongshore/tons-of-skills-marketplace.git --path skills/.curated/customerio-load-scale--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 jeremylongshore/tons-of-skills-marketplace --skill customerio-load-scale -a gemini-cliProject install goes to .agents/skills/; add -g for ~/.gemini/skills/.
$ gh skill install jeremylongshore/tons-of-skills-marketplace customerio-load-scale --agent gemini-cliProject scope by default (.agents/skills/); add --scope user for a personal install.
$ git clone --depth 1 https://github.com/jeremylongshore/tons-of-skills-marketplace.git skills-src && mkdir -p .gemini/skills && cp -r skills-src/skills/.curated/customerio-load-scale .gemini/skills/customerio-load-scale && 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 "customerio-load-scale" agent skill from https://github.com/jeremylongshore/tons-of-skills-marketplace/tree/main/skills/.curated/customerio-load-scale into .gemini/skills/customerio-load-scale/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "customerio-load-scale", 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 jeremylongshore/tons-of-skills-marketplace customerio-load-scaleInstalls 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 jeremylongshore/tons-of-skills-marketplace --skill customerio-load-scale -a github-copilotProject install goes to .agents/skills/; add -g for ~/.copilot/skills/.
$ git clone --depth 1 https://github.com/jeremylongshore/tons-of-skills-marketplace.git skills-src && mkdir -p .github/skills && cp -r skills-src/skills/.curated/customerio-load-scale .github/skills/customerio-load-scale && 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 "customerio-load-scale" agent skill from https://github.com/jeremylongshore/tons-of-skills-marketplace/tree/main/skills/.curated/customerio-load-scale into .github/skills/customerio-load-scale/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "customerio-load-scale", 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 jeremylongshore/tons-of-skills-marketplace --skill customerio-load-scale -a opencodeOpenCode documents no install command of its own. Project install goes to .agents/skills/; add -g for ~/.config/opencode/skills/.
$ gh skill install jeremylongshore/tons-of-skills-marketplace customerio-load-scale --agent opencodeProject scope by default (.agents/skills/); add --scope user for a personal install.
$ git clone --depth 1 https://github.com/jeremylongshore/tons-of-skills-marketplace.git skills-src && mkdir -p .opencode/skills && cp -r skills-src/skills/.curated/customerio-load-scale .opencode/skills/customerio-load-scale && 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 "customerio-load-scale" agent skill from https://github.com/jeremylongshore/tons-of-skills-marketplace/tree/main/skills/.curated/customerio-load-scale into .opencode/skills/customerio-load-scale/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "customerio-load-scale", 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.
customerio-load-scaleImplement Customer.io load testing and horizontal scaling. An agent skill from jeremylongshore/tons-of-skills-marketplace.
Customerio Load Scale is an agent skill from jeremylongshore/tons-of-skills-marketplace. Implement Customer.io load testing and horizontal scaling. Use when preparing for high traffic, running load tests, or designing queue-based architectures for scale. Trigger: "customer.io load test", "customer.io scale", "customer.io high volume", "customer.io k6", "customer.io performance test".
Its SKILL.md is about 2.5k tokens, which your agent loads only when the skill is triggered. The skill folder holds 2 other files, including reference files (for example `references/implementation-guide.md`). Compatibility notes: Designed for Claude Code
It sits in Testing & QA, covering Load testing. The repository describes itself as: Model-agnostic agent-skills platform with a harness-free canonical layer, verified adapters, and the ccpi package manager. Explore at tonsofskills.com. The licence is MIT.
4 steps, taken from the step headings in SKILL.md.
Read from SKILL.md and the folder at commit cfae287. It shows what the files ask for, not the result of running them.
Pre-approves these tools, so the agent can use them without asking each time:
ReadWriteEditBash(npm:*)Bash(npx:*)Bash(kubectl:*)GlobGrepFrom allowed-tools in the SKILL.md frontmatter.
Shell commands in SKILL.md call:
npmFrom 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:
track.customer.ioAlso links to:
k6.ionpmjs.combullmq.iokubernetes.ioFrom URLs in SKILL.md, links to its own repository left out.
Names these keys or tokens, usually read from environment variables:
CUSTOMERIO_TRACK_API_KEYAPI_KEYFrom names ending in _API_KEY, _TOKEN, _SECRET, _KEY or _PASSWORD in SKILL.md.
Designed for Claude Code
From compatibility in the SKILL.md frontmatter.
Customerio Load Scale loads about 2.5k tokens when it runs, and up to ~4.9k if it reads all its reference files. Until then it costs about 80 tokens; SKILL.md has 325 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); files beside SKILL.md are not scanned.
The full file from jeremylongshore/tons-of-skills-marketplace at commit cfae287, republished under its MIT licence (© jeremylongshore). 325 words, ~2,536 tokens.
.claude/skills/customerio-load-scale/SKILL.md (or your agent's skills folder). This skill also uses 1 other file; get the full folder from GitHub.Run a staged load test using synthetic profiles and fixed idempotency keys, gradually increase only within the provider limit, and record throughput, 429s, queue age, and processing errors. Stop and reduce load on error/ordering regression; never use a live recipient list as a load-test fixture.
Load testing and scaling strategies for high-volume Customer.io integrations: k6 load test scripts, scaling architecture selection based on volume tier, Kubernetes HPA autoscaling, message queue buffering, and rate-limit-aware batch processing.
| Daily Events | Architecture | Key Components |
|---|---|---|
| < 100K | Direct API | Singleton client, retry, connection pooling |
| 100K - 1M | Batched API | Event queue, batch processor, rate limiter |
| 1M - 10M | Queue-backed | Redis/Kafka queue, worker pool, backpressure |
| > 10M | Distributed | Multiple workspaces, sharded queues, regional routing |
Customer.io rate limit is ~100 req/sec per workspace. Plan your architecture around this.
// load-tests/customerio.js
// Run: k6 run --vus 10 --duration 60s load-tests/customerio.js
import http from "k6/http";
import { check, sleep } from "k6";
import { Counter, Trend } from "k6/metrics";
const SITE_ID = __ENV.CUSTOMERIO_SITE_ID;
const API_KEY = __ENV.CUSTOMERIO_TRACK_API_KEY;
const BASE_URL = "https://track.customer.io/api/v1";
const AUTH = `${SITE_ID}:${API_KEY}`;
const identifyLatency = new Trend("cio_identify_latency");
const trackLatency = new Trend("cio_track_latency");
const errors = new Counter("cio_errors");
export const options = {
scenarios: {
identify_load: {
executor: "ramping-arrival-rate",
startRate: 10,
timeUnit: "1s",
preAllocatedVUs: 20,
maxVUs: 50,
stages: [
{ duration: "30s", target: 50 }, // Ramp to 50/sec
{ duration: "60s", target: 80 }, // Hold at 80/sec (near limit)
{ duration: "30s", target: 10 }, // Cool down
],
},
},
thresholds: {
cio_identify_latency: ["p(95)<500", "p(99)<2000"],
cio_track_latency: ["p(95)<500", "p(99)<2000"],
cio_errors: ["count<50"],
},
};
export default function () {
const userId = `k6-load-${__VU}-${__ITER}`;
const headers = {
"Content-Type": "application/json",
Authorization: `Basic ${encoding.b64encode(AUTH)}`,
};
// Identify
const identifyRes = http.put(
`${BASE_URL}/customers/${userId}`,
JSON.stringify({
email: `${userId}@loadtest.example.com`,
_load_test: true,
created_at: Math.floor(Date.now() / 1000),
}),
{ headers }
);
identifyLatency.add(identifyRes.timings.duration);
check(identifyRes, { "identify 200": (r) => r.status === 200 }) || errors.add(1);
// Track event
const trackRes = http.post(
`${BASE_URL}/customers/${userId}/events`,
JSON.stringify({
name: "load_test_event",
data: { iteration: __ITER, vu: __VU },
}),
{ headers }
);
trackLatency.add(trackRes.timings.duration);
check(trackRes, { "track 200": (r) => r.status === 200 }) || errors.add(1);
sleep(0.1); // Small delay between iterations
}
// Cleanup function — suppress test users after test
export function teardown() {
console.log("Load test complete. Clean up k6-load-* users in CIO dashboard.");
}Run:
k6 run --env CUSTOMERIO_SITE_ID="$CUSTOMERIO_SITE_ID" \
--env CUSTOMERIO_TRACK_API_KEY="$CUSTOMERIO_TRACK_API_KEY" \
load-tests/customerio.js// services/cio-queue-worker.ts
import { Queue, Worker, QueueEvents } from "bullmq";
import { TrackClient, RegionUS } from "customerio-node";
import Bottleneck from "bottleneck";
const REDIS_URL = process.env.REDIS_URL ?? "redis://localhost:6379";
// Rate limiter: 80 requests per second (leave headroom under 100/sec limit)
const limiter = new Bottleneck({
maxConcurrent: 15,
reservoir: 80,
reservoirRefreshAmount: 80,
reservoirRefreshInterval: 1000,
});
const eventQueue = new Queue("cio:events", {
connection: { url: REDIS_URL },
defaultJobOptions: {
attempts: 5,
backoff: { type: "exponential", delay: 2000 },
removeOnComplete: { count: 10000 },
removeOnFail: { count: 50000 },
},
});
// Producer — your application enqueues events here
export async function enqueueEvent(
type: "identify" | "track",
userId: string,
data: Record<string, any>
): Promise<void> {
await eventQueue.add(type, { userId, data, enqueuedAt: Date.now() });
}
// Consumer — workers process events with rate limiting
export function startEventWorkers(concurrency = 10): void {
const cio = new TrackClient(
process.env.CUSTOMERIO_SITE_ID!,
process.env.CUSTOMERIO_TRACK_API_KEY!,
{ region: RegionUS }
);
const worker = new Worker(
"cio:events",
async (job) => {
await limiter.schedule(async () => {
if (job.name === "identify") {
await cio.identify(job.data.userId, job.data.data);
} else {
await cio.track(job.data.userId, job.data.data);
}
});
},
{
connection: { url: REDIS_URL },
concurrency,
}
);
worker.on("failed", (job, err) => {
console.error(`CIO event failed: ${job?.id} — ${err.message}`);
});
// Monitor queue health
const events = new QueueEvents("cio:events", {
connection: { url: REDIS_URL },
});
setInterval(async () => {
const counts = await eventQueue.getJobCounts();
console.log(
`CIO queue: waiting=${counts.waiting} active=${counts.active} ` +
`failed=${counts.failed} completed=${counts.completed}`
);
}, 30000);
}# k8s/hpa.yaml
apiVersion: autoscaling/v2
kind: HorizontalPodAutoscaler
metadata:
name: cio-worker-hpa
spec:
scaleTargetRef:
apiVersion: apps/v1
kind: Deployment
name: cio-event-worker
minReplicas: 2
maxReplicas: 20
metrics:
- type: Resource
resource:
name: cpu
target:
type: Utilization
averageUtilization: 70
- type: Pods
pods:
metric:
name: cio_queue_depth
target:
type: AverageValue
averageValue: "500"
behavior:
scaleUp:
stabilizationWindowSeconds: 60
policies:
- type: Pods
value: 4
periodSeconds: 60
scaleDown:
stabilizationWindowSeconds: 300
policies:
- type: Pods
value: 2
periodSeconds: 120// lib/cio-batch-sender.ts
import { TrackClient, RegionUS } from "customerio-node";
import Bottleneck from "bottleneck";
export async function batchSend(
operations: Array<{
type: "identify" | "track";
userId: string;
data: Record<string, any>;
}>,
ratePerSec = 80
): Promise<{ succeeded: number; failed: number }> {
const cio = new TrackClient(
process.env.CUSTOMERIO_SITE_ID!,
process.env.CUSTOMERIO_TRACK_API_KEY!,
{ region: RegionUS }
);
const limiter = new Bottleneck({
maxConcurrent: 15,
reservoir: ratePerSec,
reservoirRefreshAmount: ratePerSec,
reservoirRefreshInterval: 1000,
});
let succeeded = 0;
let failed = 0;
const promises = operations.map((op, i) =>
limiter.schedule(async () => {
try {
if (op.type === "identify") {
await cio.identify(op.userId, op.data);
} else {
await cio.track(op.userId, op.data);
}
succeeded++;
} catch {
failed++;
}
if ((succeeded + failed) % 1000 === 0) {
console.log(`Progress: ${succeeded + failed}/${operations.length}`);
}
})
);
await Promise.all(promises);
return { succeeded, failed };
}Install: npm install bottleneck bullmq
| Issue | Solution |
|---|---|
| 429 during load test | Reduce rate, check limiter config |
| Queue backlog growing | Scale workers, increase concurrency |
| Memory pressure | Limit batch and queue sizes, enable GC |
| k6 VU exhaustion | Increase preAllocatedVUs and maxVUs |
After load testing, proceed to customerio-known-pitfalls for anti-patterns to avoid.
© jeremylongshore, 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 1 other file (references) in skills/.curated/customerio-load-scale of jeremylongshore/tons-of-skills-marketplace.
Open the folder on GitHubat commit cfae287
Customerio Load Scale 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 |
|---|---|---|---|---|---|---|
| Customerio Load Scale this skilljeremylongshore/tons-of-skills-marketplace | 2.8k | — | ~2.5k | Automated safety check: Pass | MIT | |
| Writing Livekit Scenarioslivekit-examples/agent-starter-python | 264 | 1 repos | ~2.5k | Automated safety check: Pass | MIT | |
| Go Testingcxuu/golang-skills | 173 | 1 repos | ~1.3k | Automated safety check: Pass | Apache-2.0 | |
| Goalcraftgrp06/goalcraft | 102 | — | ~3.8k | Automated safety check: Pass | MIT | |
| Thinking Partnermattnowdev/thinking-partner | 206 | — | ~4.4k | Automated safety check: Pass | MIT | |
| Visionkunchenguid/vision | 331 | — | ~2.9k | Automated safety check: Pass | MIT |
livekit-examples/agent-starter-python
Creates and maintains the scenarios a LiveKit agent simulation runs, and wires the agent to consume them.
cxuu/golang-skills
A skill your agent uses when writing, reviewing, or improving Go test code — including table-driven tests, subtests, parallel tests, test helpers, test doubles, and assertions with cmp.Diff.
grp06/goalcraft
Turn a rough draft, vague ambition, or messy task brief into a powerful Codex /goal objective for persistent, evidence-checked work.
mattnowdev/thinking-partner
A deterministic thinking partner that challenges assumptions and applies mental models to sharpen decisions, solve problems, and think more clearly.
kunchenguid/vision
Draft and stress-test a VISION.md for a repository, then iterate with the author on an interactive review board until approved.
owenHochwald/volt
Safely exercise and evaluate HTTP APIs with the Volt CLI, including authenticated requests, JSON bodies, staged load, machine-readable results, performance baselines, and before/after comparisons.
jeremylongshore/tons-of-skills-marketplace
Execute this skill enables AI assistant to conduct a security-focused code review using the security-agent plugin.
jeremylongshore/tons-of-skills-marketplace
Build this skill automates the adaptation of pre-trained machine learning models using transfer learning techniques.
jeremylongshore/tons-of-skills-marketplace
Execute proactive auto-loading: automatically detects and loads agents.md files.
jeremylongshore/tons-of-skills-marketplace
Aggregate and centralize performance metrics from applications, systems, databases, caches, and services.
jeremylongshore/tons-of-skills-marketplace
Execute this skill enables AI assistant to analyze capacity requirements and plan for future growth.
jeremylongshore/tons-of-skills-marketplace
Process use when you need to work with database indexing. An agent skill from jeremylongshore/tons-of-skills-marketplace.
Categories
Implement Customer.io load testing and horizontal scaling. An agent skill from jeremylongshore/tons-of-skills-marketplace. Customerio Load Scale is an agent skill from jeremylongshore/tons-of-skills-marketplace.io load testing and horizontal scaling.
Customerio Load Scale fits situations like: preparing for high traffic; running load tests; designing queue-based architectures for scale.
Run `npx skills add jeremylongshore/tons-of-skills-marketplace --skill customerio-load-scale -a claude-code`. Or copy the skill folder (skills/.curated/customerio-load-scale in jeremylongshore/tons-of-skills-marketplace) into .claude/skills/customerio-load-scale in your project. Claude Code loads it when a task matches its description.
Run `npx skills add jeremylongshore/tons-of-skills-marketplace --skill customerio-load-scale -a codex`. Or copy the skill folder (skills/.curated/customerio-load-scale in jeremylongshore/tons-of-skills-marketplace) into .agents/skills/customerio-load-scale 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 jeremylongshore/tons-of-skills-marketplace --skill customerio-load-scale -a cursor` (or -a gemini-cli, github-copilot or opencode for the others). To copy it by hand, put the folder in .cursor/skills/customerio-load-scale, .gemini/skills/customerio-load-scale, .github/skills/customerio-load-scale and .opencode/skills/customerio-load-scale in your project.
Going by SKILL.md and its folder, Customerio Load Scale needs the command-line tools its instructions call (npm) and credentials named CUSTOMERIO_TRACK_API_KEY and API_KEY. Our summary lists: Node.js; A credential in API_KEY; A credential in CUSTOMERIO_TRACK_API_KEY. Its frontmatter pre-approves these tools: Read, Write, Edit, Bash(npm:*), Bash(npx:*), Bash(kubectl:*), Glob, Grep. Compatibility (from SKILL.md): Designed for Claude Code.
SKILL.md names 5 domains. In commands or code: track.customer.io; the agent is likely to contact it when it follows the instructions. As links in the text: k6.io, npmjs.com, bullmq.io and kubernetes.io. 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. Review the folder before installing.
Customerio Load Scale is published under the MIT licence (declared in SKILL.md). It allows redistribution, so the full SKILL.md is shown on this page.
About 2.5k tokens (SKILL.md is roughly 10k 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 2.3k tokens, read only when the agent opens those files.
Skills that share tags, products or a category with Customerio Load Scale: Writing Livekit Scenarios (livekit-examples/agent-starter-python, 264 stars), Go Testing (cxuu/golang-skills, 173 stars), Goalcraft (grp06/goalcraft, 102 stars) and Thinking Partner (mattnowdev/thinking-partner, 206 stars). The comparison table on this page puts their stars, adoption, token cost, safety result and licence side by side.
jeremylongshore (a GitHub user) maintains it in jeremylongshore/tons-of-skills-marketplace, which has 2,827 GitHub stars. The repository holds 3,342 skills in this directory. The repository was last updated on October 10, 2026.
Source: jeremylongshore/tons-of-skills-marketplace on GitHub. Facts on this page come from the repository at the commit we read; the author's words are quoted as theirs.