Agentsop Observability Setup
agentsope/SkillAlchemy
Enhancement-overlay skill — the DECISION + WIRING layer for LM observability that the single-backend skills [[langsmith]], [[phoenix]], [[mlflow]] do NOT cover.
Agent skill
by jeremylongshore in jeremylongshore/tons-of-skills-marketplace
Production-grade Langfuse architecture patterns and best practices.
$ npx skills add jeremylongshore/tons-of-skills-marketplace --skill langfuse-reference-architecture -a claude-codeProject install by default; add -g for ~/.claude/skills/.
$ gh skill install jeremylongshore/tons-of-skills-marketplace langfuse-reference-architecture --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/langfuse-reference-architecture .claude/skills/langfuse-reference-architecture && 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 "langfuse-reference-architecture" agent skill from https://github.com/jeremylongshore/tons-of-skills-marketplace/tree/main/skills/.curated/langfuse-reference-architecture into .claude/skills/langfuse-reference-architecture/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "langfuse-reference-architecture", 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/langfuse-reference-architectureType 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 langfuse-reference-architecture -a codexProject install goes to .agents/skills/; add -g for ~/.codex/skills/.
$ gh skill install jeremylongshore/tons-of-skills-marketplace langfuse-reference-architecture --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/langfuse-reference-architecture .agents/skills/langfuse-reference-architecture && rm -rf skills-srcUse ~/.agents/skills/ instead of .agents/skills for a personal install.
Codex skills documentation · loads skills from .agents/skills/
Install the "langfuse-reference-architecture" agent skill from https://github.com/jeremylongshore/tons-of-skills-marketplace/tree/main/skills/.curated/langfuse-reference-architecture into .agents/skills/langfuse-reference-architecture/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "langfuse-reference-architecture", 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 langfuse-reference-architecture -a cursorProject install goes to .agents/skills/; add -g for ~/.cursor/skills/.
$ gh skill install jeremylongshore/tons-of-skills-marketplace langfuse-reference-architecture --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/langfuse-reference-architecture .cursor/skills/langfuse-reference-architecture && 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 "langfuse-reference-architecture" agent skill from https://github.com/jeremylongshore/tons-of-skills-marketplace/tree/main/skills/.curated/langfuse-reference-architecture into .cursor/skills/langfuse-reference-architecture/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "langfuse-reference-architecture", 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/langfuse-reference-architecture--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 langfuse-reference-architecture -a gemini-cliProject install goes to .agents/skills/; add -g for ~/.gemini/skills/.
$ gh skill install jeremylongshore/tons-of-skills-marketplace langfuse-reference-architecture --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/langfuse-reference-architecture .gemini/skills/langfuse-reference-architecture && 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 "langfuse-reference-architecture" agent skill from https://github.com/jeremylongshore/tons-of-skills-marketplace/tree/main/skills/.curated/langfuse-reference-architecture into .gemini/skills/langfuse-reference-architecture/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "langfuse-reference-architecture", 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 langfuse-reference-architectureInstalls 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 langfuse-reference-architecture -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/langfuse-reference-architecture .github/skills/langfuse-reference-architecture && 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 "langfuse-reference-architecture" agent skill from https://github.com/jeremylongshore/tons-of-skills-marketplace/tree/main/skills/.curated/langfuse-reference-architecture into .github/skills/langfuse-reference-architecture/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "langfuse-reference-architecture", 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 langfuse-reference-architecture -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 langfuse-reference-architecture --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/langfuse-reference-architecture .opencode/skills/langfuse-reference-architecture && 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 "langfuse-reference-architecture" agent skill from https://github.com/jeremylongshore/tons-of-skills-marketplace/tree/main/skills/.curated/langfuse-reference-architecture into .opencode/skills/langfuse-reference-architecture/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "langfuse-reference-architecture", 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.
langfuse-reference-architectureProduction-grade Langfuse architecture patterns and best practices.
Langfuse Reference Architecture is an agent skill from jeremylongshore/tons-of-skills-marketplace. Production-grade Langfuse architecture patterns and best practices. Use when designing LLM observability infrastructure, planning Langfuse deployment, or implementing enterprise-grade tracing architecture. Trigger with phrases like "langfuse architecture", "langfuse design", "langfuse infrastructure", "langfuse enterprise", "langfuse at scale".
Its SKILL.md is about 2.6k 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.md`). Compatibility notes: Designed for Claude Code
It sits in AI & LLM Engineering, covering LLM observability. It works with Langfuse and OpenTelemetry. 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.
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:
ReadWriteEditFrom allowed-tools in the SKILL.md frontmatter.
No scripts in the folder and no shell commands in SKILL.md (its code samples are typescript).
From the folder's file list and the shell code blocks in SKILL.md.
Links to these hosts (documentation or services it may open):
langfuse.comopentelemetry.ioFrom URLs in SKILL.md, links to its own repository left out.
Names no API keys, tokens, secrets or passwords.
From names ending in _API_KEY, _TOKEN, _SECRET, _KEY or _PASSWORD in SKILL.md.
Designed for Claude Code
From compatibility in the SKILL.md frontmatter.
Langfuse Reference Architecture loads about 2.6k tokens when it runs, and up to ~3.8k if it reads all its reference files. Until then it costs about 95 tokens; SKILL.md has 321 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). 321 words, ~2,614 tokens.
.claude/skills/langfuse-reference-architecture/SKILL.md (or your agent's skills folder). This skill also uses 1 other file; get the full folder from GitHub.Production-grade architecture patterns for Langfuse LLM observability: singleton SDK, context propagation with AsyncLocalStorage, cross-service trace correlation, multi-environment configurations, and scale strategies.
@langfuse/tracing, @langfuse/otel, @opentelemetry/sdk-node| Tier | Scale | Architecture | Langfuse Host |
|---|---|---|---|
| Starter | < 100K traces/day | Direct SDK, Cloud | Langfuse Cloud |
| Growth | 100K-1M traces/day | Singleton + batching | Cloud or Self-hosted |
| Enterprise | 1M+ traces/day | Queue-buffered + sampling | Self-hosted (HA) |
// src/lib/tracing.ts -- Single module for all tracing
import { LangfuseClient } from "@langfuse/client";
import { LangfuseSpanProcessor } from "@langfuse/otel";
import { NodeSDK } from "@opentelemetry/sdk-node";
import { AsyncLocalStorage } from "async_hooks";
// Singleton OTel SDK
let sdk: NodeSDK | null = null;
export function initTracing() {
if (sdk) return sdk;
sdk = new NodeSDK({
spanProcessors: [
new LangfuseSpanProcessor({
exportIntervalMillis: 5000,
maxExportBatchSize: 50,
}),
],
});
sdk.start();
// Graceful shutdown
for (const signal of ["SIGTERM", "SIGINT"]) {
process.on(signal, async () => {
console.log(`Received ${signal}, flushing traces...`);
await sdk?.shutdown();
process.exit(0);
});
}
return sdk;
}
// Singleton client for non-tracing operations
let client: LangfuseClient | null = null;
export function getLangfuseClient(): LangfuseClient {
if (!client) client = new LangfuseClient();
return client;
}
// Request context for user/session tracking
interface RequestContext {
userId?: string;
sessionId?: string;
requestId: string;
}
const requestStore = new AsyncLocalStorage<RequestContext>();
export function getRequestContext(): RequestContext | undefined {
return requestStore.getStore();
}
export function runWithContext<T>(ctx: RequestContext, fn: () => T): T {
return requestStore.run(ctx, fn);
}// src/middleware/tracing.ts
import { startActiveObservation, updateActiveObservation } from "@langfuse/tracing";
import { runWithContext, getRequestContext } from "../lib/tracing";
import { randomUUID } from "crypto";
import type { Request, Response, NextFunction } from "express";
export function langfuseMiddleware() {
return (req: Request, res: Response, next: NextFunction) => {
const ctx = {
requestId: req.headers["x-request-id"]?.toString() || randomUUID(),
userId: req.headers["x-user-id"]?.toString(),
sessionId: req.headers["x-session-id"]?.toString(),
};
runWithContext(ctx, () => {
startActiveObservation(`${req.method} ${req.path}`, async () => {
updateActiveObservation({
input: {
method: req.method,
path: req.path,
query: req.query,
},
metadata: {
userId: ctx.userId,
sessionId: ctx.sessionId,
requestId: ctx.requestId,
},
});
// Capture response
const originalEnd = res.end.bind(res);
res.end = function (...args: any[]) {
updateActiveObservation({
output: { statusCode: res.statusCode },
});
return originalEnd(...args);
} as any;
next();
}).catch(next);
});
};
}
// Usage
import express from "express";
import { initTracing } from "./lib/tracing";
import { langfuseMiddleware } from "./middleware/tracing";
initTracing();
const app = express();
app.use(langfuseMiddleware());For microservices, propagate trace context via HTTP headers:
// Service A: Inject trace context into outbound requests
import { context, propagation } from "@opentelemetry/api";
async function callServiceB(data: any) {
const headers: Record<string, string> = {};
// OTel propagation injects traceparent header automatically
propagation.inject(context.active(), headers);
const response = await fetch("https://service-b.internal/api/process", {
method: "POST",
headers: {
"Content-Type": "application/json",
...headers, // Includes traceparent, tracestate
},
body: JSON.stringify(data),
});
return response.json();
}// Service B: Extract and continue trace context
import { context, propagation } from "@opentelemetry/api";
import { startActiveObservation, updateActiveObservation } from "@langfuse/tracing";
app.post("/api/process", async (req, res) => {
// OTel automatically extracts context from incoming headers
// when using standard HTTP instrumentation.
// Any startActiveObservation call will be a child of the extracted trace.
await startActiveObservation("service-b-process", async () => {
updateActiveObservation({ input: req.body });
const result = await processData(req.body);
updateActiveObservation({ output: result });
res.json(result);
});
});// src/config/langfuse.ts
type Environment = "development" | "staging" | "production";
const configs: Record<Environment, {
exportIntervalMillis: number;
maxExportBatchSize: number;
sampleRate: number;
}> = {
development: {
exportIntervalMillis: 1000, // Immediate visibility
maxExportBatchSize: 1,
sampleRate: 1.0, // Trace everything
},
staging: {
exportIntervalMillis: 5000,
maxExportBatchSize: 25,
sampleRate: 0.5, // 50% sampling
},
production: {
exportIntervalMillis: 10000,
maxExportBatchSize: 100,
sampleRate: 0.1, // 10% sampling
},
};
// Pass the selected environment from the application's configuration boundary.
// Keeping configuration resolution outside tracing makes this module deterministic
// and straightforward to test.
export function getTracingConfig(env: Environment = "development") {
return configs[env] || configs.development;
}When Langfuse is unavailable, the app must keep running:
// The v4+ SDK with OTel handles this gracefully:
// - Failed exports are logged but don't throw
// - Events are buffered in the queue
// - Queue drops oldest events when maxQueueSize is exceeded
//
// For additional safety at the application level:
import { observe, updateActiveObservation } from "@langfuse/tracing";
let tracingHealthy = true;
let consecutiveFailures = 0;
const MAX_FAILURES = 10;
export function safeTrace<T extends (...args: any[]) => Promise<any>>(
name: string,
fn: T
): T {
return (async (...args: Parameters<T>) => {
if (!tracingHealthy) {
return fn(...args); // Circuit breaker open
}
try {
const result = await observe({ name }, async () => {
updateActiveObservation({ input: args });
const r = await fn(...args);
updateActiveObservation({ output: r });
return r;
})();
consecutiveFailures = 0;
return result;
} catch (error) {
consecutiveFailures++;
if (consecutiveFailures >= MAX_FAILURES) {
tracingHealthy = false;
console.error("Langfuse tracing disabled (circuit breaker open)");
// Re-enable after 5 minutes
setTimeout(() => { tracingHealthy = true; consecutiveFailures = 0; }, 300000);
}
return fn(...args);
}
}) as T;
}| Decision | Starter | Growth | Enterprise |
|---|---|---|---|
| Langfuse host | Cloud | Cloud or Self-hosted | Self-hosted (HA) |
| SDK version | v4+ | v4+ | v4+ with custom processor |
| Sampling | 100% | 50-100% | 5-20% + error always |
| Context propagation | Not needed | AsyncLocalStorage | OTel + HTTP headers |
| Queue buffer | SDK internal | SDK internal | External (SQS/Kafka) |
| Failover | None | Log-and-continue | Circuit breaker |
| Issue | Cause | Solution |
|---|---|---|
| Multiple SDK instances | No singleton | Centralize in tracing.ts module |
| Lost traces on deploy | No SIGTERM handler | Register shutdown handler |
| Cross-service trace gaps | No context propagation | Inject OTel traceparent header |
| Scale bottleneck | Direct SDK at high volume | Add queue buffer or increase sampling |
Produce an architecture decision record identifying the selected deployment tier, tracing boundary, context-propagation method, failure mode, retention owner, and rollback path. Include the tested revision and state whether the evidence comes from a local, staging, or production-like environment.
A growth-stage service can keep the SDK's internal queue and add AsyncLocalStorage propagation, then test that a request and downstream worker share the trace context. An enterprise deployment can put a queue between the application and self-hosted Langfuse, trip the circuit breaker during an export failure drill, and prove application traffic continues while telemetry recovers.
© 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/langfuse-reference-architecture of jeremylongshore/tons-of-skills-marketplace.
Open the folder on GitHubat commit cfae287
Langfuse Reference Architecture 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 |
|---|---|---|---|---|---|---|
| Langfuse Reference Architecture this skilljeremylongshore/tons-of-skills-marketplace | 2.8k | — | ~2.6k | Automated safety check: Pass | MIT | |
| Agentsop Observability Setupagentsope/SkillAlchemy | 436 | — | ~4.4k | Automated safety check: Pass | MIT | |
| Olore Langfuse Latestolorehq/olore | 104 | — | ~1.2k | Automated safety check: Pass | MIT | |
| Telemetry AnalyzerIBM/ibm-watsonx-orchestrate-adk | 178 | — | ~10k | Automated safety check: Notes | MIT | |
| Ak Dev New Tracing Provideryaalalabs/agent-kernel | 192 | — | ~3.5k | Automated safety check: Pass | Apache-2.0 | |
| Backend Dev Guidelineslangfuse/langfuse | 36k | — | ~1.9k | Automated safety check: Pass | Custom licence |
agentsope/SkillAlchemy
Enhancement-overlay skill — the DECISION + WIRING layer for LM observability that the single-backend skills [[langsmith]], [[phoenix]], [[mlflow]] do NOT cover.
olorehq/olore
Local Langfuse documentation reference (latest). An agent skill from olorehq/olore.
IBM/ibm-watsonx-orchestrate-adk
A skill your agent uses when the user wants to analyze agent telemetry traces to find bugs and get fix recommendations — walks through exporting traces from a local or remote watsonx Orchestrate…
yaalalabs/agent-kernel
Step-by-step guide for adding a new observability/tracing provider to Agent Kernel.
langfuse/langfuse
Build or review Langfuse backend code. An agent skill from langfuse/langfuse.
ag2ai/build-with-ag2
Add OpenTelemetry traces to an AG2 beta Agent via TelemetryMiddleware (autogen.beta.middleware.builtin).
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.
Works with
Categories
Production-grade Langfuse architecture patterns and best practices. Langfuse Reference Architecture is an agent skill from jeremylongshore/tons-of-skills-marketplace. Production-grade Langfuse architecture patterns and best practices.
Langfuse Reference Architecture fits situations like: designing LLM observability infrastructure; planning Langfuse deployment; implementing enterprise-grade tracing architecture; with phrases like langfuse architecture.
Run `npx skills add jeremylongshore/tons-of-skills-marketplace --skill langfuse-reference-architecture -a claude-code`. Or copy the skill folder (skills/.curated/langfuse-reference-architecture in jeremylongshore/tons-of-skills-marketplace) into .claude/skills/langfuse-reference-architecture in your project. Claude Code loads it when a task matches its description.
Run `npx skills add jeremylongshore/tons-of-skills-marketplace --skill langfuse-reference-architecture -a codex`. Or copy the skill folder (skills/.curated/langfuse-reference-architecture in jeremylongshore/tons-of-skills-marketplace) into .agents/skills/langfuse-reference-architecture 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 langfuse-reference-architecture -a cursor` (or -a gemini-cli, github-copilot or opencode for the others). To copy it by hand, put the folder in .cursor/skills/langfuse-reference-architecture, .gemini/skills/langfuse-reference-architecture, .github/skills/langfuse-reference-architecture and .opencode/skills/langfuse-reference-architecture in your project.
SKILL.md names no scripts, command-line tools or credentials: Langfuse Reference Architecture is instructions for the agent only. Our summary lists: Node.js. Its frontmatter pre-approves these tools: Read, Write, Edit. Compatibility (from SKILL.md): Designed for Claude Code.
SKILL.md names 2 domains. As links in the text: langfuse.com and opentelemetry.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.
Langfuse Reference Architecture is published under the MIT licence (declared in SKILL.md). It allows redistribution, so the full SKILL.md is shown on this page.
About 2.6k 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 1.2k tokens, read only when the agent opens those files.
Skills that share tags, products or a category with Langfuse Reference Architecture: Agentsop Observability Setup (agentsope/SkillAlchemy, 436 stars), Olore Langfuse Latest (olorehq/olore, 104 stars), Telemetry Analyzer (IBM/ibm-watsonx-orchestrate-adk, 178 stars) and Ak Dev New Tracing Provider (yaalalabs/agent-kernel, 192 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.