clade-webhooks-events

A model-agnostic agent-skills platform.

审核状态：已审核Quality 72Security 70

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项目 README

来源文件：README.md

抓取于 2026年8月28日

Tons of Skills

A model-agnostic agent-skills platform. The canonical layer is harness-free by construction; Claude Code is currently the verified-native harness. Other harnesses remain engineering candidates until their native-path integration is verified; source research alone is never presented as public support.

Version semantics: the release badge is this marketplace's display version. npm packages, including the ccpi CLI and publishable plugins, retain their own package versions; they are intentionally not expected to equal the display version. The version-surface checker governs the display surfaces without rewriting package semver.

Install

Inside Claude Code, one command installs the whole marketplace:

/plugin marketplace add jeremylongshore/claude-code-plugins

Or use the CLI:

pnpm add -g @intentsolutionsio/ccpi
ccpi install devops-automation-pack

Browse the marketplace · Explore plugins · Download bundles

Killer Skill of the Week — no-ai-slop by Peter Yang

Strip AI slop from any draft — named-pattern edits that keep the writer's real voice

no-ai-slop does two jobs and refuses to fake a third. In Edit mode it makes the minimum effective edit — cutting throat-clearing, weak verbs, and abstract nouns while deliberately preserving the writer's cadence, bluntness, humor, and honest admissions, so a rough draft still sounds like the same person afterward. In Detect mode it names each AI-slop pattern it finds, quotes the offending line, and gives the fix in a few words — and pointedly does NOT score the draft or guess whether an AI wrote it. That restraint is the whole point: AI detectors guess; named patterns are evidence the reader can check. MIT-licensed, single focused skill, actively maintained by Peter Yang.

"AI detectors guess. Named patterns are evidence the user can check." — Peter Yang

Grade: A | Week of July 22, 2026 (W30) | View on GitHub

Previous picks: tonone, mnemos, databricks-pack, kobiton-automate, skyvern, code-cleanup, web-analytics, token-optimizer, executive-assistant-skills, skill-creator, cursor-pack, crypto-portfolio-tracker. See all at tonsofskills.com.

Scale, labeled

Every number below names the cohort it counts and the command that reproduces it — an unlabeled count is how a corpus ends up with five contradictory answers to "how many skills."

Count	Cohort	Reproduce with
442	catalog plugins (catalog-entry cohort)	`node scripts/generate-readme-toc.mjs` over `marketplace.extended.json`
3,067	marketplace-visible skills (distinct)	`node -e "import('./scripts/corpus-resolver.mjs').then(m=>console.log(m.resolveCorpus('marketplace-visible').length))"`
347	agent definitions in plugins	`git ls-files 'plugins/*' \| grep '/agents/.\.md'`
19	plugin categories	`ls -d plugins/*/`

📦 Live npm Downloads

Across 396 published packages in the claude-code-plugins namespace. Updated daily by GitHub Actions.

Window	All packages	Established (>30d)
Last 24 hours	962	962
Last 7 days	2,920	2,916
Last 30 days	12,868	12,779

_{"Established" excludes packages first published within the last 30 days, so a bulk-publish event doesn't dominate the headline.}

Top 10 by last 30 days:

#	Package	Last 30d
1	`@intentsolutionsio/openrouter-pack`	556
2	`@intentsolutionsio/groq-pack`	496
3	`@intentsolutionsio/databricks-pack`	274
4	`@intentsolutionsio/clickhouse-pack`	273
5	`@intentsolutionsio/wallet-security-auditor`	263
6	`@intentsolutionsio/notion-pack`	258
7	`@intentsolutionsio/elevenlabs-pack`	244
8	`@intentsolutionsio/freshie-inventory-manager`	214
9	`@intentsolutionsio/supabase-pack`	210
10	`@intentsolutionsio/agency-os`	204

_{Last refreshed 2026-08-19T03:03:05.709Z.}

Ways in

Five real questions, five doors — each resolves to a live, generated surface, never a hand-maintained list:

By category — the table below, regenerated from the catalog on every sync.
By plugin — tonsofskills.com/explore, the full browsable catalog.
By skill — tonsofskills.com/skills, searchable across the whole corpus.
By job to be done — tonsofskills.com/cowork, curated bundles as one-click downloads.
By certification tier — the Certification section below, rendered from the live report.

Browse by category

The 19 categories below link into the live marketplace. Plugin counts are the catalog-entry cohort — regenerated from marketplace.extended.json by this generator; the catalog itself lives on tonsofskills.com, never in this file (§ 6A of the platform blueprint).

	Category	Plugins
🤖	AI & Machine Learning	36
🎭	AI Agents & Agency	10
🔌	API Development	26
💼	Business Tools	6
👥	Community	21
₿	Crypto & Web3	27
💾	Database	26
🎨	Design	2
🔧	DevOps & Infrastructure	36
📚	Examples & Templates	5
🧩	MCP Servers	16
📦	Packages	5
⚡	Performance	25
✅	Productivity	30
🎁	SaaS Skill Packs	106
🔐	Security	27
✨	Skill Enhancers	9
🧪	Testing	28
📁	Analytics	1

What the classes mean

Four artifact classes live in this repository, distinguished on sight and never blurred — provenance is a truth requirement here, not a UX nicety:

Class	What it is	How the reader can tell
Canonical skill	First-party, harness-free, the source of truth	No `.source.json` in its plugin directory
Generated adapter	A thin, machine-produced harness projection	Lives under a generated path with a "generated — do not edit" header
First-party package	An Intent Solutions distribution (npm, cowork zip)	`@intentsolutionsio` scope, IS-authored license
Upstream mirror	Somebody else's work, hosted mirror-by-default	`.source.json` present — upstream author, license, and pinned commit recorded

Certification

Not yet certified. The certification program (tiers T0–T4 with retained, hash-matched evidence) is a later epic of the platform blueprint; until its report exists, no artifact on this surface claims a tier. This line is rendered from the absence of certification-report.json — honestly, not cosmetically.

Contribute

Start with the contribution guide, then the intake and review standards every submission passes through:

Contribution requirements — including the AI-assistance disclosure expectation.
Skill submission intake standard — the tiered document matrix new plugins ship with.
External-PR review standard — how maintainers triage and what gets a submission merged.

Governance

STANDARDS.md — the public spec posture and the canonical-documents index (one owner per fact class).
The platform master blueprint — CI gates, release, docs governance, and this README's own landing contract.
GOVERNANCE.md · SECURITY.md · LICENSE

Provenance

External plugins are hosted mirror-by-default: the contributor's repository stays the source of truth, every mirrored source is pinned in a content lockfile, and upstream credit — author, license, resolved commit — is recorded in the mirror itself. Improvements flow by upstreaming to the author's repository, never by silently editing the mirror. The full decision record is the external-sync model.

License

MIT for the repository scaffolding and first-party tooling; each plugin carries its own license in its manifest, and mirrored plugins keep their upstream license verbatim.

其他

中风险

来源需自行核对维护者身份。
包含脚本或命令调用，安装前请复核。
可能需要外部 token、网络权限或第三方服务。
未检测到高风险命令。
扫描发现：2 条。

Codex — Git Clone 安装

安装前请先查看来源仓库和风险报告。
克隆仓库：git clone https://github.com/jeremylongshore/tons-of-skills-marketplace.git
将 "skills/.curated/clade-webhooks-events" 文件夹复制到 Codex 的 skills 目录中。
重启 Codex 让新的 skill 生效。

Codex — 手动复制安装

安装前请先查看来源仓库和风险报告。
从源仓库下载 SKILL.md 及相关文件。
在 Codex 的 skills 目录中创建新文件夹。
将所有 skill 文件复制到新文件夹中。
重启 Codex 让新的 skill 生效。

Claude Code — Git Clone 安装

安装前请先查看来源仓库和风险报告。
克隆仓库：git clone https://github.com/jeremylongshore/tons-of-skills-marketplace.git
将 "skills/.curated/clade-webhooks-events" 文件夹复制到 Claude Code 的 skills 目录中。
重启 Claude Code 让新的 skill 生效。

Claude Code — 手动复制安装

安装前请先查看来源仓库和风险报告。
从源仓库下载 SKILL.md 及相关文件。
在 Claude Code 的 skills 目录中创建新文件夹。
将所有 skill 文件复制到新文件夹中。
重启 Claude Code 让新的 skill 生效。

Cursor — Git Clone 安装

安装前请先查看来源仓库和风险报告。
克隆仓库：git clone https://github.com/jeremylongshore/tons-of-skills-marketplace.git
将 "skills/.curated/clade-webhooks-events" 文件夹复制到 Cursor 的 skills 目录中。
重启 Cursor 让新的 skill 生效。

Cursor — 手动复制安装

安装前请先查看来源仓库和风险报告。
从源仓库下载 SKILL.md 及相关文件。
在 Cursor 的 skills 目录中创建新文件夹。
将所有 skill 文件复制到新文件夹中。
重启 Cursor 让新的 skill 生效。

GitHub Copilot — Git Clone 安装

安装前请先查看来源仓库和风险报告。
克隆仓库：git clone https://github.com/jeremylongshore/tons-of-skills-marketplace.git
将 "skills/.curated/clade-webhooks-events" 文件夹复制到 GitHub Copilot 的 skills 目录中。
重启 GitHub Copilot 让新的 skill 生效。

GitHub Copilot — 手动复制安装

安装前请先查看来源仓库和风险报告。
从源仓库下载 SKILL.md 及相关文件。
在 GitHub Copilot 的 skills 目录中创建新文件夹。
将所有 skill 文件复制到新文件夹中。
重启 GitHub Copilot 让新的 skill 生效。

Windsurf — Git Clone 安装

安装前请先查看来源仓库和风险报告。
克隆仓库：git clone https://github.com/jeremylongshore/tons-of-skills-marketplace.git
将 "skills/.curated/clade-webhooks-events" 文件夹复制到 Windsurf 的 skills 目录中。
重启 Windsurf 让新的 skill 生效。

Windsurf — 手动复制安装

安装前请先查看来源仓库和风险报告。
从源仓库下载 SKILL.md 及相关文件。
在 Windsurf 的 skills 目录中创建新文件夹。
将所有 skill 文件复制到新文件夹中。
重启 Windsurf 让新的 skill 生效。

查看 SKILL.md 原文

name: clade-webhooks-events
description: 'Use Anthropic Message Batches for async bulk processing and event handling.

  Use when working with webhooks-events patterns.

  Trigger with "anthropic batches", "claude batch api", "anthropic async",

  "bulk claude processing", "anthropic webhook".

  '
allowed-tools: Read, Write, Edit, Bash(curl:*)
version: 1.0.0
license: MIT
author: Jeremy Longshore <jeremy@intentsolutions.io>
tags:
- saas
- anthropic
- claude
- batches
- async
compatibility: Designed for Claude Code

Anthropic Message Batches & Async Processing

Overview

Anthropic doesn't have traditional webhooks. Instead, use Message Batches for async bulk processing — up to 10,000 requests per batch at 50% off, with a 24-hour processing SLA.

Prerequisites

Completed clade-install-auth
Multiple prompts/documents to process in bulk
Tolerance for async processing (results within 24 hours)

Instructions

Step 1: Create a Batch

import Anthropic from '@claude-ai/sdk';

const client = new Anthropic();

const batch = await client.messages.batches.create({
  requests: documents.map((doc, i) => ({
    custom_id: `doc-${i}`,
    params: {
      model: 'claude-sonnet-4-20250514',
      max_tokens: 1024,
      messages: [{ role: 'user', content: `Summarize: ${doc.text}` }],
    },
  })),
});

console.log(`Batch ${batch.id} created — ${batch.request_counts.processing} processing`);

Step 2: Poll for Completion

async function waitForBatch(batchId: string): Promise<Anthropic.Messages.MessageBatch> {
  while (true) {
    const batch = await client.messages.batches.retrieve(batchId);

    if (batch.processing_status === 'ended') {
      console.log(`Batch complete:
        Succeeded: ${batch.request_counts.succeeded}
        Errored: ${batch.request_counts.errored}
        Expired: ${batch.request_counts.expired}`);
      return batch;
    }

    console.log(`Processing... ${batch.request_counts.processing} remaining`);
    await new Promise(r => setTimeout(r, 30_000)); // Check every 30s
  }
}

Step 3: Retrieve Results

const results = await client.messages.batches.results(batch.id);

for await (const result of results) {
  if (result.result.type === 'succeeded') {
    const text = result.result.message.content[0].text;
    console.log(`${result.custom_id}: ${text.substring(0, 100)}...`);
  } else {
    console.error(`${result.custom_id}: ${result.result.type} — ${result.result.error?.message}`);
  }
}

Python Example

import anthropic
import time

client = anthropic.Anthropic()

batch = client.messages.batches.create(
    requests=[
        {
            "custom_id": f"doc-{i}",
            "params": {
                "model": "claude-sonnet-4-20250514",
                "max_tokens": 1024,
                "messages": [{"role": "user", "content": f"Summarize: {doc}"}],
            },
        }
        for i, doc in enumerate(documents)
    ]
)

# Poll
while batch.processing_status != "ended":
    time.sleep(30)
    batch = client.messages.batches.retrieve(batch.id)

# Get results
for result in client.messages.batches.results(batch.id):
    if result.result.type == "succeeded":
        print(result.custom_id, result.result.message.content[0].text[:100])

Batch Limits

Limit	Value
Max requests per batch	10,000
Max concurrent batches	100
Processing SLA	24 hours
Pricing	50% of standard per-token pricing
Result availability	29 days after creation

Output

Batch created with up to 10,000 requests
Processing status tracked via polling
Results retrieved with per-request success/error status
Failed requests identified for retry in a new batch

Error Handling

Result Type	Meaning	Action
`succeeded`	Normal response	Process `result.message`
`errored`	API error	Check `result.error` — retry failed items in new batch
`expired`	Not processed within 24h	Resubmit in new batch
`canceled`	Batch was canceled	Resubmit if needed

Examples

See Step 1 (batch creation), Step 2 (polling), Step 3 (result retrieval), Python example, and Batch Limits table above.

Resources

Message Batches API
Batch Pricing — 50% off standard

Next Steps

See clade-ci-integration for using batches in CI pipelines.

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