复制安装命令
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A model-agnostic agent-skills platform.
用 Codex 或 Claude 安装复制这段 Prompt,粘贴到 Codex、Claude 或其他助手里,让它先审查 Skill 页面再帮你安装。
复制前请先查看来源、License 和安全提示。
来源文件:README.md
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
ccpiCLI 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.
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.
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/*/ |
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:
Last refreshed 2026-08-19T03:03:05.709Z.
Five real questions, five doors — each resolves to a live, generated surface, never a hand-maintained list:
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 |
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 |
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.
Start with the contribution guide, then the intake and review standards every submission passes through:
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.
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.
name: clade-ci-integration
description: "Test and validate Claude integrations in CI/CD pipelines \u2014\nUse\
\ when working with ci-integration patterns.\nGitHub Actions, mocking strategies,\
\ and cost control.\nTrigger with \"anthropic ci\", \"test claude in ci\", \"anthropic\
\ github actions\",\n\"claude automated testing\".\n"
allowed-tools: Read, Write, Edit, Bash(npm:*)
version: 1.0.0
license: MIT
author: Jeremy Longshore <jeremy@intentsolutions.io>
tags:
- saas
- anthropic
- claude
- ci
- testing
compatibility: Designed for Claude CodeTesting Claude integrations in CI requires handling API keys securely, mocking for unit tests, and making real calls only in integration tests.
# .github/workflows/test.yml
name: Test Claude Integration
on: [push, pull_request]
jobs:
test:
runs-on: ubuntu-latest
steps:
- uses: actions/checkout@v4
- uses: actions/setup-node@v4
with:
node-version: 20
- run: npm ci
# Unit tests — no API key needed (mocked)
- run: npm run test:unit
# Integration tests — real API calls
- run: npm run test:integration
env:
ANTHROPIC_API_KEY: ${{ secrets.ANTHROPIC_API_KEY }}
// tests/helpers/mock-anthropic.ts
import { vi } from 'vitest';
export function mockAnthropicClient() {
return {
messages: {
create: vi.fn().mockResolvedValue({
id: 'msg_mock',
type: 'message',
role: 'assistant',
model: 'claude-sonnet-4-20250514',
content: [{ type: 'text', text: 'Mock response' }],
stop_reason: 'end_turn',
usage: { input_tokens: 10, output_tokens: 5 },
}),
stream: vi.fn().mockReturnValue({
async *[Symbol.asyncIterator]() {
yield { type: 'content_block_delta', delta: { type: 'text_delta', text: 'Mock' } };
},
finalMessage: vi.fn().mockResolvedValue({ usage: { input_tokens: 10, output_tokens: 5 } }),
}),
},
};
}
// In your test:
import { mockAnthropicClient } from './helpers/mock-anthropic';
test('summarize function returns text', async () => {
const client = mockAnthropicClient();
const result = await summarize(client, 'Some long text...');
expect(result).toBe('Mock response');
expect(client.messages.create).toHaveBeenCalledWith(
expect.objectContaining({ model: 'claude-sonnet-4-20250514' })
);
});
// tests/integration/claude.test.ts
import Anthropic from '@claude-ai/sdk';
import { describe, test, expect } from 'vitest';
describe('Claude API Integration', () => {
const client = new Anthropic(); // Uses ANTHROPIC_API_KEY env var
test('messages.create returns valid response', async () => {
const message = await client.messages.create({
model: 'claude-haiku-4-5-20251001', // Cheapest for CI
max_tokens: 50,
messages: [{ role: 'user', content: 'Say "test passed" in 2 words.' }],
});
expect(message.content[0].type).toBe('text');
expect(message.stop_reason).toBe('end_turn');
expect(message.usage.output_tokens).toBeGreaterThan(0);
}, 30_000); // 30s timeout for API calls
});
| Strategy | How |
|---|---|
| Use Haiku only | Cheapest model, fast |
| Limit max_tokens | max_tokens: 50 for validation tests |
| Skip on PRs from forks | Don't expose API key to untrusted code |
| Run integration tests only on main | if: github.ref == 'refs/heads/main' |
| Budget cap | Set spending limits in Anthropic console |
| Error | Cause | Solution |
|---|---|---|
| API Error | Check error type and status code | See clade-common-errors |
See GitHub Actions YAML, Mock Strategy with Vitest, Integration Test with real API, and Cost Control table above.
See clade-deploy-integration for deploying to production.
ANTHROPIC_API_KEY stored as GitHub Actions secretEach section contains production-ready code examples. Copy and adapt them to your use case.
Integrate the patterns that match your requirements. Test each change individually.
Run your test suite to confirm the integration works correctly.
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