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, 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 |
|---|---|---|
| 440 | catalog plugins (catalog-entry cohort) | node scripts/generate-readme-toc.mjs over marketplace.extended.json |
| 2,984 | 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 394 published packages in the claude-code-plugins namespace. Updated daily by GitHub Actions.
| Window | All packages | Established (>30d) |
|---|---|---|
| Last 24 hours | 641 | 641 |
| Last 7 days | 3,272 | 3,272 |
| Last 30 days | 11,794 | 11,794 |
"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 2026-09-02T04:55:57.759Z.
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 | 37 |
| 🎭 | AI Agents & Agency | 9 |
| 🔌 | API Development | 26 |
| 💼 | Business Tools | 6 |
| 👥 | Community | 20 |
| ₿ | Crypto & Web3 | 27 |
| 💾 | Database | 26 |
| 🎨 | Design | 2 |
| 🔧 | DevOps & Infrastructure | 36 |
| 📚 | Examples & Templates | 5 |
| 🧩 | MCP Servers | 17 |
| 📦 | Packages | 5 |
| ⚡ | Performance | 25 |
| ✅ | Productivity | 29 |
| 🎁 | SaaS Skill Packs | 105 |
| 🔐 | 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: clay-cost-tuning
description: 'Optimize Clay credit spending with provider key management, waterfall
tuning, and budget controls.
Use when analyzing Clay costs, reducing credit consumption,
or implementing spending alerts and caps.
Trigger with phrases like "clay cost", "clay billing", "reduce clay costs",
"clay pricing", "clay expensive", "clay budget", "clay credits".
'
allowed-tools: Read, Write, Edit, Grep
version: 1.14.0
license: MIT
author: Jeremy Longshore <jeremy@intentsolutions.io>
tags:
- saas
- clay
- api
- monitoring
- cost-optimization
compatibility: Designed for Claude CodeReduce Clay data enrichment spending by connecting your own API keys (70-80% savings), optimizing waterfall depth, improving input data quality, and implementing budget controls. Clay's March 2026 pricing split credits into Data Credits and Actions, changing the optimization calculus.
This is the single most impactful cost reduction. Clay charges 0 Data Credits when you use your own API keys:
| Provider | Clay-Managed Cost | Own Key Cost | Annual Savings (10K rows/mo) |
|---|---|---|---|
| Apollo | 2 credits/lookup | 0 credits | ~240K credits/year |
| Clearbit | 2-5 credits | 0 credits | ~360K credits/year |
| Hunter.io | 2 credits | 0 credits | ~240K credits/year |
| Prospeo | 2 credits | 0 credits | ~240K credits/year |
| People Data Labs | 3 credits | 0 credits | ~360K credits/year |
| ZoomInfo | 5-13 credits | 0 credits | ~1M+ credits/year |
Setup: Go to Settings > Connections in Clay, click Add Connection, and paste your provider API key. All enrichments using that provider will consume 0 Clay credits (1 Action is still consumed per enrichment).
Each waterfall step costs credits (if using Clay-managed keys) and time:
# Expensive waterfall (5 providers, 10-15 credits/row):
expensive:
- apollo: 2 credits
- hunter: 2 credits
- prospeo: 2 credits
- dropcontact: 3 credits
- findymail: 3 credits
total_max: 12 credits/row
coverage: ~92%
# Optimized waterfall (2 providers, 4 credits/row):
optimized:
- apollo: 2 credits # Highest coverage provider first
- hunter: 2 credits # Strong backup
total_max: 4 credits/row
coverage: ~83%
savings: "67% credit reduction, ~9% coverage loss"
March 2026 change: Failed lookups no longer cost Data Credits. This makes wider waterfalls less expensive than before, since you only pay when data is actually found.
Credits wasted on unenrichable rows are the most common cost leak:
// src/clay/cost-filter.ts
function estimateCreditCost(rows: any[], creditsPerRow: number): {
filteredRows: any[];
estimatedCredits: number;
savings: number;
} {
const personalDomains = new Set([
'gmail.com', 'yahoo.com', 'hotmail.com', 'outlook.com', 'icloud.com',
]);
const filtered = rows.filter(row => {
if (!row.domain?.includes('.')) return false;
if (personalDomains.has(row.domain)) return false;
if (!row.first_name || !row.last_name) return false;
return true;
});
// Deduplicate
const seen = new Set<string>();
const deduped = filtered.filter(row => {
const key = `${row.domain}:${row.first_name}:${row.last_name}`.toLowerCase();
if (seen.has(key)) return false;
seen.add(key);
return true;
});
return {
filteredRows: deduped,
estimatedCredits: deduped.length * creditsPerRow,
savings: (rows.length - deduped.length) * creditsPerRow,
};
}
// Usage
const { filteredRows, estimatedCredits, savings } = estimateCreditCost(rawLeads, 6);
console.log(`Will process ${filteredRows.length} rows (${estimatedCredits} credits)`);
console.log(`Saved ${savings} credits by pre-filtering`);
Test enrichment quality on a small sample before committing credits to the full list:
// src/clay/sampler.ts
function sampleForTest(rows: any[], sampleSize = 100): {
sample: any[];
remaining: any[];
estimatedTotalCredits: number;
} {
// Random sample for representative results
const shuffled = [...rows].sort(() => Math.random() - 0.5);
const sample = shuffled.slice(0, sampleSize);
const remaining = shuffled.slice(sampleSize);
return {
sample,
remaining,
estimatedTotalCredits: rows.length * 6, // Estimate 6 credits/row average
};
}
// Workflow:
// 1. Send sample (100 rows) to Clay test table
// 2. Check hit rate after enrichment completes
// 3. If hit rate > 60%, proceed with full list
// 4. If hit rate < 40%, clean input data first
// src/clay/budget-monitor.ts
interface CreditBudget {
monthlyLimit: number; // From your plan
dailyThreshold: number; // Alert if exceeded
perTableMax: number; // Cap per table
}
const PLAN_BUDGETS: Record<string, CreditBudget> = {
launch: { monthlyLimit: 2_500, dailyThreshold: 125, perTableMax: 500 },
growth: { monthlyLimit: 6_000, dailyThreshold: 300, perTableMax: 1_500 },
enterprise: { monthlyLimit: 50_000, dailyThreshold: 2_500, perTableMax: 10_000 },
};
class BudgetMonitor {
private dailyUsage = 0;
private monthlyUsage = 0;
private tableUsage = new Map<string, number>();
constructor(private budget: CreditBudget) {}
recordUsage(tableId: string, credits: number) {
this.dailyUsage += credits;
this.monthlyUsage += credits;
this.tableUsage.set(tableId, (this.tableUsage.get(tableId) || 0) + credits);
// Check thresholds
if (this.dailyUsage > this.budget.dailyThreshold) {
console.warn(`ALERT: Daily credit usage (${this.dailyUsage}) exceeds threshold (${this.budget.dailyThreshold})`);
}
if (this.monthlyUsage > this.budget.monthlyLimit * 0.8) {
console.warn(`ALERT: Monthly credits at ${((this.monthlyUsage / this.budget.monthlyLimit) * 100).toFixed(0)}%`);
}
if ((this.tableUsage.get(tableId) || 0) > this.budget.perTableMax) {
console.error(`STOP: Table ${tableId} exceeded per-table cap (${this.budget.perTableMax} credits)`);
}
}
}
function calculateCostPerLead(
totalCredits: number,
totalRows: number,
rowsWithEmail: number,
rowsPushedToCRM: number,
): void {
console.log('=== Clay Cost Analysis ===');
console.log(`Credits used: ${totalCredits}`);
console.log(`Cost per row processed: ${(totalCredits / totalRows).toFixed(1)} credits`);
console.log(`Cost per email found: ${(totalCredits / Math.max(rowsWithEmail, 1)).toFixed(1)} credits`);
console.log(`Cost per CRM lead: ${(totalCredits / Math.max(rowsPushedToCRM, 1)).toFixed(1)} credits`);
console.log(`Email find rate: ${((rowsWithEmail / totalRows) * 100).toFixed(1)}%`);
console.log(`Qualification rate: ${((rowsPushedToCRM / totalRows) * 100).toFixed(1)}%`);
}
| Issue | Cause | Solution |
|---|---|---|
| Credits burning fast | Waterfall enriching all providers | Enable "stop on first result", reduce depth |
| Low hit rate (<30%) | Bad input data | Filter personal domains, validate before import |
| Unexpected charges | New column added with auto-run | Review all auto-run columns monthly |
| Credit rollover capped | Balance exceeds 2x monthly | Use credits before they cap out |
Publish a credit-control decision with table scope, budget, actual usage, cost-per-qualified-result, quality baseline, owner, alert threshold, and rollback/stop condition. Treat pricing and calculator results as estimates; validate current plan behavior in the authorized workspace before expanding automated enrichments.
Set a staging table’s per-run and monthly credit caps, run a qualified sample, and compare cost-per-lead with the prior baseline. If spend rises while hit rate falls, trip the stop condition, disable the expensive auto-run column, and review input quality and provider order before resuming.
For reference architecture patterns, see clay-reference-architecture.
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