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attio-cost-tuning

A model-agnostic agent-skills platform.

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项目 README

来源文件:README.md

抓取于 2026年8月27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.

Release CLI Plugins Skills GitHub Stars skills.sh Sponsor: Kobiton Buy me a monster

ko-fi

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."

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

📦 Live npm Downloads

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

WindowAll packagesEstablished (>30d)
Last 24 hours962962
Last 7 days2,9202,916
Last 30 days12,86812,779

"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:

#PackageLast 30d
1@intentsolutionsio/openrouter-pack556
2@intentsolutionsio/groq-pack496
3@intentsolutionsio/databricks-pack274
4@intentsolutionsio/clickhouse-pack273
5@intentsolutionsio/wallet-security-auditor263
6@intentsolutionsio/notion-pack258
7@intentsolutionsio/elevenlabs-pack244
8@intentsolutionsio/freshie-inventory-manager214
9@intentsolutionsio/supabase-pack210
10@intentsolutionsio/agency-os204

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:

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).

CategoryPlugins
🤖AI & Machine Learning36
🎭AI Agents & Agency10
🔌API Development26
💼Business Tools6
👥Community21
₿Crypto & Web327
💾Database26
🎨Design2
🔧DevOps & Infrastructure36
📚Examples & Templates5
🧩MCP Servers16
📦Packages5
⚡Performance25
✅Productivity30
🎁SaaS Skill Packs106
🔐Security27
✨Skill Enhancers9
🧪Testing28
📁Analytics1

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:

ClassWhat it isHow the reader can tell
Canonical skillFirst-party, harness-free, the source of truthNo .source.json in its plugin directory
Generated adapterA thin, machine-produced harness projectionLives under a generated path with a "generated — do not edit" header
First-party packageAn Intent Solutions distribution (npm, cowork zip)@intentsolutionsio scope, IS-authored license
Upstream mirrorSomebody 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:

Governance

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。
  • 未检测到明显脚本安装指令。
  • 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

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

Codex — 手动复制安装

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

Claude Code — Git Clone 安装

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

Claude Code — 手动复制安装

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

Cursor — Git Clone 安装

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

Cursor — 手动复制安装

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

GitHub Copilot — Git Clone 安装

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

GitHub Copilot — 手动复制安装

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

Windsurf — Git Clone 安装

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

Windsurf — 手动复制安装

  1. 安装前请先查看来源仓库和风险报告。
  2. 从源仓库下载 SKILL.md 及相关文件。
  3. 在 Windsurf 的 skills 目录中创建新文件夹。
  4. 将所有 skill 文件复制到新文件夹中。
  5. 重启 Windsurf 让新的 skill 生效。
查看 SKILL.md 原文
name: attio-cost-tuning
description: 'Optimize Attio API usage costs -- reduce request volume, select the

  right plan, monitor usage, and implement budget alerts.

  Trigger: "attio cost", "attio billing", "reduce attio costs",

  "attio pricing", "attio expensive", "attio budget", "attio usage".

  '
allowed-tools: Read, Grep
version: 1.7.0
license: MIT
author: Jeremy Longshore <jeremy@intentsolutions.io>
tags:
- saas
- crm
- attio
compatibility: Designed for Claude Code

Attio Cost Tuning

Overview

Attio pricing is based on workspace seats, not API calls. However, API rate limits effectively cap throughput, so optimizing request volume improves both performance and cost efficiency. This skill covers practical strategies to reduce unnecessary API calls.

Attio Pricing Model

PlanPriceKey Limits
Free$0/user/mo3 users, basic objects, limited automations
Plus$29/user/moUnlimited objects, lists, advanced reporting
Pro$59/user/moAdvanced automations, API access, webhooks
EnterpriseCustomSSO, audit logs, dedicated support, custom rate limits

API access requires Plus plan or higher. Rate limits are per-workspace, not per-seat.

Instructions

Step 1: Audit Current API Usage

// Instrument all API calls to measure usage patterns
class AttioUsageTracker {
  private calls: Array<{
    method: string;
    path: string;
    timestamp: number;
    durationMs: number;
    cached: boolean;
  }> = [];

  async track<T>(
    method: string,
    path: string,
    operation: () => Promise<T>,
    cached = false
  ): Promise<T> {
    const start = Date.now();
    try {
      const result = await operation();
      this.calls.push({
        method, path, timestamp: start,
        durationMs: Date.now() - start, cached,
      });
      return result;
    } catch (err) {
      this.calls.push({
        method, path, timestamp: start,
        durationMs: Date.now() - start, cached: false,
      });
      throw err;
    }
  }

  report(windowMs = 3600_000): {
    totalCalls: number;
    cachedCalls: number;
    topEndpoints: Array<{ path: string; count: number }>;
  } {
    const cutoff = Date.now() - windowMs;
    const recent = this.calls.filter((c) => c.timestamp > cutoff);
    const cached = recent.filter((c) => c.cached).length;

    const endpointCounts = new Map<string, number>();
    for (const call of recent) {
      const key = `${call.method} ${call.path}`;
      endpointCounts.set(key, (endpointCounts.get(key) || 0) + 1);
    }

    const topEndpoints = [...endpointCounts.entries()]
      .sort((a, b) => b[1] - a[1])
      .slice(0, 10)
      .map(([path, count]) => ({ path, count }));

    return { totalCalls: recent.length, cachedCalls: cached, topEndpoints };
  }
}

Step 2: Reduce Request Volume

The five biggest cost/rate-limit savers:

StrategyReductionImplementation
Cache object schemas50-90% of schema readsCache GET /objects and /attributes for 30 min
Batch with $in filterN:1 on lookupsSingle query instead of N individual fetches
Use limit: 5005x fewer pagination requestsMax page size per request
Webhook-driven syncEliminate pollingReact to changes instead of polling every N seconds
Cache records30-80% of record readsLRU cache with webhook invalidation

Step 3: Eliminate Polling with Webhooks

// BAD: Polling every 30 seconds for changes
setInterval(async () => {
  const records = await client.post("/objects/people/records/query", {
    filter: { updated_at: { $gt: lastCheck.toISOString() } },
    limit: 500,
  });
  for (const record of records.data) await processUpdate(record);
  lastCheck = new Date();
}, 30_000);
// Cost: 2,880 requests/day MINIMUM (even with no changes)

// GOOD: Webhook-driven (0 requests when no changes)
app.post("/webhooks/attio", async (req, res) => {
  res.status(200).json({ received: true });
  const event = req.body;
  if (event.event_type === "record.updated") {
    const record = await client.get(
      `/objects/${event.object.api_slug}/records/${event.record.id.record_id}`
    );
    await processUpdate(record);
  }
});
// Cost: 1 request per actual change

Step 4: Smart Caching Tiers

import { LRUCache } from "lru-cache";

// Tier 1: Schema data (changes very rarely)
const schemaCache = new LRUCache<string, unknown>({
  max: 100,
  ttl: 30 * 60 * 1000, // 30 minutes
});

// Tier 2: Record data (changes occasionally)
const recordCache = new LRUCache<string, unknown>({
  max: 5000,
  ttl: 5 * 60 * 1000, // 5 minutes
});

// Tier 3: List/query results (changes frequently)
const queryCache = new LRUCache<string, unknown>({
  max: 200,
  ttl: 30 * 1000, // 30 seconds
});

function getCacheForPath(path: string): LRUCache<string, unknown> {
  if (path.includes("/attributes") || path === "/objects") return schemaCache;
  if (path.includes("/records/") && !path.includes("/query")) return recordCache;
  return queryCache;
}

Step 5: Request Budget Monitor

class AttioRequestBudget {
  private requestsToday = 0;
  private dayStart = this.todayStart();
  private readonly dailyBudget: number;
  private readonly warningThreshold: number;

  constructor(dailyBudget = 10_000) {
    this.dailyBudget = dailyBudget;
    this.warningThreshold = dailyBudget * 0.8;
  }

  private todayStart(): number {
    const d = new Date();
    d.setHours(0, 0, 0, 0);
    return d.getTime();
  }

  recordRequest(): void {
    const today = this.todayStart();
    if (today !== this.dayStart) {
      this.dayStart = today;
      this.requestsToday = 0;
    }
    this.requestsToday++;

    if (this.requestsToday === Math.floor(this.warningThreshold)) {
      console.warn(`Attio budget warning: ${this.requestsToday}/${this.dailyBudget} requests today`);
    }

    if (this.requestsToday >= this.dailyBudget) {
      console.error(`Attio daily budget exceeded: ${this.requestsToday} requests`);
    }
  }

  getUsage(): { today: number; budget: number; percentUsed: number } {
    return {
      today: this.requestsToday,
      budget: this.dailyBudget,
      percentUsed: Math.round((this.requestsToday / this.dailyBudget) * 100),
    };
  }
}

Step 6: SQL Usage Dashboard

If you log API calls to a database:

-- Daily request volume (last 30 days)
SELECT
  DATE(timestamp) AS day,
  COUNT(*) AS total_requests,
  COUNT(CASE WHEN cached THEN 1 END) AS cache_hits,
  ROUND(COUNT(CASE WHEN cached THEN 1 END) * 100.0 / COUNT(*), 1) AS cache_hit_pct,
  ROUND(AVG(duration_ms), 0) AS avg_latency_ms
FROM attio_api_log
WHERE timestamp >= CURRENT_DATE - INTERVAL '30 days'
GROUP BY DATE(timestamp)
ORDER BY day DESC;

-- Top endpoints by volume (identify optimization targets)
SELECT
  method || ' ' || path AS endpoint,
  COUNT(*) AS calls,
  ROUND(AVG(duration_ms), 0) AS avg_ms,
  COUNT(CASE WHEN status = 429 THEN 1 END) AS rate_limited
FROM attio_api_log
WHERE timestamp >= CURRENT_DATE - INTERVAL '7 days'
GROUP BY method, path
ORDER BY calls DESC
LIMIT 10;

Cost Optimization Checklist

[ ] Object schema calls cached (30-minute TTL)
[ ] Record lookups cached (5-minute TTL with webhook invalidation)
[ ] Polling replaced with webhooks where possible
[ ] Bulk operations use $in filter (1 request instead of N)
[ ] Pagination uses limit: 500 (max page size)
[ ] Unnecessary API calls identified and eliminated
[ ] Usage monitoring in place with daily budget alerts
[ ] Cache hit rate > 50% on read-heavy workloads

Prerequisites

Confirm that you have an Attio workspace appropriate to the task, a dedicated non-production record or workspace for testing, and only the API token scopes or administrative access required by the procedure.

Output

Following this guide produces the Attio integration outcome for its topic—configuration, validation evidence, operational recovery, or a documented migration result. Record command output and relevant identifiers so a failed step is traceable.

Examples

Start with the smallest applicable command or code example in the relevant section, using a dedicated test record or workspace and non-production credentials. Confirm the expected response or validation result before applying the pattern to production.

Error Handling

Cost issueRoot causeFix
High request volumePolling loopSwitch to webhooks
Low cache hit rateShort TTL or no cacheIncrease TTL, add webhook invalidation
Rate limiting (429s)Burst without throttlingAdd PQueue with intervalCap
N+1 queriesIndividual record fetchesBatch with $in filter

Resources

Next Steps

For architecture patterns, see attio-reference-architecture.

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