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 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 | 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: bamboohr-cost-tuning
description: 'Optimize BambooHR integration costs through request reduction, caching,
and usage monitoring. Use when analyzing API usage patterns, reducing
unnecessary calls, or implementing request budgets.
Trigger with phrases like "bamboohr cost", "bamboohr usage",
"reduce bamboohr calls", "bamboohr optimization", "bamboohr budget".
'
allowed-tools: Read, Grep
version: 1.4.0
license: MIT
author: Jeremy Longshore <jeremy@intentsolutions.io>
tags:
- saas
- hr
- bamboohr
- optimization
compatibility: Designed for Claude CodeBambooHR pricing is per-employee-per-month (not per-API-call), but excessive API usage triggers rate limiting (503 errors) which causes sync failures and operational issues. This skill covers reducing API call volume, monitoring usage, and building efficient sync patterns.
BambooHR charges by employee count, not API calls:
| Plan | Pricing Model | API Access |
|---|---|---|
| Essentials | Per employee/month | Full REST API |
| Advantage | Per employee/month | Full REST API + advanced reports |
| Custom/Enterprise | Negotiated | Full API + dedicated support |
Key insight: API call volume does not directly affect your bill, but hitting rate limits causes operational failures. Optimize for reliability, not cost.
// Instrument your client to log all API calls
class InstrumentedBambooHRClient {
private callLog: { endpoint: string; method: string; timestamp: number; durationMs: number }[] = [];
async request<T>(method: string, path: string, body?: unknown): Promise<T> {
const start = Date.now();
const result = await this.innerClient.request<T>(method, path, body);
this.callLog.push({
endpoint: path.split('?')[0], // Strip query params
method,
timestamp: start,
durationMs: Date.now() - start,
});
return result;
}
generateReport(): void {
// Group by endpoint
const byEndpoint = new Map<string, number>();
for (const call of this.callLog) {
const key = `${call.method} ${call.endpoint}`;
byEndpoint.set(key, (byEndpoint.get(key) || 0) + 1);
}
console.log('\n=== BambooHR API Usage Report ===');
console.log(`Total calls: ${this.callLog.length}`);
console.log(`Time window: ${((Date.now() - this.callLog[0]?.timestamp || 0) / 1000 / 60).toFixed(1)} minutes`);
console.log('\nBy endpoint:');
for (const [endpoint, count] of [...byEndpoint.entries()].sort((a, b) => b[1] - a[1])) {
const pct = ((count / this.callLog.length) * 100).toFixed(1);
console.log(` ${count.toString().padStart(5)} (${pct}%) ${endpoint}`);
}
}
}
Pattern 1: Replace polling with webhooks
// BAD: Polling every 5 minutes (288 calls/day minimum)
setInterval(async () => {
const dir = await client.getDirectory();
checkForChanges(dir);
}, 5 * 60 * 1000);
// GOOD: Use webhooks for real-time changes (0 polling calls)
// See bamboohr-webhooks-events skill
// Only poll as a fallback safety net (once per hour)
setInterval(async () => {
const changed = await client.request('GET',
`/employees/changed/?since=${lastSync}`);
// Only process if webhook missed something
}, 60 * 60 * 1000);
Pattern 2: Request only needed fields
// BAD: Requesting all fields when you only need 3
const emp = await client.getEmployee(id, [
'firstName', 'lastName', 'displayName', 'jobTitle', 'department',
'division', 'location', 'workEmail', 'homeEmail', 'mobilePhone',
'hireDate', 'payRate', 'payType', 'ssn', 'dateOfBirth', // ...etc
]);
// GOOD: Only request what you use
const emp = await client.getEmployee(id, ['firstName', 'lastName', 'workEmail']);
Pattern 3: Cache the directory
// BAD: Fetching directory on every page load
app.get('/employees', async (req, res) => {
const dir = await client.getDirectory(); // Called 1000x/day
res.json(dir.employees);
});
// GOOD: Cache with webhook-based invalidation
let cachedDirectory: any = null;
let cacheTimestamp = 0;
async function getDirectory() {
if (cachedDirectory && Date.now() - cacheTimestamp < 5 * 60 * 1000) {
return cachedDirectory;
}
cachedDirectory = await client.getDirectory();
cacheTimestamp = Date.now();
return cachedDirectory;
}
// Invalidate on webhook
function onWebhookReceived() {
cachedDirectory = null;
}
Pattern 4: Use custom reports for bulk data
// BAD: 500 individual employee GETs
for (const id of employeeIds) {
await client.getEmployee(id, ['firstName', 'department']);
}
// GOOD: 1 custom report
const all = await client.customReport(['firstName', 'lastName', 'department']);
class RequestBudget {
private count = 0;
private windowStart = Date.now();
private readonly maxPerHour: number;
constructor(maxPerHour = 500) {
this.maxPerHour = maxPerHour;
}
async acquire(): Promise<void> {
// Reset counter every hour
if (Date.now() - this.windowStart > 3600_000) {
this.count = 0;
this.windowStart = Date.now();
}
if (this.count >= this.maxPerHour) {
const waitMs = 3600_000 - (Date.now() - this.windowStart);
console.warn(`Request budget exhausted. Waiting ${(waitMs / 1000).toFixed(0)}s`);
await new Promise(r => setTimeout(r, waitMs));
this.count = 0;
this.windowStart = Date.now();
}
this.count++;
}
stats() {
return {
used: this.count,
budget: this.maxPerHour,
remaining: this.maxPerHour - this.count,
windowResetIn: Math.max(0, 3600_000 - (Date.now() - this.windowStart)),
};
}
}
const budget = new RequestBudget(500);
// Wrap all BambooHR calls
async function budgetedRequest<T>(operation: () => Promise<T>): Promise<T> {
await budget.acquire();
return operation();
}
-- If logging API calls to a database
SELECT
DATE_TRUNC('hour', timestamp) AS hour,
endpoint,
COUNT(*) AS calls,
AVG(duration_ms) AS avg_latency,
COUNT(*) FILTER (WHERE status >= 400) AS errors,
COUNT(*) FILTER (WHERE status = 503) AS rate_limits
FROM bamboohr_api_log
WHERE timestamp >= NOW() - INTERVAL '7 days'
GROUP BY 1, 2
ORDER BY 1 DESC, calls DESC;
| Optimization | Calls Before | Calls After | Reduction |
|---|---|---|---|
| Webhooks vs polling | 288/day | 24/day (safety net) | 92% |
| Custom reports vs N+1 | 501/sync | 1/sync | 99.8% |
| Directory caching | 1000/day | 12/day | 98.8% |
| Incremental sync | Full pull | Delta only | 90-99% |
Measure aggregate request counts for the approved integration scope, minimize field selection, and cache only encrypted, access-controlled data with a defined expiry. Verify current plan terms through BambooHR and the account owner before making cost claims; changes that affect HR-data freshness require a reconciliation check and rollback flag.
| Issue | Cause | Solution |
|---|---|---|
| Budget exhausted | High-traffic feature | Increase budget or add caching |
| Stale cached data | Cache TTL too long | Reduce TTL or invalidate on webhook |
| Webhook delivery gaps | BambooHR delivery failure | Keep hourly polling as fallback |
| Rate limit during sync | Too many parallel requests | Use queue with concurrency limit |
For architecture patterns, see bamboohr-reference-architecture.
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