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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: clickhouse-enterprise-rbac
description: |
Configure ClickHouse enterprise RBAC — SQL-based users, roles, row policies,
column-level grants, and quota management.
Use when setting up multi-user access control, implementing tenant isolation,
or configuring enterprise security for ClickHouse.
Trigger with "clickhouse RBAC", "clickhouse roles", "clickhouse permissions",
"clickhouse row policy", "clickhouse enterprise access", "clickhouse GRANT".
allowed-tools: Read, Write
version: 1.7.0
license: MIT
author: Jeremy Longshore <jeremy@intentsolutions.io>
tags:
- saas
- database
- analytics
- clickhouse
- olap
compatibility: Designed for Claude CodeImplement enterprise-grade role-based access control in ClickHouse using SQL-based user management, hierarchical roles, row-level policies, column grants, quotas, and settings profiles. The workflow builds least-privilege access from the ground up: create authenticated users, compose reusable roles, then narrow visibility with row and column policies and cap resource use with quotas.
Follow the seven steps below at a high level from this file; drill into the full implementation for every SQL statement, and worked examples for two end-to-end scenarios plus audit queries.
access_management = 1 enabled (default in Cloud)GRANT OPTIONThe build-out is seven steps. Steps 1–3 (users, roles, row security) carry the core skeleton here; Steps 4–7 (column grants, quotas, settings profiles, and the application wrapper) are summarized here and fully specified in references/implementation.md.
Pick an authentication method per user: sha256_password (standard),
double_sha1_password (MySQL wire protocol), or bcrypt_password (strongest — use
for admin accounts). Restrict network reach with HOST IP and cap per-user resources
inline with SETTINGS.
CREATE USER app_backend
IDENTIFIED WITH sha256_password BY 'strong-password-here'
DEFAULT DATABASE analytics
HOST IP '10.0.0.0/8' -- Restrict to VPC
SETTINGS max_memory_usage = 10000000000, -- 10GB per query
max_execution_time = 60; -- 60s timeout
SHOW CREATE USER app_backend; -- Verify
Build leaf-level base roles (data_reader, data_writer, schema_manager), then
compose them into job roles (analyst, developer, platform_admin). Grant roles to
users and set a default role that activates on connect.
CREATE ROLE data_reader;
GRANT SELECT ON analytics.* TO data_reader;
CREATE ROLE analyst;
GRANT data_reader TO analyst; -- Composite inherits base
GRANT analyst TO app_backend;
SET DEFAULT ROLE analyst TO app_backend;
SHOW GRANTS FOR app_backend; -- Verify the full chain
Isolate multi-tenant data with row policies — each user sees only rows matching its
USING predicate. A permissive USING 1 = 1 policy lets an admin role see everything.
CREATE ROW POLICY acme_isolation ON analytics.events
FOR SELECT
USING tenant_id = 1
TO tenant_acme;
SELECT * FROM system.row_policies; -- List all policies
GRANT SELECT(col, ...) to hide PII columns and
GRANT INSERT(col, ...) to prevent metadata injection.queries, read_rows, result_rows, and execution_time
per interval so one user cannot exhaust the cluster.readonly, memory, thread, and concurrency
ceilings; a separate ETL profile enables async_insert.Full SQL and the TypeScript wrapper: references/implementation.md.
Running this workflow produces, in the target ClickHouse instance:
system.row_policies.SHOW GRANTS FOR <role>.Verify the deployment with SHOW ACCESS, SHOW GRANTS FOR <user>, and the audit
queries in references/examples.md.
| Error Code | Name | Solution |
|---|---|---|
| 497 | ACCESS_DENIED | SHOW GRANTS FOR user, add missing GRANT |
| 516 | AUTHENTICATION_FAILED | Verify password, check HOST restriction |
| 164 | READONLY | User has readonly=1, grant write if needed |
| 497 | Not enough privileges to execute GRANT | Use admin user with GRANT OPTION |
Two end-to-end scenarios — a multi-tenant SaaS isolation setup and a PII-safe analyst role — plus the access-control audit queries live in references/examples.md. The core of Example 1:
-- Each tenant reads only its own rows from a shared table
CREATE ROW POLICY acme_isolation ON analytics.events FOR SELECT USING tenant_id = 1 TO tenant_acme;
CREATE ROW POLICY globex_isolation ON analytics.events FOR SELECT USING tenant_id = 2 TO tenant_globex;
-- Connected as tenant_acme, this returns ONLY tenant_id = 1:
SELECT tenant_id, count() FROM analytics.events GROUP BY tenant_id;
For schema migrations, see the clickhouse-migration-deep-dive skill in this pack.
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