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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: cad-dxf-agent
description: Analyzes DXF drawings deterministically — ADA/IBC code compliance, drawing health and QA, quantity takeoff, plain-English summaries, RFI generation, and room/zone detection — with no LLM or API key. Use when a user has a .dxf file and wants to check code compliance, audit drawing quality, pull quantities, summarize a drawing, generate RFIs, or detect rooms and areas. Trigger with "analyze this DXF", "check compliance", "drawing health", "quantity takeoff", "summarize this drawing", "generate RFIs", "detect zones", or "/cad-dxf-agent".
allowed-tools: Read, Glob, Bash(cad-analyze:*), Bash(cad-revision:*), Bash(pip:*), Bash(python:*), Bash(python3:*), AskUserQuestion
argument-hint: a path to a .dxf file (and optionally which check — compliance, health, takeoff, summary, rfi, zones)
version: 0.1.0
author: Jeremy Longshore <jeremy@intentsolutions.io>
license: Apache-2.0
compatibility: Designed for Claude Code
tags:
- dxf
- cad
- compliance
- takeoff
- drawing-analysisCAD reviewers manually scan drawings for code compliance, QA defects, quantities,
and ambiguities — slow and error-prone. This skill automates that for DXF files by
driving the deterministic cad-analyze CLI (no LLM, no API key, no network) and
reporting the findings in prose.
| Capability | What it answers | Command |
|---|---|---|
| compliance | Does it meet ADA / IBC / a custom code? | cad-analyze compliance FILE [--profile ada|ibc-2021|residential] |
| health | Is the drawing clean? (overlaps, text, orphan layers) | cad-analyze health FILE |
| takeoff | How much of everything? | cad-analyze takeoff FILE |
| summary | What is this drawing, in plain English? | cad-analyze summary FILE |
| rfi | What's ambiguous / needs clarification? | cad-analyze rfi FILE |
| zones | What rooms/areas are enclosed, and how big? | cad-analyze zones FILE |
| compare | What changed between two revisions? | cad-revision diff MASTER REVISION |
The CLI ships with the cad-dxf-agent Python package. Check, install only if missing:
command -v cad-analyze >/dev/null 2>&1 || \
pip install "git+https://github.com/jeremylongshore/cad-ai-agent.git"
Glob for **/*.dxf and, if several match, ask which one with AskUserQuestion.--json, e.g. cad-analyze health DRAWING.dxf --json.--profile when the user names a code; default ada.See references/capabilities.md for each report's JSON shape.
Report in prose, not raw JSON. Lead with the headline, then cite the drawing's own evidence—entity handles and layers—so a reviewer can act.
0 means the command completed. Compliance may exit 1 when violations
are present; parse its JSON and report the findings rather than treating it as
a command failure.2 means the file is missing or unreadable. Confirm the path and that it
is a valid DXF before retrying.cad-analyze is unavailable, install the prerequisite once and rerun the
requested command.Check a floor plan for ADA compliance
cad-analyze compliance ./plans/level-1.dxf --profile ada --json
Report the violation count and every finding's rule and evidence handles.
Audit drawing quality
cad-analyze health drawing.dxf --json
Report the score, then group issues by severity.
cad-revision apply/bundle writes a new file; the original is never touched.Natural-language editing and agent-mode tool use require a bring-your-own LLM provider and are not exposed here.
references/capabilities.md — JSON shape of each report and how to read it.
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