anima-common-errors

A model-agnostic agent-skills platform.

审核状态：已审核Quality 72Security 70

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项目 README

来源文件：README.md

抓取于 2026年9月2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.

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, 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."

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/*/`

📦 Live npm Downloads

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:

#	Package	Last 30d
1	`@intentsolutionsio/openrouter-pack`	556
2	`@intentsolutionsio/groq-pack`	496
3	`@intentsolutionsio/databricks-pack`	274
4	`@intentsolutionsio/clickhouse-pack`	273
5	`@intentsolutionsio/wallet-security-auditor`	263
6	`@intentsolutionsio/notion-pack`	258
7	`@intentsolutionsio/elevenlabs-pack`	244
8	`@intentsolutionsio/freshie-inventory-manager`	214
9	`@intentsolutionsio/supabase-pack`	210
10	`@intentsolutionsio/agency-os`	204

_{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:

By category — the table below, regenerated from the catalog on every sync.
By plugin — tonsofskills.com/explore, the full browsable catalog.
By skill — tonsofskills.com/skills, searchable across the whole corpus.
By job to be done — tonsofskills.com/cowork, curated bundles as one-click downloads.
By certification tier — the Certification section below, rendered from the live report.

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).

	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

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:

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

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:

Contribution requirements — including the AI-assistance disclosure expectation.
Skill submission intake standard — the tiered document matrix new plugins ship with.
External-PR review standard — how maintainers triage and what gets a submission merged.

Governance

STANDARDS.md — the public spec posture and the canonical-documents index (one owner per fact class).
The platform master blueprint — CI gates, release, docs governance, and this README's own landing contract.
GOVERNANCE.md · SECURITY.md · LICENSE

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.

开发与工程

中风险

来源需自行核对维护者身份。
包含脚本或命令调用，安装前请复核。
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：3 条。

Codex — Git Clone 安装

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

Codex — 手动复制安装

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

Claude Code — Git Clone 安装

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

Claude Code — 手动复制安装

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

Cursor — Git Clone 安装

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

Cursor — 手动复制安装

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

GitHub Copilot — Git Clone 安装

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

GitHub Copilot — 手动复制安装

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

Windsurf — Git Clone 安装

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

Windsurf — 手动复制安装

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

查看 SKILL.md 原文

name: anima-common-errors
description: 'Diagnose and fix common Anima SDK design-to-code errors.

  Use when encountering Figma token errors, code generation failures,

  node not found issues, or output quality problems.

  Trigger: "anima error", "anima not working", "anima debug", "figma to code error".

  '
allowed-tools: Read, Write, Edit, Bash(curl:*), Grep
version: 1.4.0
license: MIT
author: Jeremy Longshore <jeremy@intentsolutions.io>
tags:
- saas
- design
- figma
- anima
- troubleshooting
compatibility: Designed for Claude Code

Anima Common Errors

Overview

Use this guide to diagnose design-to-code failures without widening design-file access or leaking tokens. Start from a reproducible file/node/settings tuple and use a least-privilege development credential for all verification.

Prerequisites

A sanitized error record with the design file identifier, node identifier, selected generation settings, timestamp, and request ID where available.
Scoped Anima and Figma credentials held in a secret store; never paste a personal access token into a ticket, source file, or shared diagnostic log.
A staging or disposable design fixture so fixes can be reproduced without mutating a production design file.

Instructions

Classify the failure as authentication, file/node resolution, generator configuration, timeout/rate limit, or rendered-output quality.
Reproduce it with the smallest approved frame/component and the diagnostic commands, capturing only sanitized results.
Correct the matching design input, entitlement, or generation configuration and rerun only that fixture.
Validate the generated file location, lint/build result, and visual review before updating a broader component set.

Error Reference

Authentication Errors

Error	Root Cause	Fix
`Invalid Anima token`	Token not provisioned or expired	Request new token from Anima team
`Invalid Figma token`	PAT expired or revoked	Generate new PAT: Figma > Settings > Access Tokens
`Unauthorized`	Token lacks file access	Ensure Figma PAT has file read permission

File & Node Errors

Error	Root Cause	Fix
`File not found`	Wrong file key	Extract from Figma URL: `figma.com/file/{KEY}/...`
`Node not found`	Invalid node ID	Copy node link from Figma: right-click > Copy link
`No renderable content`	Selected a page or group	Select a frame, component, or component set
Empty `files` array	Node is empty or hidden	Unhide layers; ensure node has visible content

Code Generation Errors

// Common generation error handler
async function safeGenerate(anima: Anima, params: any) {
  try {
    return await anima.generateCode(params);
  } catch (err: any) {
    if (err.message?.includes('rate limit')) {
      console.error('Rate limited — wait 60s before retrying');
    } else if (err.message?.includes('timeout')) {
      console.error('Generation timed out — simplify the Figma node');
    } else if (err.message?.includes('Invalid settings')) {
      console.error('Invalid settings combo — check framework/styling/uiLibrary compatibility');
    } else {
      console.error('Generation error:', err.message);
    }
    return null;
  }
}

Output Quality Issues

Symptom	Cause	Fix
Messy layout	No auto-layout in Figma	Convert frames to auto-layout
Wrong colors	Hardcoded hex instead of Figma variables	Use Figma color variables/styles
Missing text	Text is inside masked groups	Flatten masks before generating
Extra wrappers	Deeply nested groups	Flatten group hierarchy
Wrong component names	Unnamed Figma layers	Name layers descriptively

Valid Settings Combinations

Framework	Language	Styling	UI Library
`react`	`typescript`, `javascript`	`tailwind`, `css`, `styled-components`	`none`, `mui`, `antd`, `shadcn`
`vue`	`typescript`, `javascript`	`tailwind`, `css`	`none`
`html`	`javascript`	`css`, `tailwind`	`none`

Diagnostic Script

# Verify Figma token
curl -s "https://api.figma.com/v1/me" \
  -H "X-Figma-Token: ${FIGMA_TOKEN}" | jq '.handle // .err'

# Verify file access
curl -s "https://api.figma.com/v1/files/${FIGMA_FILE_KEY}" \
  -H "X-Figma-Token: ${FIGMA_TOKEN}" | jq '.name // .err'

Output

Error classified and root cause identified
Valid settings matrix for reference
Diagnostic commands for token and file verification

Examples

When a staging generation returns Node not found, compare the copied node ID with the approved Figma link, then run the file-access diagnostic using a scoped development token. Regenerate only that small frame after correcting the ID and confirm files are emitted to the expected generated-code directory. If access is denied, the node remains hidden, or output is empty, stop the run and ask the file owner to correct permissions or visibility; do not expand the token’s scope or substitute a personal token to get past the error.

Error Handling

Failure	Response
Token is invalid, expired, or over-scoped	Stop the diagnostic, replace it through managed secret rotation, and avoid logging the value.
File or node cannot be resolved	Verify the approved link and visibility with the design owner before retrying.
Generator times out or rate-limits	Use bounded backoff or simplify the fixture; do not fan out uncontrolled retries.
Generated output is unsafe or wrong	Keep it out of the main branch, correct source design/settings, and rerun targeted validation.

Resources

Next Steps

For collecting debug data, see anima-debug-bundle.

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