agnix

Name: agnix
Author: agent-sh

AI Community

Repo stars 264
Author updated Live
Author repo agnix

Fluxly profile Facts only: domain, agents, trust score, runtime, permissions and network

Domain: AI
Compatible agents: Claude Code
Cursor
Cline
Codex
Windsurf
Gemini CLI

+20
Trust score: 88 / 100 · community maintained
Author / version / license: @agent-sh · no license declared
Token usage: Lean
Setup complexity: Guided setup
External API key: Not required
Operating systems: Unspecified (assume cross-platform)
Runtime requirements: No special requirements
Permissions: Read-only
Shell exec
Write / modify
Network behavior: Local-only
Install commands: 26 variants

Profile is derived at build time from SKILL.md and install vectors. Subject to drift from author intent.

Heads up: 未限定 allowed-tools，默认拥有全部工具权限。

Output preview agnix.preview

---
name: agnix
description: Use when user asks to 'lint agent configs', 'validate skills', 'check CLAUDE.md', 'validate hook…
category: ai
runtime: no special runtime
---

# agnix output preview

## PART A: Task fit
- Use case: Use when user asks to 'lint agent configs', 'validate skills', 'check CLAUDE.md', 'validate hooks', 'lint MCP'. Validates agent configuration files against 422 rules across 10+ AI tools..
- Inputs: target material, constraints, expected output, and acceptance criteria.
- Evidence boundary: follow “Parse Arguments / When to Use / Prerequisites” and do not present inference as author intent.

## PART B: Execution result
- **01** The card summarizes the use case; runtime output centers on “Use when user asks to 'lint agent configs', 'validate skills', 'check CLAUDE.md', 'validate hooks', 'lint MCP'. Validates agent configuration files against 422 rules across 10+ AI tools.”.
- **02** When the source has headings, the agent prioritizes “Parse Arguments / When to Use / Prerequisites” so the result follows the author’s structure.
- **03** Typical output includes task judgment, concrete steps, required commands or file edits, validation, and follow-up options.
- **04** Risk context follows the fingerprint: read files, run shell commands, write/modify files; mostly runs locally; usually needs no extra API key.

## Running Rules
- read files, run shell commands, write/modify files; mostly runs locally; usually needs no extra API key.
- Validate with a small sample before expanding scope.
- Return the result, validation criteria, and next iteration options.

SKILL.md SKILL.md

---
name: agnix
description: Use when user asks to 'lint agent configs', 'validate skills', 'check CLAUDE.md', 'validate hook…
category: ai
source: agent-sh/agnix
---

# agnix

## When to use
- Use when user asks to 'lint agent configs', 'validate skills', 'check CLAUDE.md', 'validate hooks', 'lint MCP'. Valida…
- Use it when the task has clear inputs, repeatable steps, and validation criteria.

## What to provide
- Target material, scope, expected result, and forbidden changes.
- Whether network, commands, file writes, or external services are allowed.

## Execution rules
- Organize steps around “Parse Arguments / When to Use / Prerequisites” and keep inference separate from source facts.
- read files, run shell commands, write/modify files; mostly runs locally; usually needs no extra API key.
- Validate with a small sample before expanding the task.

## Output requirements
- Return the deliverable, key evidence, validation method, and next action.
- Mark missing information as unknown; do not invent commands, platforms, or dependencies.

Evidence boundary and execution chain

The author source anchors workflow facts; repository files anchor sources and commands; Fluxly only adds fit, limitations, and quality judgment.

skill "agnix" {
  input      -> user goal + target files + boundaries + acceptance criteria
  context    -> Parse Arguments / When to Use / Prerequisites
  rules      -> SKILL.md triggers / order / output contract
  runtime    -> no special runtime | read files, run shell commands, write/modify files | mostly runs locally
  guardrails -> usually needs no extra API key + small-sample validation + diff/log review
  output     -> copyable result + checklist + next iteration
}

Interpretation is structured for decision-making; original keeps the upstream SKILL.md unchanged.

Decide Fit First

Core job: Use when user asks to 'lint agent configs', 'validate skills', 'check CLAUDE.md', 'validate hooks', 'lint MCP'. Validates agent…
Best fit: Use it when the task has reusable inputs, steps, and validation criteria rather than a one-off answer.
Avoid forcing it: If the source lacks commands, platform support, or external-service evidence, keep those fields unknown instead of guessing.

Design Intent

Structure: The skill is organized around “Parse Arguments”, “When to Use”, “Prerequisites”, “Execution”, showing how the author expects the agent to judge fit, collect context, and produce verifiable output.
Trigger evidence: Prioritize the author’s wording around when to use it, what context to collect, and what output shape to produce.
Evidence boundary: Author text states facts, repository files prove commands and paths, and Fluxly only adds fit, limits, and usage judgment.

How To Use It

Inputs: Provide target material, scope, expected result, forbidden changes, and validation method.
Invocation: Name agnix directly; if the source includes slash commands, start with the command and then add task context.
Validation: Start small and check whether the result follows “Parse Arguments / When to Use / Prerequisites” before expanding.

Boundaries And Review

Dependencies: It usually needs no extra API key, so start with a small validation task.
Permissions: Declared permissions include read / shell-exec / write; ask the agent to state file, command, and rollback boundaries before acting.
Quality bar: A useful result names the deliverable, evidence, and next action. Generic prose means the task needs tighter context.

agnix

Lint agent configurations before they break your workflow. Validates Skills, Hooks, MCP, Memory, Plugins across 10+ AI tools including Claude Code, Cursor, GitHub Copilot, Codex CLI, OpenCode, Gemini CLI, Cline, Windsurf, Kiro, and Amp.

Parse Arguments

const args = '$ARGUMENTS'.split(' ').filter(Boolean);
const targetPath = args.find(a => !a.startsWith('--')) || '.';
const fix = args.includes('--fix');
const strict = args.includes('--strict');
let target = args.find(a => a.startsWith('--target='))?.split('=')[1];
if (!target) {
  const idx = args.indexOf('--target');
  if (idx !== -1 && args[idx + 1]) target = args[idx + 1];
}
target = target || 'claude-code';

When to Use

Invoke when user asks to:

"Lint my agent configs"
"Validate my skills"
"Check my CLAUDE.md"
"Validate hooks"
"Lint MCP configs"
"Fix agent configuration issues"
"Check if my SKILL.md is correct"

Prerequisites

agnix must be installed. Check with:

agnix --version

If not installed:

cargo install agnix-cli

Execution

1. Validate Project

agnix .

2. If Issues Found and Fix Requested

agnix --fix .

3. Re-validate to Confirm

agnix .

CLI Reference

Command	Description
`agnix .`	Validate current project
`agnix --fix .`	Auto-fix issues
`agnix --strict .`	Treat warnings as errors
`agnix --target claude-code .`	Only Claude Code rules
`agnix --target cursor .`	Only Cursor rules
`agnix --watch .`	Watch mode - re-validate on changes
`agnix --format json .`	JSON output
`agnix --format sarif .`	SARIF for GitHub Code Scanning

Supported Files

File Type	Examples
Skills	`SKILL.md`
Memory	`CLAUDE.md`, `AGENTS.md`
Hooks	`${STATE_DIR}/settings.json`
MCP	`*.mcp.json`
Cursor	`.cursor/rules/*.mdc`
Copilot	`.github/copilot-instructions.md`

Output Format

CLAUDE.md:15:1 warning: Generic instruction 'Be helpful' [fixable]
  help: Remove generic instructions. Claude already knows this.

skills/review/SKILL.md:3:1 error: Invalid name [fixable]
  help: Use lowercase letters and hyphens only

Found 1 error, 1 warning (2 fixable)

Exit codes:

0 - No errors (warnings allowed)
1 - Errors found
2 - Invalid arguments

Rule Categories

Prefix	Category	Examples
AS-*	Agent Skills	Name format, triggers, description
CC-*	Claude Code	Hooks, memory, plugins
MCP-*	MCP Protocol	Server config, tool definitions
PE-*	Prompt Engineering	Generic instructions, redundancy
XP-*	Cross-Platform	Compatibility across tools
AGM-*	AGENTS.md	Structure, sections
COP-*	GitHub Copilot	Instructions format
CUR-*	Cursor	MDC format, rules

Common Issues & Fixes

Issue	Solution
Invalid skill name	Use lowercase with hyphens: `my-skill`
Directory/name mismatch	Rename directory to match `name:` field
Generic instructions	Remove "be helpful", "be accurate"
Missing trigger phrase	Add "Use when..." to description

Integration

This skill is standalone and can be invoked directly via /agnix.

For CI integration, see the GitHub Action.

Install command

One-click installPick a runner, click Copy, paste into your terminal, press enter

npx skills add agent-sh/agnix/plugin/skills/agnix -y

Open general install guide

View skill source

Works with

Claude Code
Cursor
Cline
Codex
Windsurf
Gemini
OpenCode
Roo Code
AAide
+Augment
GitHub Copilot
OpenClaw
KKiro
Junie
WWarp
Goose
Trae
Kilo Code
OpenHands
Amp
Zencoder
CContinue
AIAider
CodeBuddy
CodeGeeX
Replit Agent

Security audit

88 / 100

Community

未声明 license/许可。
未声明 version。
未限定 allowed-tools，默认拥有全部工具权限。

Metadata

Source: github
agent-sh/agnix
中文

More by @agent-sh

A agnix 88

Category & tags

Category AI

agnix

Decide Fit First

Design Intent

How To Use It

Boundaries And Review

agnix

Parse Arguments

When to Use

Prerequisites

Execution

1. Validate Project

2. If Issues Found and Fix Requested

3. Re-validate to Confirm

CLI Reference

Supported Files

Output Format

Rule Categories

Common Issues & Fixes

Integration

Links

Discussion