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cli-coding-agents

AI Community
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
@0-CYBERDYNE-SYSTEMS-0 · no license declared
Token usage
Lean
Setup complexity
Guided setup
External API key
Required · Anthropic
Operating systems
macOS
Runtime requirements
Node.js
Permissions
  • Read-only
  • Write / modify
  • Env read
Network behavior
External requests
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 cli-coding-agents.preview 
---
name: cli-coding-agents
description: CLI Coding Agents. Use when the user request matches this skill's domain and capabilities. Launc…
category: ai
runtime: Node.js
---

# cli-coding-agents output preview

## PART A: Task fit
- Use case: CLI Coding Agents. Use when the user request matches this skill's domain and capabilities. Launch coding agents across Claude, Droid, and OpenCode CLI platforms with unified profile management and flexible configuration. requires Anthropic API key; runs on Node.js. Works with Claude Code, Cursor, Cline and 23 more..
- Inputs: target material, constraints, expected output, and acceptance criteria.
- Evidence boundary: follow “When to use this skill / When not to use this skill / Quick Start” and do not present inference as author intent.

## PART B: Execution result
- **01** The card summarizes the use case; runtime output centers on “CLI Coding Agents. Use when the user request matches this skill's domain and capabilities. Launch coding agents across Claude, Droid, and OpenCode CLI platforms with unified profile management and flexible configuration. requires Anthropic API key; runs on Node.js. Works with Claude Code, Cursor, Cline and 23 more.”.
- **02** When the source has headings, the agent prioritizes “When to use this skill / When not to use this skill / Quick Start” 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, write/modify files, read environment variables; may access external network resources; requires Anthropic API keys.

## Running Rules
- read files, write/modify files, read environment variables; may access external network resources; requires Anthropic API keys.
- Validate with a small sample before expanding scope.
- Return the result, validation criteria, and next iteration options.
Interpretation is structured for decision-making; original keeps the upstream SKILL.md unchanged.

Decide Fit First

  • Core job: CLI Coding Agents. Use when the user request matches this skill's domain and capabilities. Launch coding agents across Claude, D…
  • 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 “When to use this skill”, “When not to use this skill”, “Quick Start”, “Profile Management (All CLIs)”, 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 cli-coding-agents 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 “When to use this skill / When not to use this skill / Quick Start” before expanding.

Boundaries And Review

  • Dependencies: Prepare Anthropic API keys before running a full task.
  • Permissions: Declared permissions include read / write / env-read; 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.

Discussion

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