customize

Name: customize
Author: 0-CYBERDYNE-SYSTEMS-0

Other Community

Repo stars 0
Author updated Live
Author repo nano-core

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

Domain: Other
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: Not required
Operating systems: Linux · Docker
Runtime requirements: Docker
Permissions: Read-only
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 customize.preview

---
name: customize
description: Add new capabilities or modify nano-core behavior. Use when user wants to add channels (Telegram…
category: other
runtime: Docker
---

# customize output preview

## PART A: Task fit
- Use case: Add new capabilities or modify nano-core behavior. Use when user wants to add channels (Telegram, Slack, email input), change triggers, add integrations, modify the router, or make any other customizations. This is an interactive skill that asks questions to understand what the user wants..
- Inputs: target material, constraints, expected output, and acceptance criteria.
- Evidence boundary: follow “Workflow / Key Files / Common Customization Patterns” and do not present inference as author intent.

## PART B: Execution result
- **01** The card summarizes the use case; runtime output centers on “Add new capabilities or modify nano-core behavior. Use when user wants to add channels (Telegram, Slack, email input), change triggers, add integrations, modify the router, or make any other customizations. This is an interactive skill that asks questions to understand what the user wants.”.
- **02** When the source has headings, the agent prioritizes “Workflow / Key Files / Common Customization Patterns” 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; mostly runs locally; usually needs no extra API key.

## Running Rules
- read files, 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: customize
description: Add new capabilities or modify nano-core behavior. Use when user wants to add channels (Telegram…
category: other
source: 0-CYBERDYNE-SYSTEMS-0/nano-core
---

# customize

## When to use
- Add new capabilities or modify nano-core behavior. Use when user wants to add channels (Telegram, Slack, email input)…
- 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 “Workflow / Key Files / Common Customization Patterns” and keep inference separate from source facts.
- read files, 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 "customize" {
  input      -> user goal + target files + boundaries + acceptance criteria
  context    -> Workflow / Key Files / Common Customization Patterns
  rules      -> SKILL.md triggers / order / output contract
  runtime    -> Docker | read files, 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: Add new capabilities or modify nano-core behavior. Use when user wants to add channels (Telegram, Slack, email input), change tr…
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 “Workflow”, “Key Files”, “Common Customization Patterns”, “Adding a New Input Channel (e.g., Telegram, Slack, Email)”, 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 customize 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 “Workflow / Key Files / Common Customization Patterns” 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 / 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.

nano-core Customization

This skill helps users add capabilities or modify behavior. Use AskUserQuestion to understand what they want before making changes.

Workflow

Understand the request - Ask clarifying questions
Plan the changes - Identify files to modify
Implement - Make changes directly to the code
Test guidance - Tell user how to verify

Key Files

File	Purpose
`src/config.ts`	Assistant name, trigger pattern, directories
`src/index.ts`	Message routing, WhatsApp connection, agent invocation
`src/db.ts`	Database initialization and queries
`src/types.ts`	TypeScript interfaces
`src/whatsapp-auth.ts`	Standalone WhatsApp authentication script
`.mcp.json`	MCP server configuration (reference)
`groups/CLAUDE.md`	Global memory/persona

Common Customization Patterns

Adding a New Input Channel (e.g., Telegram, Slack, Email)

Questions to ask:

Which channel? (Telegram, Slack, Discord, email, SMS, etc.)
Same trigger word or different?
Same memory hierarchy or separate?
Should messages from this channel go to existing groups or new ones?

Implementation pattern:

Find/add MCP server for the channel
Add connection and message handling in src/index.ts
Store messages in the database (update src/db.ts if needed)
Ensure responses route back to correct channel

Adding a New MCP Integration

Questions to ask:

What service? (Calendar, Notion, database, etc.)
What operations needed? (read, write, both)
Which groups should have access?

Implementation:

Add MCP server to the mcpServers config in src/index.ts
Add tools to allowedTools array
Document in groups/CLAUDE.md

Changing Assistant Behavior

Questions to ask:

What aspect? (name, trigger, persona, response style)
Apply to all groups or specific ones?

Simple changes → edit src/config.ts Persona changes → edit groups/CLAUDE.md Per-group behavior → edit specific group's CLAUDE.md

Adding New Commands

Questions to ask:

What should the command do?
Available in all groups or main only?
Does it need new MCP tools?

Implementation:

Add command handling in processMessage() in src/index.ts
Check for the command before the trigger pattern check

Changing Deployment

Questions to ask:

Target platform? (Linux server, Docker, different Mac)
Service manager? (systemd, Docker, supervisord)

Implementation:

Create appropriate service files
Update paths in config
Provide setup instructions

After Changes

Always tell the user:

# Rebuild and restart
npm run build
launchctl unload ~/Library/LaunchAgents/com.nano-core.plist
launchctl load ~/Library/LaunchAgents/com.nano-core.plist

Example Interaction

User: "Add Telegram as an input channel"

Ask: "Should Telegram use the same @Andy trigger, or a different one?"
Ask: "Should Telegram messages create separate conversation contexts, or share with WhatsApp groups?"
Find Telegram MCP or library
Add connection handling in index.ts
Update message storage in db.ts
Tell user how to authenticate and test

Install command

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

npx skills add 0-CYBERDYNE-SYSTEMS-0/nano-core/skills/setup/customize -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
0-CYBERDYNE-SYSTEMS-0/nano-core
中文

More by @0-CYBERDYNE-SYSTEMS-0

Category & tags

Category Other

Decide Fit First

Design Intent

How To Use It

Boundaries And Review

nano-core Customization

Workflow

Key Files

Common Customization Patterns

Adding a New Input Channel (e.g., Telegram, Slack, Email)

Adding a New MCP Integration

Changing Assistant Behavior

Adding New Commands

Changing Deployment

After Changes

Example Interaction

Discussion