add-telegram-swarm

Delegate legacy add-telegram-swarm calls to the canonical SKILL.md implementation.

3|1|Updated Feb 10, 2026

Search Tags:#compatibility #delegation #canonical #skill #telegram #wrapper

Ready to run

npx skills add https://github.com/ShalomObongo/nanoclaw --skill add-telegram-swarm-shalomobongo

💬 Prompt for ChatGPT / Claude Chat▼

Please help me install this Agent Skill.
Skill: add-telegram-swarm
Source: https://github.com/ShalomObongo/nanoclaw/tree/main/.claude/skills/add-telegram-swarm
Command: npx skills add https://github.com/ShalomObongo/nanoclaw --skill add-telegram-swarm-shalomobongo

SYSTEM DOCUMENTATION & REQUIREMENTS

What problem does it solve?

Legacy compatibility while updating skill ecosystems by routing execution through the canonical telegram-swarm skill, enabling older wrappers to work without changes.

Core Features & Use Cases

Backward compatibility by delegating to the canonical skill file.
Transparent wrapper behavior that preserves the original skill semantics and enables gradual migration to the canonical location.

Quick Start

Read and execute the canonical add-telegram-swarm skill file located at .codex/skills/add-telegram-swarm/SKILL.md.

Frequently Asked Questions about add-telegram-swarm

High-intent search queries and answers about installing and using this skill.

FAQPage Schema

How does backward compatibility work for legacy Telegram swarm skill wrappers?▼

Backward compatibility for legacy Telegram swarm wrappers works by delegating execution directly to the canonical telegram-swarm skill file, preserving original semantics without modifying logic or configuration.

How do I migrate a legacy Telegram workflow to the canonical skill location?▼

To migrate a Telegram workflow, read and execute the canonical add-telegram-swarm skill file located at .codex/skills/add-telegram-swarm/SKILL.md, which enables gradual migration without breaking older wrappers.

When do I need to use a legacy wrapper for Telegram automation?▼

You need a legacy wrapper for Telegram automation when older workflows depend on the add-telegram-swarm wrapper to invoke the canonical implementation, allowing them to function without changes during ecosystem updates.

Can I modify the canonical Telegram swarm logic through the wrapper?▼

No, the Telegram swarm wrapper delegates execution transparently by reading and executing the canonical SKILL.md without modifying its logic or configuration, ensuring consistent behavior across legacy and canonical paths.

Does the Telegram swarm wrapper require additional dependencies to run?▼

No, the Telegram swarm wrapper requires no additional dependencies to run, as it simply reads and executes the canonical skill file located at .codex/skills/add-telegram-swarm/SKILL.md.

Why does my legacy Telegram wrapper still work after the skill ecosystem update?▼

Your legacy Telegram wrapper still works because it routes execution through the canonical telegram-swarm skill, enabling older wrappers to operate transparently without requiring code changes.