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agentic-engineering

Guidelines and patterns for autonomous agentic task decomposition, subagent delegation, and tool routing.

Skill by medboughrara

IndexedMIT
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Works with Claude Code, Claude apps, Codex, Cursor, Gemini CLI, GitHub Copilot, VS Code, OpenCode, Goose, Windsurf. Read the repository before you give any tool access to your data.

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About

Guidelines and patterns for autonomous agentic task decomposition, subagent delegation, and tool routing.

Use cases: productivity, agent-building

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What this skill can do and what it asks for, from its SKILL.md. Checked Oct 25, 2026.

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  • codeload.github.com · found in install command

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  • ~/.claude/skills/agentic-engineering

What's inside

Skill name
agentic-engineering
Description
Guidelines and patterns for autonomous agentic task decomposition, subagent delegation, and tool routing.
License
MIT
Instructions
17 lines in SKILL.md · view on GitHub

Files (1)

  • SKILL.md

SKILL.md (first lines)

# Agentic Engineering & Task Decomposition Playbook

When executing complex multi-step user goals autonomously:

1. **Task Decomposition & Intent Filtering**:
   - Break large user requests into discrete, verifiable sub-tasks.
   - Use dynamic tool scoping (`ComposioRouter`) to reduce context token overhead.

2. **Reflex & Instinct Evaluation**:
   - Evaluate automatic reflex rules before calling LLM APIs (`agent/instincts.py`).
   - Trigger quantitative pass/fail checks prior to generating natural language summaries.

3. **Verification & Fail-Fast Fallbacks**:
   - Run capability tests and verify return status codes (`status == "success"`).
   - Use multi-tier LLM key rotation and cloud fallback tiers when encountering rate limits (HTTP 429).

From medboughrara/Jarvis-Copilot, MIT.

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Last commit (this folder)
Aug 5, 2026 (2 months ago)

From GitHub (fetched Oct 24, 2026).

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License
MIT
First seen
Oct 24, 2026
Last checked
Oct 24, 2026

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agentic-engineering skill. Agent Mart. https://agentmart.dev/skills/medboughrara-agentic-engineering (last updated 2026-10-24)