Agentica Prompt Engineering

Agentica Prompt Engineering is an AI Engineering skill for Claude Code, published by vibeeval in vibecosystem.

528 stars44 forkson vibeeval/vibecosystemAdded 2026/08/26Repository updated 2026/08/08

ai-agentsai-software-teamanthropicautomationclaudeclaude-codeclaude-skillsdeveloper-toolsdevtoolshooksmulti-agentopen-sourceself-learningvibe-codingvibecoding

Install in seconds

Install Agentica Prompt Engineering

Copy Agentica Prompt Engineering into your Claude Code skills folder. Run the command in your terminal, or review the source on GitHub before installing.

terminal

npx degit https://github.com/vibeeval/vibecosystem/tree/main/skills/agentica-prompts ~/.claude/skills/agentica-prompts

Requires Node.js. Downloads this skill only — not the rest of the repository — into your Claude Code skills folder.

Without Node.js

git clone https://github.com/vibeeval/vibecosystem.git

Clones the whole repository, then copy the skill’s own directory into your skills folder yourself.

In this catalog

Source file: skills/agentica-prompts/SKILL.md in vibeeval/vibecosystem
Installs to: ~/.claude/skills/agentica-prompts
Collection: One of 25 skills cataloged from this repository
Category: AI Engineering — 2451 skills

What Agentica Prompt Engineering does

Agentica Prompt Engineering helps you write prompts that Claude/REPL agents follow reliably by removing ambiguous instructions and using explicit handoff patterns. Use it for multi-agent orchestration, structured outputs, and prompt templates for research, planning, review, and debugging.

Agentica Prompt Engineering is cataloged under AI Engineering on DirSkills. Agentica Prompt Engineering comes from a repository tagged ai-agents, ai-software-team, anthropic, automation and claude.

Documentation

README

Excerpt

Agentica Prompt Engineering

Write prompts that Agentica agents reliably follow. Standard natural language prompts fail ~35% of the time due to LLM instruction ambiguity.

The Orchestration Pattern

Proven workflow for context-preserving agent orchestration:

1. RESEARCH (Nia)     → Output to .claude/cache/agents/research/
       ↓
2. PLAN (RP-CLI)      → Reads research, outputs .claude/cache/agents/plan/
       ↓
3. VALIDATE           → Checks plan against best practices
       ↓
4. IMPLEMENT (TDD)    → Failing tests first, then pass
       ↓
5. REVIEW (Jury)      → Compare impl vs plan vs research
       ↓
6. DEBUG (if needed)  → Research via Nia, don't assume

Key: Use Task (not TaskOutput) + directory handoff = clean context

This is the opening of the README. Read the full README on GitHub.

Frequently asked about Agentica Prompt Engineering

What else does vibeeval publish alongside Agentica Prompt Engineering?
Agentica Prompt Engineering is one of 25 skills that DirSkills catalogs from vibeeval/vibecosystem, the repository it ships in. Its siblings there include AI Slop Cleaner, API Patterns and API Versioning Patterns. Each one is a separate skill with its own page in this directory, installs the same way Agentica Prompt Engineering does, and is maintained by vibeeval in that same repository. The rest of the collection is listed on the vibeeval/vibecosystem page.
How does Agentica Prompt Engineering compare to other AI Engineering skills?
Agentica Prompt Engineering ranks #2106 by stars among the 2451 AI Engineering skills in this catalog. The most-starred ones next to it are Architecture Decision Records, AI-First Engineering and Agentic OS. DirSkills ranks by the star count of the repository each skill ships in, so that order reflects how popular those repositories are rather than any review of Agentica Prompt Engineering against them. Open each page to compare what they document and how they install.