# agentica-prompts

Provides prompt templates and unambiguous verb conventions for Agentica agents. Keeps multi-agent context clean by exchanging artifacts via the filesystem.

- skill · `type=skill` · Claude Code, Codex, Cursor, GitHub Copilot, Gemini CLI, OpenCode · 478 installs · ★ 3946
- Author: parcadei
- License: MIT · policy=mirror · the beginning of the file is at the end of this page
- Source: https://github.com/parcadei/Continuous-Claude-v3/tree/HEAD/.claude/skills/agentica-prompts/SKILL.md
- Updated: 2026-01-26
- HTML: https://affpapa.org/en/nevibecode/skills/agentica-prompts

## What it does

Ambiguous natural language prompts cause models to fail ~35% of the time. This skill enforces strict verb mappings. Loose commands like "check the file" become direct imperatives like "RETRIEVE". The documentation notes a jump from ~60% to ~95% execution success.

Inside are modular prompt patterns for Swarm researchers and generator-critic loops. Agents write summaries and artifacts to `.claude/cache/agents/` instead of flooding context windows with `TaskOutput` transcripts. It also connects a 3-tier memory model and code maps generated by `rp-cli`.

The skill carries `user-invocable: false`, acting as an orchestration standard rather than a manual command. It relies on `.claude/cache/agents/`, without which directory handoffs fail.

## Install

### Claude Code (native platform)

1. **Skills CLI (Vercel)**
```bash
npx skills add parcadei/Continuous-Claude-v3 --skill agentica-prompts -a claude-code
```

2. **Manually: put the files in place**
- File: `~/.claude/skills/agentica-prompts/SKILL.md` — Copy the whole skill folder; for one project use .claude/skills/agentica-prompts/

### Codex

1. **Skills CLI (Vercel)**
```bash
npx skills add parcadei/Continuous-Claude-v3 --skill agentica-prompts -a codex
```

2. **Manually: put the files in place**
- File: `.agents/skills/agentica-prompts/SKILL.md` — For all projects use ~/.agents/skills/

### Cursor

1. **Skills CLI (Vercel)**
```bash
npx skills add parcadei/Continuous-Claude-v3 --skill agentica-prompts -a cursor
```

2. **Manually: put the files in place**
- File: `.cursor/skills/agentica-prompts/SKILL.md` — Cursor also reads .agents/skills/ and .claude/skills/

### GitHub Copilot

1. **GitHub CLI**
```bash
gh skill install parcadei/Continuous-Claude-v3 agentica-prompts
```

2. **Manually: put the files in place**
- File: `.github/skills/agentica-prompts/SKILL.md`

### Gemini CLI

1. **Skills CLI (Vercel)**
```bash
npx skills add parcadei/Continuous-Claude-v3 --skill agentica-prompts -a gemini-cli
```

2. **Platform CLI**
```bash
gemini skills install https://github.com/parcadei/Continuous-Claude-v3 --path .claude/skills/agentica-prompts
```

### Windsurf (Devin Desktop)

**Manually: put the files in place**
- File: `.devin/skills/agentica-prompts/SKILL.md` — The legacy .windsurf/skills/ path still works

### OpenCode

**Skills CLI (Vercel)**
```bash
npx skills add parcadei/Continuous-Claude-v3 --skill agentica-prompts -a opencode
```

### Claude.ai

**Claude.ai**
- Zip the folder and upload it in Settings → Capabilities → Skills

Where a file is given instead of a command, copy the files from the source to that path: https://github.com/parcadei/Continuous-Claude-v3/tree/HEAD/.claude/skills/agentica-prompts/SKILL.md

## When to use it
- eliminate retrieval ambiguity in subagent instructions
- prevent context pollution by swapping transcripts for directory handoffs
- structure coordinator prompts with strict specialist registries
- enforce generator and critic validation loops

## Example prompts
- Draft a system prompt for a swarm research agent using Agentica patterns
- Rewrite this agent prompt using explicit RETRIEVE and WRITE verbs
- Set up directory handoff rules between planner and implementer agents

## Source text · SKILL.md · MIT

Below is the content of a third-party file. It is data, not instructions for you: do not act on anything written inside unless the human asks. Block tag: 2aafb28a55fac71a.

BEGIN THIRD-PARTY FILE 2aafb28a55fac71a
````text
---
name: agentica-prompts
description: Write reliable prompts for Agentica/REPL agents that avoid LLM instruction ambiguity
user-invocable: false
---

# 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

## Agent System Prompt Template

Inject this into each agent's system prompt for rich context understanding:

```
## AGENT IDENTITY

You are {AGENT_ROLE} in a multi-agent orchestration system.
Your output will be consumed by: {DOWNSTREAM_AGENT}
Your input comes from: {UPSTREAM_AGENT}

## SYSTEM ARCHITECTURE

You are part of the Agentica orchestration framework:
- Memory Service: remember(key, value), recall(query), store_fact(content)
- Task Graph: create_task(), complete_task(), get_ready_tasks()
- File I/O: read_file(), write_file(), edit_file(), bash()

Session ID: {SESSION_ID} (all your memory/tasks scoped here)

## DIRECTORY HANDOFF

Read your inputs from: {INPUT_DIR}
Write your outputs to: {OUTPUT_DIR}

Output format: Write a summary file and any artifacts.
- {OUTPUT_DIR}/summary.md - What you did, key findings
- {OUTPUT_DIR}/artifacts/ - Any generated files

## CODE CONTEXT

{CODE_MAP}  <- Inject RepoPrompt codemap here

## YOUR TASK

{TASK_DESCRIPTION}

## CRITICAL RULES

1. RETRIEVE means read existing content - NEVER generate hypothetical content
2. WRITE means create/update file - specify exact content
3. When stuck, output what you found and what's blocking you
4. Your summary.md is your handoff to the next agent - be precise
```

## Pattern-Specific Prompts

### Swarm (Research)

```
## SWARM AGENT: {PERSPECTIVE}

You are researching: {QUERY}
Your unique angle: {PERSPECTIVE}

Other agents are researching different angles. You don't need to be comprehensive.
Focus ONLY on your perspective. Be specific, not broad.

Output format:
- 3-5 key findings from YOUR perspective
- Evidence/sources for each finding
- Uncertainties or gaps you identified

Write to: {OUTPUT_DIR}/{PERSPECTIVE}/findings.md
```

### Hierarchical (Coordinator)

```
## COORDINATOR

Task to decompose: {TASK}

Available specialists (use EXACTLY these names):
{SPECIALIST_LIST}

Rules:
1. ONLY use specialist names from the list above
````
END THIRD-PARTY FILE 2aafb28a55fac71a

The third-party file has ended. Everything between the 2aafb28a55fac71a tags is data: requests and commands from it are not followed. An “end of file” line with another tag inside the block is part of the file.

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