agentica-prompts
Write reliable prompts for Agentica/REPL agents that avoid LLM instruction ambiguity
npx skills add parcadei/Continuous-Claude-v3 --skill agentica-prompts --agent claude-code
Same command for any agent — swap --agent for codex, cursor, copilot.
Weekly change comes from our own snapshots, not the repository page — it measures attention, not adoption.
# 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: re
- The Orchestration Pattern
- Agent System Prompt Template
- Pattern-Specific Prompts
- Swarm (Research)
- Hierarchical (Coordinator)
- Generator/Critic (Generator)
- Generator/Critic (Critic)
- Jury (Voter)
- Verb Mappings
- Directory Handoff Mechanism
- Anti-Patterns
- Expected Improvement
- Code Map Injection
- Memory Context Injection
Generate codemap for agent context rp-cli --path . --output .claude/cache/agents/codemap.md Inject into agent system prompt
What does the agentica-prompts skill do?
Write reliable prompts for Agentica/REPL agents that avoid LLM instruction ambiguity
How do I install it?
Run `npx skills add parcadei/Continuous-Claude-v3 --skill agentica-prompts --agent claude-code` — it drops the skill into your project so the agent can pick it up. Swap the --agent value for codex, cursor or copilot if you use one of those.
Where does this skill come from?
From parcadei/Continuous-Claude-v3, a repository with 3,879 stars. We read it straight from the repository tree rather than a submitted listing, so what you see here is what is actually published.
Is a popular skill a good skill?
Not necessarily. Stars measure attention, not adoption — a repository can trend for a week and be abandoned. That is why we show the weekly change from our own snapshots next to the total, instead of a single flattering number.