matyasstoch/david-skills/delegating-to-agents
Claude Code and agent skill by matyasstoch/david-skills
- community
Checking that the SKILL.md file is still in the repository.
MUST be read ANY time another AI agent is involved — sending a prompt to or polling a Pi/Codex/Claude Code/Hermes/OpenCode agent, driving an agent running in another cmux pane/surface/terminal/tmux window, delegating or relaying ANYTHING to an agent in the same cmux workspace, spawning a sub-agent, or orchestrating agent-to-agent work. Read it BEFORE the first message you send to another agent. Covers the critical rule that prompts sent to a TUI agent must be ONE single line (newlines = Enter =…
Install
npx vskill@latest install matyasstoch/david-skills/delegating-to-agentsSKILL.md
Delegating to Agents
Which agent to pick (most important)
- For most tasks → just open Pi Agent with the
picommand in a cmux terminal. Default Pi agents run on opus-4.8-fast via OpenRouter API at xhigh reasoning effort. - Default for coding → Codex CLI. It's currently the most powerful coding agent — stronger than Claude Code and Opus 4.8 — especially on complex, long-running SWE tasks. Delegate hard/multi-step engineering work here.
- Frontend / design → Pi Agent with Opus 4.8 Fast. For UI, styling, and design work, Pi + Opus 4.8 Fast beats Codex.
- Codex is on David's ChatGPT Pro plan, so usage limits are effectively near-unlimited — don't ration Codex calls to save quota.
- A good setup for complex work: Pi Agent (you) as the orchestrator, delegating execution to Codex CLI running in the right pane in cmux. This isn't the only setup that works, but it's a solid default for heavy, long-running tasks.
Polling cadence — keep sleeps SHORT
General principle: when waiting on another agent, use short sleep intervals so you check often. Don't sleep 30. Start with sleep 3-5; if the agent isn't done, just sleep 5 again and re-check. Scale up only for genuinely heavy tasks.
Sending prompts — NEVER put newlines in the message body
When sending a prompt to a TUI agent (Pi, Hermes, Claude Code, Codex) via cmux send, tmux send-keys, or similar, the message text must be a single line. In these TUIs a newline = Enter, so a multi-line string submits after the first line and the rest arrive as separate mid-turn "Steering" messages — cutting off / fragmenting your prompt.
Fixes (pick one):
- Send the whole prompt as one line (use ". " or "; " instead of line breaks), then one explicit
send-key enter. - For long/multi-step instructions, write them to a file and tell the agent to read it:
cmux send --surface X 'read /tmp/task.md and follow it'thensend-key enter.
Managing a remote VPS via an agent
To have an agent manage a remote VPS, SSH in first and launch the agent ON the VPS (e.g. codex --yolo), then drive that on-box agent — it has full local context and avoids fragile per-command SSH round-trips. Don't run an agent locally and tell it to SSH for every step.
Agent characteristics
- Pi Agent — starts & responds very fast. Usually launches within 1-2s and responds within a few seconds. No need for long waits;
sleep 3-5is plenty. - Pi & Hermes — both run on OpenRouter with
opus-4.8-fast, which responds very fast. Same rule: poll with short 3-5s sleeps, not long ones.
The 4 agents (compressed reference)
Background only — don't over-index on this. All four use the portable SKILL.md standard (~/.{agent}/skills/, project version wins; one folder can be symlinked across all). Pi, Codex, Hermes are model-agnostic (BYOK); Claude Code is Claude-centric.
- Pi (pi.dev, Mario Zechner / earendil-works, open-source TS, npm). Minimal 4-tool core (read/write/edit/bash) that self-extends via TS extensions, skills, prompt templates, packages. True BYOK (Claude/GPT/Gemini/Grok/DeepSeek/local), best-in-class branch/fork/resume sessions, transparent. Weak: smaller ecosystem, assemble-your-own workflow. Skills:
~/.pi/agent/skills/. - Hermes (Nous Research, MIT, Python). Persistent self-improving autonomous agent (not a copilot) — cross-session memory, learning loop that auto-writes reusable skills, 40+ tools, cron/scheduling, subagent delegation, 20+ messaging platforms. Can orchestrate other agents (Codex, OpenCode) as workers. Weak: heavy setup (systemd/server), not IDE-tethered. Skills:
~/.hermes/skills/(project cwdskills/wins). - Claude Code (Anthropic, TS). Deepest model integration, clean
.claude/conventions (CLAUDE.md, rules/, agents/ subagents, skills/plugins), live skill hot-reload mid-session. Skills are injected instructions in the main conversation, not separate processes. Weak: Anthropic-centric, less infra/sandbox tooling. Skills:~/.claude/skills/(personal) +.claude/skills/(project). - Codex CLI (OpenAI, Apache 2.0, ~95% Rust). Fastest startup, low memory; only agent with kernel-level sandboxing (Apple Seatbelt / Landlock+seccomp); strong for CI (
codex exec), MCP, GitHub PR review. ReadsAGENTS.md. Weak: tied to ChatGPT/OpenAI auth, sparse docs, sandbox can change script behavior. Skills:~/.codex/skills/(personal) +.codex/skills/(project).
Driving interactive CLIs
- Codex, Pi, OpenCode: tooling that drives them needs
pty=true. - Claude Code: prefers
--print --permission-mode bypassPermissions(no PTY). - Hermes is the orchestrator/persistent agent — it can drive the coding CLIs, not just be one.
Security
- Security scanPassed, 100 of 100Pattern checks on the skill's files.
- Model reviewNot runA model review is scheduled for the next rescan.
Quality evaluation
- Task evaluationNot runNo evaluation yet. Run one in Skill Studio.
Source
- SKILL.md in the repositoryCheckingskills/delegating-to-agents/SKILL.md
Popularity
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Works with
Any agent vskill installs to: 56 targets in all. These 39 have a page on this site.
- Claude Code
- Cursor
- GitHub Copilot
- Windsurf
- Codex
- Gemini CLI
- Cline
- Amp
- Roo Code
- Goose
- Continue
- Kilo Code
- Junie
- Trae
- OpenHands
- Qwen Code
- AI Agent
- Tabnine Chat
- Sourcegraph Cody
- Amazon Q
- Firebase Genkit
- Sweep
- Devin
- Phind
- Mentat
- Claude Desktop
- Aider
- GPT Pilot
- Plandex
- bolt.new
- v0
- Replit Agent
- Anse
- TypingMind
- BetterChatGPT
- LibreChat
- Warp AI
- Pieces
- Fig AI
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