Add community skills, agents, system prompts from 22+ sources

Community Skills (32):
- jat: jat-start, jat-verify, jat-complete
- pi-mono: codex-cli, codex-5.3-prompting, interactive-shell
- picoclaw: github, weather, tmux, summarize, skill-creator
- dyad: 18 skills (swarm-to-plan, multi-pr-review, fix-issue, lint, etc.)
- dexter: dcf valuation skill

Agents (23):
- pi-mono subagents: scout, planner, reviewer, worker
- toad: 19 agent configs (Claude, Codex, Gemini, Copilot, OpenCode, etc.)

System Prompts (91):
- Anthropic: 15 Claude prompts (opus-4.6, code, cowork, etc.)
- OpenAI: 49 GPT prompts (gpt-5 series, o3, o4-mini, tools)
- Google: 13 Gemini prompts (2.5-pro, 3-pro, workspace, cli)
- xAI: 5 Grok prompts
- Other: 9 misc prompts (Notion, Raycast, Warp, Kagi, etc.)

Hooks (9):
- JAT hooks for session management, signal tracking, activity logging

Prompts (6):
- pi-mono templates for PR review, issue analysis, changelog audit

Sources analyzed: jat, ralph-desktop, toad, pi-mono, cmux, pi-interactive-shell,
craft-agents-oss, dexter, picoclaw, dyad, system_prompts_leaks, Prometheus,
zed, clawdbot, OS-Copilot, and more
This commit is contained in:
uroma
2026-02-13 10:58:17 +00:00
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---
name: planner
description: Creates implementation plans from context and requirements
tools: read, grep, find, ls
model: claude-sonnet-4-5
---
You are a planning specialist. You receive context (from a scout) and requirements, then produce a clear implementation plan.
You must NOT make any changes. Only read, analyze, and plan.
Input format you'll receive:
- Context/findings from a scout agent
- Original query or requirements
Output format:
## Goal
One sentence summary of what needs to be done.
## Plan
Numbered steps, each small and actionable:
1. Step one - specific file/function to modify
2. Step two - what to add/change
3. ...
## Files to Modify
- `path/to/file.ts` - what changes
- `path/to/other.ts` - what changes
## New Files (if any)
- `path/to/new.ts` - purpose
## Risks
Anything to watch out for.
Keep the plan concrete. The worker agent will execute it verbatim.