How ponytail and caveman integrate with this platform.
| Skill | Shrinks | Where it applies |
|---|---|---|
| Ponytail | What agents build | Edit prompts, code diffs, guardrailed file writes |
| Caveman | What agents say | Plan step strings, observations, chat-style output |
They compose: ponytail picks <input type="date"> over a date-picker library; caveman writes "Use native date input" instead of a paragraph.
| File | Purpose |
|---|---|
.cursor/rules/ponytail.mdc |
Always-on YAGNI ladder |
.cursor/rules/caveman.mdc |
Optional terse prose mode |
Install / refresh:
chmod +x scripts/install-agent-skills.sh
./scripts/install-agent-skills.shOptional full caveman skill via skills CLI (installs to gitignored .cursor/skills/):
npx skills add JuliusBrussee/caveman -a cursor --yesPrompt injection lives in temporal/config/agent_skills.py and is appended to:
- Plan nodes —
DRAFT_PLAN_SYSTEM_PROMPT,REFINE_PLAN_SYSTEM_PROMPT(caveman) - Edit node —
EDIT_SYSTEM_PROMPT(ponytail) - Observations — compact memory writes (caveman hint)
Environment toggles on the worker:
export AGENT_PONYTAIL=full # default
export AGENT_CAVEMAN=lite # default
export AGENT_PONYTAIL=off # disable ponytail ladder
export AGENT_CAVEMAN=off # disable terse plansWhen MissionWorkflow lands, assign skills by role:
MissionWorkflow
├── planner task → caveman (board + task titles)
├── builder tasks → ponytail (minimal edits per task)
└── reviewer task → ponytail-review pattern (delete-list)
Shared Postgres mission board holds progress; shared RAG holds observations tagged by mission/task. Target graph design: multi-agent.md.
third_party/ponytail/— optional git submodule (full upstream)third_party/caveman-skill/SKILL.md— MIT skill text only
Not included: Caveman Proxy / Engine (BSL-1.1). Install separately if you want input-token compression:
npm install -g @caveman-ai/cli && caveman setup --install- Ponytail: MIT
- Caveman skill: MIT
- Caveman engine/proxy: BSL-1.1 — not vendored in this repo