| name | lope-negotiate |
| description | Draft a sprint doc via multi-round negotiation with AI validators. Lope sends your plan to other AI CLIs (Claude, Gemini, OpenCode, Codex, Mistral Vibe, Aider, Ollama, Goose, llama.cpp, Open Interpreter, Copilot, Amazon Q, or any HTTP API) for independent review. Majority vote. No single-model blindspot. Works for engineering, business (marketing, finance, ops), and research domains. |
Lope Negotiate
Lope uses independent AI validators to critique your sprint plan across multiple rounds until consensus. No single-model blindspot.
This skill is invoked two ways:
- Explicit: the user typed
/lope-negotiate "goal" and expects you to run that exact goal
- Implicit (via
using-lope auto-trigger skill): the user described multi-phase work in natural language and the using-lope skill mapped it to this command. In this case you construct the goal string yourself from the user's prose.
Either way, the flow below is the same.
How it works
- Drafter LLM (the primary validator in the pool) proposes a sprint doc
- Validator pool (2+ different AI CLIs) independently reviews
- On NEEDS_FIX: drafter refines with validator feedback
- Repeats up to 3 rounds until PASS or escalation
Steps
- Determine the goal. If the user typed an explicit
/lope-negotiate "...", use that string. Otherwise extract the goal from the user's natural-language prompt — one sentence, imperative or noun-phrase form, specific enough that a drafter can scope it.
- Pick the domain:
engineering (default) — code, software, technical workbusiness — marketing, finance, ops, management, consultingresearch — studies, academic work, systematic reviews
- Run negotiation:
PYTHONPATH=~/.lope python3 -m lope negotiate "$GOAL" --out "$SPRINT_PATH" --max-rounds 3
PYTHONPATH=~/.lope python3 -m lope negotiate "Q2 product launch campaign" --domain business
PYTHONPATH=~/.lope python3 -m lope negotiate "Systematic review of X" --domain research
PYTHONPATH=~/.lope python3 -m lope negotiate "$GOAL" --context-file ./brief.md
Brief-first workflow for large specs: --context-file is read from disk and inlined into the model prompt. It is not attached as a separate file, and validators do not open it independently. For multi-page specs, create a compact LOPE_BRIEF.md with only the goal, constraints, key evidence, and acceptance gates, then run:
PYTHONPATH=~/.lope python3 -m lope negotiate "$GOAL" --context-file ./LOPE_BRIEF.md --timeout 300
Use the default/global timeout or --timeout 300+ for multi-page negotiate prompts. Do not use short --timeout 120 runs for long context; that makes healthy providers look broken.
- Read and present the resulting sprint doc
- If passed: ask if user wants to proceed to
/lope-execute
- If escalated: present validator feedback and discuss with user
Examples by domain
Engineering:
/lope-negotiate "Add JWT auth middleware with refresh token rotation"/lope-negotiate "Migrate from REST to gRPC for internal services"
Business:
/lope-negotiate "Q4 enterprise launch campaign" --domain business/lope-negotiate "Quarterly financial close process" --domain business/lope-negotiate "Digital transformation roadmap for retail client" --domain business
Research:
/lope-negotiate "Systematic review of LLM alignment techniques" --domain research/lope-negotiate "Ethnographic study of remote team collaboration" --domain research
v0.7 superpowers (opt-in)
lope negotiate "Add JWT auth" --brain-context "prior auth incidents" --brain-log
--brain-context exits 2 outside Makakoo with an actionable error — public
Lope still works without Makakoo OS.
Dynamic sprint mode
Treat the sprint as dynamic. If during work you discover a better approach or have an "aha" moment — do not silently expand scope and do not ignore it. Raise it with your lope teammates, negotiate whether it belongs, and fold it in if agreed.
