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SkillsMP has collected 17 skills from traylinx/lope. Open a skill to review its source and details.
Showing 17 of 17 collected skills.
Ask every configured validator the same question and return N independent answers — one per model. No sprint framing, no phases, no verdict parsing. Use for any multi-perspective query: 'what do these 5 CLIs think about X?', 'compare how 3 models solve this…
Compare two files across every validator. Each model picks which file is better against explicit criteria (--criteria flag). Tally the picks; print the winner. Use for A/B review, before/after diff evaluation, migration decisions, bake-offs. Criteria is…
Run an Agent-Order-style council deliberation on a decision artifact. Six built-in templates: ADR, PRD, RFC, build-vs-buy, migration-plan, incident-review. The 7-stage protocol — independent positions, anonymized critique, revision, synthesis, rubric review,…
Execute a sprint phase-by-phase with validator-in-the-loop retry. For each phase: implement (code, deliverables, research, etc.) → AI validators review → retry on NEEDS_FIX → advance on PASS. Works with any domain (engineering, business, research).
Run a declarative GRAPH workflow where AI agents negotiate autonomously — no human gates. A flow is a DOT graph: nodes are agent turns, ensemble reviews, shell verify-steps, or judge/routers; edges carry conditions and loops. Each node dispatches into lope's…
Run a sprint with zero-human swarm orchestration. First select implementation agents and escalation agents, then Lope executes phases without further human input. Use when the user says implement the whole sprint, stay out of the loop, use Claude/OpenCode or…
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…
Read stdin as the prompt, fan out to every configured validator, print per-model answers. The composable shell verb — anything that produces text on stdout can feed lope in a pipeline. Per-validator isolation by default: one timeout doesn't kill the run. Pass…
Fan out a file review to every configured validator and collect N independent critiques — one per model. Use for cross-model code review, doc review, contract review, resume review, or any review-shaped task where multiple perspectives catch what a single…
Manage the validator team (add, list, remove, smoke-test) via CLI flags. Trigger on any user request about adding, removing, configuring, enabling, disabling, or testing a validator/teammate/CLI on lope — including 'add openclaw to lope', 'remove ollama from…
Send a question with a fixed list of options to every validator. Each one replies with exactly one option label. Tally the picks; print the winner. Use for decisions where you want multi-model consensus on a pre-defined set of choices — 'should we ship X or…
Use Lope when cross-model perspective helps: multi-phase sprints, flow graphs, ask/review/vote/compare/pipe, team, lope memory, lope deliberate, gate/check, update, or Headroom setup. Trigger on 3+ phases, consequential multi-file work, second opinions,…
Multi-CLI validator ensemble for AI work. Use for multi-phase sprints, single-shot cross-model checks, autonomous flow graphs, evidence gates, team management, persistent finding memory, council deliberation, and self-update. Any AI CLI implements, any AI CLI…
Use when configuring, installing, verifying, or troubleshooting optional Headroom MCP compression with Lope or Lope-installed agent hosts. Covers opt-in Headroom MCP registration, large validator/tool-output compression, Claude/Codex/Cursor MCP status checks,…
Print the complete lope reference into the current session — all modes, flags, domains, env vars, slash-command vs natural-language invocation per host, troubleshooting, and hard rules for agents. Use when the user asks 'how does lope work', 'what can lope…
Query the persistent Lope finding store (SQLite, populated by `lope review --remember`). Use when the user asks 'is this a recurring issue?', 'which files keep getting flagged?', 'show me everything Lope knows about auth.py', 'what was that finding from last…
Generate a scorecard from sprint execution results — per-phase verdicts, confidence scores, duration, overall status. Optionally writes to the lope journal for historical tracking.