Goal-driven improvement loop: understand what needs improving, forge a /goal completion condition, then race a different-model Claude against Codex (each in its own git worktree) round by round until the goal is met, summarize, and ship a PR.
Plugin dual-haul from marketplace ccomkhj-skills in ccomkhj/skills. Commands read from the repo's manifest — 12 days ago.
dual-goalPhase 2 of dual-haul. Turns .dualhaul/UNDERSTANDING.md into a /goal-ready completion condition — one measurable end state, a stated transcript-demonstrable check, the constraints that must hold, and a turn cap — written to .dualhaul/GOAL.md plus the literal /goal line for the user to run. Use after
dual-haulAuto-chaining orchestrator for goal-driven improvement. Understand what the user wants improved, forge a /goal completion condition, then race a different-model Claude against Codex (each in its own git worktree) round by round until the goal is met, summarize, and open a PR. Use when the user wants
dual-loopPhase 3 of dual-haul — the per-turn race. Under an active /goal, each turn the orchestrator commissions two independent implementers (a Claude on a chosen model + Codex on a chosen model), each in its own git worktree off the current base commit, then judges both against the goal's stated check and
dual-reportPhase 4 of dual-haul. Fires once the /goal condition is met (the goal auto-clears) or the round cap is hit. Reports goal-vs-achieved with the final check numbers, which racer won each round and why, the net diff that was kept, and what's still open. Writes .dualhaul/SUMMARY.md. Use after dual-loop c
dual-shipPhase 5 of dual-haul — the finishing move. Commits the kept improvement on a feature branch, opens a PR (body drawn from .dualhaul/SUMMARY.md), and tears down the dual-haul worktrees and state. Always confirms the branch name and PR body with the user before pushing. Use as the last phase of a dual-
dual-understandPhase 1 of dual-haul. Improvement-focused brainstorming — assumes the user wants something existing made better, and digs for what's deficient now, what "better" means concretely, and the measurable success signal. Produces .dualhaul/UNDERSTANDING.md. Use as the first phase of a dual-haul run, or st
Solo long-horizon goal loop: sharpen a spec (grill if vague), forge a /goal completion condition, then haul toward it turn after turn in a git worktree — each turn deciding explore (a fresh approach off the base) vs exploit (refine the incumbent), keeping only measured wins on a ratcheting incumbent branch, until the goal holds or the round cap trips. Then wrap up with a PR.
5 skills
Product design loop for an existing Next.js/React app: define the problem, explore competing UX flows, validate the direction, prototype in the real codebase, and hand off a developer-ready behavior spec. Five skills, each usable alone, sharing one experiment record that keeps proposed, done, approved and unverified apart.
5 skills
Harness-native ECC operator layer - 71 agents, 314 skills, 98 legacy command shims, reusable hooks, rules, selective install profiles, and production-ready workflows for Claude Code, Codex, OpenCode, Cursor, and related agent harnesses
200 skills · 98 commands · 71 agents · 1 MCP server · hooks
Interactive self-referential AI loops for iterative development. Claude works on the same task repeatedly, seeing its previous work, until completion.
3 commands · hooks
Open-source AI job search that runs locally in your AI coding CLI: scan job portals, evaluate listings into a structured A-H report with a 1-5 score, tailor your CV, track applications
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5 skills · 1 command · 4 agents
Skill: add headroom-ai compress() to a Python or TypeScript app to cut LLM input tokens (tool outputs, logs, JSON, chat history). No API key.
1 skill
Use Alibaba Open Code Review from local Codex.
2 skills
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