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gitnexus-lfg — plan → gate → work → review

gitnexus-claude-plugin/skills/gitnexus-lfg/README.md

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gitnexus-lfg — plan → gate → work → review

Thin pipeline orchestrator over three existing skills: gitnexus-plan produces the plan (asking up front how deep to go), the user chooses at a blocking gate to proceed or stop (an explicit deepen request is still honored), gitnexus-work executes it as verified atomic commits, and gitnexus-review reviews the result (the open PR if one exists, else the branch diff against the default branch). One bounded fix cycle for review findings, then a final report. It never pushes or opens a PR on its own.

Invocation

CLIHow to invoke
Claude Code/gitnexus-lfg <task description> or /gitnexus-lfg docs/plans/<plan>.md
Codex CLIAsk: "run the gitnexus pipeline on <task>" (Codex reads AGENTS.md), or install the skill user-level (below)

Codex (user-level install)

cp -r .claude/skills/gitnexus-lfg ~/.agents/skills/gitnexus-lfg

Optionally, for an explicit slash command, create ~/.codex/prompts/gitnexus-lfg.md:

markdown
---
description: GitNexus pipeline — plan (depth asked up front), user gate, work, PR review
argument-hint: <task description or plan path>
---
Use the gitnexus-lfg skill for: $ARGUMENTS

Read `~/.agents/skills/gitnexus-lfg/SKILL.md` (prefer the repo copy at
`.claude/skills/gitnexus-lfg/SKILL.md` when present) and follow its lanes in
order, invoking the real gitnexus-plan / gitnexus-work / gitnexus-review
skills for each lane. Stop at the plan gate for the user's choice.

The three lanes

LaneSkillGate
Plangitnexus-plan (.claude/skills/gitnexus-plan/)Depth asked up front; blocking gate: proceed / stop
Workgitnexus-work (.claude/skills/gitnexus-work/)Structural drift routes back to the plan gate
Reviewgitnexus-review (.claude/skills/gitnexus-review/)One fix cycle max, then report

Threshold governance (maintainers)

The Lane 1 planning boundary (~35 turns) is a promoted benchmark policy from the GitNexus repository's eval/workflow_bench/ paired candidate loop. Re-evaluate it offline whenever the named model or tool harness changes, and at least every 90 days; update the SKILL.md threshold only after the deterministic promotion gate shows no quality regression. Reading agents never self-edit it from a live task.