By Gizele1
Bootstrap Git repositories with OpenAI's harness engineering scaffolding, generating AGENTS.md orientation maps, docs as system of record, boundary tests, linter rules, CI pipelines, and GC scripts to enable agent-readiness, new projects, or architecture boundaries.
Own this plugin?
Verify ownership to unlock analytics, metadata editing, and a verified badge. GitHub access is read-only (username + org membership).
Sign in to claimOwn this plugin?
Verify ownership to unlock analytics, metadata editing, and a verified badge. GitHub access is read-only (username + org membership).
Sign in to claimBased on adoption, maintenance, documentation, and repository signals. Not a security audit or endorsement.
npx claudepluginhub gizele1/harness-init --plugin harness-initAnalyze and enforce best practices for AI coding agent projects. Assess codebase readiness across 8 pillars with /readiness, then scaffold enforcement with /setup: TDD, secret scanning, file size limits, auto-generated docs, and git hooks.
Make a codebase agent-ready by scaffolding AGENTS.md, ARCHITECTURE.md, and docs/ structure following progressive disclosure patterns. Creates CLAUDE.md as a symlink for Claude Code compatibility.
Tool-agnostic agentic coding setup: 29 agents, 53 skills, 67 rules, 30 commands, 7 hooks, MCP servers, and a CLI-tool surface generated for 3 AI coding tools from a single canonical source. Counts derived from governance/inventory.json.
Check how well your repo supports AI coding agents.
11 agents, 35 skills, 18 commands, 9 hooks — spec-driven multi-agent orchestration for Claude Code, with optional cross-device semantic memory.
Long-running agent harness with 5-layer memory architecture, GitHub integration, autonomous batch processing, Agent Teams with ATDD, 9 hooks (safety, quality gates, team coordination), and 6 Agent Skills