9 skills published by OdradekAI across 2 repositories. Together they weigh 284 291 tokens — that is what loading all of them at once would cost you in context.
9 skills 284 291 tokens total
Use when reviewing a bundle-plugin for structural issues, version drift, skill quality, workflow integration, or security risks — before releasing, after changes, or after adding skills. Auto-detects scope (full project vs skill vs workflow)
Use when writing, completing, improving, or adapting SKILL.md and agents/*.md in a bundle-plugin — integrating external skills, filling scaffolded stubs, or rewriting for better triggering and token efficiency
Use when planning new bundle-plugins, splitting complex skills, combining skills into bundles, or exploring a vague idea about packaging skills
Use when optimizing a bundle-plugin or single skill — improving descriptions, reducing tokens, fixing audit findings, restructuring workflows, adding skills to fill gaps, or iterating on user feedback
Use when releasing a bundle-plugin, bumping versions, fixing version drift across manifests, setting up version sync infrastructure, updating CHANGELOG, publishing to marketplaces, or checking release readiness
Use when generating project structure for new bundle-plugins, adding or removing platform support (Claude Code, Cursor, Codex, OpenCode, Gemini CLI, OpenClaw), updating platform manifests, or migrating hooks and configuration between platforms
Use when testing a bundle-plugin locally before release — generating dev-marketplace environments, verifying component discovery, running hook smoke tests, and validating cross-platform readiness
Use when starting any conversation involving bundle-plugins — blueprinting, scaffolding, authoring, auditing, testing, optimizing, or releasing. Also use when feeling unsure which bundles-forge skill applies
> Audit, design, and implement AI agent harnesses for any codebase. A harness is the constraints, feedback loops, and verification systems surrounding AI coding agents — improving it is the (set up components), Design (full strategy). Use whenever the user mentions harness engineering, agent guardrails, AI coding quality, AGENTS.md, CLAUDE.md setup, agent feedback loops, entropy management, AI code review, vibe coding quality, harness audit, harness score, AI slop, agent-first engineering. Also trigger when users want to understand why AI agents produce bad code, make their repo work better with AI agents, set up CI/CD for agent workflows, design verification systems, or scale AI-assisted development. Proactively suggest when discussing AI code drift or controlling AI-generated code quality.