AI Agent2026
Implements a Manus-style, file-backed planning workflow for AI agents using a three-file Markdown pattern (task_plan.md, findings.md, progress.md) to persist plans, findings and session logs—reducing context drift and enabling session recovery. Adds IDE/CLI hooks to re-read plans and verify completion.
AI Agent2026
Runs an autonomous agent loop that uses AI coding tools (Amp or Claude Code) to implement PRD user stories iteratively, persisting context via git history, progress.txt and prd.json; designed for small, CI-backed tasks.
AI Agent2026
Teaches LLMs to detect and remove “AI tells” from prose using curated phrase/structure lists, before/after examples, and a 5‑dimension scoring rubric. Delivered as a reusable skill (SKILL.md + reference files) designed to plug into Claude or any LLM workflow for automated style sanitization.
AI Agent2026
Provides a modular collection of marketing “skills” (CRO, copywriting, SEO, analytics, growth engineering) expressed as markdown workflows so AI agents can apply marketing frameworks. Built to plug into Agent Skills–compatible agents like Claude Code and OpenAI Codex.
A concise, four‑principle guideline (as CLAUDE.md or a Claude Code plugin) that teaches LLMs to: state assumptions, prefer simple solutions, make surgical edits, and use testable success criteria — reducing overcomplication and unwanted changes when an LLM edits code.
AI Coding2026
Improves Claude Code's coding behavior with a single CLAUDE.md that prescribes four practical rules—Think Before Coding, Simplicity First, Surgical Changes, and Goal-Driven Execution—to reduce LLM assumptions, overengineering, and unrelated edits.
AI Agent2026
Generates protocol-bound GEP prompts that guide iterative evolution of AI agent behavior from runtime logs, producing auditable EvolutionEvents and reusable Genes/Capsules. Node.js-based and works offline; optional EvoMap network integration enables skill sharing, worker pools and leaderboards while git provides rollback and validation.
AI Dataset2026
Cleaned reasoning dataset of problem→thinking→solution triplets derived from Opus 4.6, provided in Parquet with ~2,160 cleaned rows (original 3,305). Filters remove empty/short/refusal/non‑substantive responses; hosted on Hugging Face under Apache‑2.0.
AI Agent2026
Provides portable agent 'skills' that steer code-generating agents toward higher-quality UI: stronger layout, typography, spacing and image-reference boards. Ships adjustable dials for design variance, motion and density and image→code pipelines for agent-led frontends.
AI Agent2026
Provides a suite of Claude Code skills that guide the full academic pipeline—research, write, review, revise, and finalize—while enforcing integrity gates (citation verification, anti-hallucination checks) and keeping a human-in-the-loop workflow.
AI Agent2026
Convenes 18 deliberately polarized AI personas to produce structured, multi-round deliberations on hard questions across multiple LLM providers. Key features: multi-provider auto-routing, enforced dissent/novelty rules, triad/panel modes and CLI integration for Claude Code/Codex. Good for high-stakes product, strategy, or safety decisions.
AI Agent2026
Automatically evolves Hermes Agent skills, prompts, tool descriptions and code using DSPy + GEPA — mutating text via API calls, evaluating trace-based failures, and selecting variants that pass tests and human PR review. No GPU training required; runs cost roughly $2–$10 per optimization.